HHS Office of Disability, Aging and Long-Term Care Policy
Health Care Financing Administration
American Association of Retired Persons
This package--distributed at a national conference held at the Harbourtowne Golf Resort and Conference Center, St. Michaels, Maryland on November 20-22, 1996--was prepared by the Office of Disability, Aging and Long-Term Care Policy with the U.S. Department of Health and Human Services (HHS). Additional funding for this conference was provided by the HHS Health Care Financing Administration and the American Association of Retired Persons. For additional information about the study, you may visit the DALTCP home page at http://aspe.hhs.gov/daltcp/home.htm or contact the ASPE Project Officer, Andreas Frank, at HHS/ASPE/DALTCP, Room 424E, H.H. Humphrey Building, 200 Independence Avenue, SW, Washington, DC 20201. His e-mail address is: Andreas.Frank@hhs.gov.
Each conference package tab is/will be available in both HTML and PDF. New tab files will be added as they are electronicly formatted.
"TAB 1: GENERAL CONFERENCE INFORMATION
Map Layout of Harbourtowne Conference Center
Map Layout of St. Michaels and Points of Interest
Accommodations
Barrett's Bed & Breakfast Inn
204 N. Talbot Street, 745-3322
Experience a double jacuzzi tub in front of the fireplace, A/C, queen bed, quilts, private bath plus full breakfast with homebaked bread! Mid-week reduced rates.
Beacon Hall
103 N. Harbor Drive, 745-9494
Elegant, casual, expansive, harborfront home. Sweeping water views from living, dining & guest rooms (queen, twin beds). Home-made breakfast breads. Sailboat, bicycles available.
Best Western St. Michaels Motor Inn
1228 S. Talbot Street, 745-3333
93 rooms. We offer a complimentary continental breakfast during the summer season, two outdoor pools, HBO, ESPN and complete conference and banquet facilities.
Captain's Quarters Bed and Bath
115 E. Chew Avenue, 745-9152
Enjoy a charming, two room suite with private entrance and bath in this quaint 1929 St. Michaels home. Easy walk to shops, restaurants, museums, and the harbor.
Chew Inn Bed & Bath
114 E. Chew Avenue, 745-3243
Walk to the shops, harbor, restaurants, and museums, or borrow a vintage bike and ride. Sleep in an old Victorian home (1889) in quaint comfortable rooms.
Cove Guest House
9241 Deepwater Pt Rd., P.O. Box 681, 745-5142
Casual elegance on the water. Private baths. Restful, peaceful, seclusion near St. Michaels.
Dr. Dodson House Bed & Breakfast
200 Cherry Street, P.O. Box 956, 745-3691
c. 1799 brick home (originally a tavern) near harbor. Enjoy private bathrooms, canopy beds, fireplaces, evening hors d'oeuvres, room service coffee, gourmet breakfasts, bicycles & gracious hospitality.
Fleets's Inn
200 E. Chew Avenue, 745-9678
Elegant home in the heart of St. Michaels. Harbor, shopping, golfing, dining and museums delight you by day. Charming accommodations comfort you at night.
The Getaway Bed & Breakfast
Long Haul Creek, P.O. Box 928, 745-2094
Secluded waterfront tranquility a mile from St. Michaels. King beds, all private baths. English guest house. Huge shade trees, hammocks, bikes, dock & beautiful vistas. QUIET!
Hambleton Inn
202 Cherry Street, 745-3350
On the harbor, Hambleton Inn is a charming retreat with a turn-of the century atmosphere. Five guest rooms decorated with period furniture, all private baths.
Harbor Hideaway
208 E. Chew Ave., 610-941-1019
A charming 2 bedroom vacation home in the heart of St. Michaels. Near harbor and only two blocks from quaint shops and fine dining. Relax & Unwind!
Harbortowne Golf Resort & Conference Center
Route 33, ½ Mile North of St. Michaels, 1-800-446-9066
111 elegantly appointed waterfront rooms overlooking the Chesapeake Bay. Bayview Restaurant, Pete Dye golf course, pool and tennis compliment our complete resort and conference center.
Harris Cove Cottages Bed 'N Boat
Oyster Shell Lane Bozman, P.O. Box 855, 745-9701
Waterfront efficiency, A/C cottages and "tree house units" on Harris Creek. "No breakfast;...wife would kill me! Boat ramp, boats and motors available. Joan and Norm Dreisch, "Cottagekeepers".
The Inn at Perry Cabin
308 Watkins Lane, 745-2200
Enjoy the finest British Hospitality at this award winning Inn rated 5th Best Resort Hotel in USA. Enjoy Breakfast, Lunch, Tea & Dinner. Call for Reservations.
Inn at Royal Oak
Rt. 329, Royal Oak, 745-5053
An historic country inn (c. 1748) on Oak Creek, just 4 miles East. Elegant guest rooms overlooking the water. Small boats, swimming pool and bikes for guests. Waterfront dining.
Kemp House Inn
412 S. Talbot Street, 745-2243
A fine 1807 Georgian house with period furnishings. Central location. Working fireplaces, air conditioning and private bath. General Robert E. Lee spent two nights at this house.
Little House on Chestnut Street
120 W. Chestnut Street, 745-9347
Enjoy your own private, unique 1850's vacation home/bed n' breakfast. Cozy country furnishings, waterview, shady yard and gardens. Charming romantic getaway. Central A/C. Walk to everything.
Parsonage Inn
210 N. Talbot Street, 1-800-394-5519
Restored Victorian home (c. 1883) with 8 guest bedrooms, some with fireplaces, private baths. Parlor, deck, bicycles & gourmet breakfast for our pampered guests. Mobil ***
Rigby Valliant House B&B
123 W. Chestnut Street, 745-3977
Circa 1832 residential B&B on quiet residential street. Easy walk to everything; no parking problem. Enjoy our Great Room, deck, hot tub & outstanding breakfast.
Snuggery Guest House
203 Cherry Street, 745-3558
A charming Victorian Cottage with harbor view. All shops, museum and dining nearby. Guest suite includes canopy bed, private bath and spacious parlor. Continental breakfast.
St. Michaels Harbour Inn & Marina
101 N. Harbor Road, 1-800-955-9001
46 luxurious waterfront suites/rooms, Lighthouse Restaurant and lounge, 60 slip transient marina, conference & banquet facilities, outdoor pool/whirlpool, bike & boat rentals.
Tarr House Bed & Breakfast
109 Green Street, 745-2175
Share the charm & elegance of one of the oldest restored homes in St. Michaels. Harbor views, walking distance to town, fireplaces, private baths & solarium.
The Thomas Harrison House
201 Green Street, 703-816-4021
On the harbor with beautiful waterviews, this c. 1790 retreat is at the center of St. Michaels, period furniture, air conditioning, private baths, fireplaces, bicycles.
Two Swann Inn
Foot of Carpenter St., 745-2929
Be our guest at our Colonial Inn on the harbor. All rooms have harborviews & private baths. Walking distance to town. 2 bedroom cottage available for extended stays.
Victoriana Inn
205 Cherry Street, 745-3368
The gardens & porches of Victoriana offer quiet luxury; relaxation in full view of the harbor. Rooms decorated with antique furniture, A/C, country breakfast, open all year.
Wades Point Inn on the Bay
Wades Point Rd./P.O. Box 7, 745-2500
Enjoy country serenity and Bay splendor at this Historic Inn. One mile jogging and nature trail on 120 acre waterfront farm. All waterview rooms.
Markets and Restaurants
208 Talbot
208 N. Talbot Street, 745-3838
Gourmet cuisine expertly served in a casual atmosphere. Serving Lunch & Dinner Tuesday thru Sunday and Sunday Brunch. Reservations recommended. "When you get to 208 Talbot you've arrived"...Baltimore Sun.
Bay River Gourmet and Espresso Bar
NW Corner Talbot & North Streets, 745-3784
"Seattle-Style" cappuccino bar. The Shore's oldest and finest. Where we believe you can't have too much fun. Iced drinks and gourmet gifts.
Big Al's Seafood Inc.
302 N. Talbot St., 745-2637
"Steamed crabs our specialty". Fresh seafood, carryout, liquor, wine, beer, groceries, ice, decoys, bait, hunting & fishing supplies. Open 7 days. All seafood packed for travel.
Bistro St. Michaels
403 S. Talbot Street, 745-9111
Great New Bistro with wonderfully prepared food in a beautiful/fun setting. Reservations suggested.
The Buttermilk Cafe
306 N. Talbot Street, 745-2224
The New York Times gave these chef/owners 3 stars! Find out why-fresh ingredients, cooked to order. Seafood, steak, chicken & more! Lunch, dinner, take out & catering.
Carpenter Street Saloon
113 S. Talbot, 745-5111
Breakfast, Lunch, Dinner. Steaming waffles, juicy burgers & fresh backfin crab cakes highlight our full menu. Families welcome - or revel in the tavern, til 2 a.m. "Beat Feet to C-Street"
Crab Claw Restaurant
Navy Point, 745-2900
Specializing in fresh Chesapeake Bay Seafood and Maryland Blue Crabs. Open March thru November daily 11:00 a.m. to 10:00 p.m.
Dinghy Dog
112 N. Talbot Street
Delicious all beef hotdogs to carry out. Our pedigrees include - Hebrew National, and Boars Head. Picnic trays with all the trimmings in the heart of restaurant row.
The Inn at Royal Oak
Rt. 329 - Royal Oak, 745-3439
Enjoy waterfront dining on our deck or Victorian dining rooms overlooking Oak Creek. "California grill" featuring the best seafood, pasta and grilled meats with great wines and desserts.
Justine's Ice Cream Parlour
101 S. Talbot Street, 745-5416
"Still the Best on the Bay!" Serving old fashioned sodas, sundaes, non-fat yogurt, malts and thick creamy shakes. Home of the creamsickle shake!
Lighthouse Restaurant
101 N. Harbor Rd., (St. Michaels Harbour Inn), 745-5102
Creative American & Eastern Shore cuisine. Beautiful harbor views for breakfast, lunch, & dinner. Casual atmosphere. Pool bar in-season.
Morsels
205 N. Talbot Street, 745-2911
Creative dining in casual atmosphere. Serving lunch and dinner. Homemade desserts, breads, soups. Reservations appreciated.
Poppi's Restaurant
207 N. Talbot Street, 745-3158
Serving breakfast and lunch from 7 a.m.. Beer, wine and ice cream. Fast service, reasonable prices. "Still the best burgers in town." Dining room or take-out.
St. Michaels Crab House
305 Mullberry Street, P.O. Box 870, 745-3737
In a casual waterfront atmosphere, hot, spicy steamed crabs, fresh seafood, sandwiches, and American favorites served continuously from 11 a.m.. Indoor/outdoor seating. Air conditioned. Credit cards.
Michael Rork's Town Dock Restaurant
125 Mulberry Street, P.O. Box 355, 745-5577
Choice waterfront location, outdoor seating in season. Chef Rork's menu features fresh fish, seafood, prime meats, poultry and vegetarian specialties. Live entertainment weekends May - November.
Two Go
106 N. Talbot Street, 745-9243
Freshly prepared foods to go. Salads, sandwiches, dinner entrees, fresh breads & desserts. Ideal for picnickers, bikers, boaters-or those who don't feel like cooking!
Museums/Galleries
Chesapeake Bay Maritime Museum
Mill Street/Navy Point, 745-2916
Nine exhibit buildings on 18 waterfront acres trace heritage of hemisphere's largest estuary. Lighthouse, boat yard, historic boats, kids' exhibits, decoys, festivals... Open year-round, seasonal hours.
The Cultural Arts Center
103 S. Fremont Street, 745-6107
Gallery and gift shop displays unique local and exotic art and distinctive gifts of outstanding design. Guest artisans are scheduled regularly.
St. Mary's Square Museum
St. Mary's Square, 745-9561
Open May thru October. Hours: 10 a.m. to 4 p.m., Saturdays and Sundays. St. Michaels Historic Walking Tour Brochure available at the Museum.
Service Businesses
Century 21 Today's Choice Realty, Inc.
203 N. Talbot Street, 745-6464
Put the #1 Real Estate Organization in the world to work for you. Residential, Waterfront and Commercial properties. Knowledgeable, professional REALTORS on top of today's market.
Coldwell Banker Latham Realtors
202 S. Talbot Street, 745-9700
Forty-three years of service in Talbot County! Full time Realtors! Open 7 Days a Week! Knowledgeable, professional staff!
Kagan & Associates, Inc.
201 S. Talbot Street, 745-5006
"The Real Estate Professionals." Town, County and waterfront properties. Open 7 days a week with a courteous and knowledgeable fulltime staff.
Nationsbank
305 S. Talbot Street, 745-5066
"Full Service Bank"-around the corner all over the State, ATM, MOST & CIRRUS, Plus American Express, MasterCard & Visa network.
St. Michaels Bank
213 S. Talbot Street, 745-5091
24 Hour automatic teller service (MOST & PLUS). Complete banking services. Affiliate - Mercantile Bank Shares.
St. Michaels Realty
205 S. Talbot Street, 745-3072
Your "Home Town" Realtor. Offering knowledgeable and friendly service 7 days a week. "If we don't have it, we'll find it."
St. Michaels Town Dock Marina, Inc.
305 Mullberry Street, 745-2400
Transient dockage with water and electric, gasoline and diesel fuel, ice, marine store with apparel, publications and boating accessories, swimming pool. Bicycle and runabout rentals.
The Talbot Bank
St. Michaels Village, 745-9166
MOST & CIRRUS 24 Hour Banking, Traveler's Checks. VISA/MasterCard. Full service community bank established in 1885.
Shops and Boutiques
Aileen Arader Boutique
201 Talbot Street, 745-9735
Fabulous finds for the fashion minded. Discover occasion dressing by Nicole Miller, cotton cashmere from Joan Vass, spectacular silks by Magaschoni and accessories to compliment any wardrobe.
Antiques and Collectibles
116 N. Talbot Street, 745-5589
Wonderful variety of antique furnishings, tools, collectibles, primitives, nautical and more! Multi-dealer shop. Great prices! Open 10:00 a.m. till 5:00 p.m..
Antiques and Such, I and II
Talbot & Mulberry Streets, 745-5231
2 Buildings filled with Period furniture and appropriate accessories including porcelains, paintings, silver, prints, textiles and books 745-5231 or 745-5283.
Artiste Locale
203 S. Talbot Street, 745-6580
A showplace of local art featuring pottery, jewelry, baskets, paintings, prints, home furnishings, music & much more. Specialty gifts for every occasion.
B's Stitches at the Brick House
202 N. Talbot, 745-6146
Fine needlecrafts. Handpainted needlepoint canvases, unique cross stitch designs, various wools, silks, cotton and metallic fibers and supplies for needleworkers.
Bags Aloft
207 S. Talbot Street, 745-3954
Canvas and assorted handbags totes and duffels for year round fun! Extensive selection of Vera Bradley Designs - most monogrammed free while you shop! Gifts - Accessories.
Blue Swan
216 S. Talbot Street, 745-9346
"A Christmas Shop For All Seasons." Offering the charms of the Eastern Shore and specially selected gifts from around the world.
Broken Rudder Sportswear
101 N. Talbot Street, 745-9170
Fine embroidered sportswear specially designed with the spirit of St. Michaels & Chesapeake Bay area.
Calico Gallery
212 S. Talbot Street, 745-5370
Charming Eastern Shore Gallery in center of town featuring a wide selection of waterfowl and Bay area prints - cards, delightful music, books, and gifts. Unique toy store upstairs.
Celebrate Maryland
100 S. Talbot Street, 745-5900
Maryland's best Maryland store stocks over 5000 different custom Maryland gifts and souvenirs. For corporate gifts business meetings... Call 1-800-999-8330 for free catalog. Open daily.
Chesapeake Bay Maritime Museum Store
Mill Street - Navy Point, 745-2098
Specially created and selected, all inspired by the Bay -- books, toys, gourmet foods, gifts, model boat kits, boat plans, things nautical. Open daily year-round.
Chesapeake Bay Outfitters
100 N. Talbot Street, 745-5590
The shore's best selection of Woolrich, Columbia, Rockports, Topsiders, Colehaans, Timberlands, plus the Bay's finest tees, sweatshirts, hats, quality resortwear, unique gifts plus kids.
Chesapeake Trading Co.
102 Talbot Street, 745-9797
Bookstore...Music...Espresso Bar amid a festival of artfully selected Apparel, Hats, Jewelry and Gifts. "Steadily Becoming A Bay Tradition." Open eves and all year.
Consignment Treasures
300 N. Talbot Street, 745-6013
"One person's consignment is another person's treasure." Clothes, jewelry, furniture, household items, antiques - fun shop.
Deep Blue Sea Jewelers - St. Michaels
111 S. Talbot Street, 745-2626
Finest selection of handcrafted 14KT/18KT gold & sterling jewelry. Custom jewelry design and repair on the premise. Open year round.
Flamingo Flats
406 Talbot Street, 745-2053
Southwestern, Caribbean, Mexican & Creative American Foods. Hot sauces to artwork, Salsa's to jewelry, Barbecue's to dinnerware. This shop's FUN & HOT. Come visit our Tasting Bar.
Freedom House Antiques & Artifacts
415 S. Talbot Street, 745-6143
A unique concept specializing in fine antiques, artifacts and comestibles; espresso bar café. Our second shop's in an 18th century barn down path off Talbot Street.
Galerie Francaise
211 N. Talbot Street, 745-6329
Visit our collection of authentic antique French posters; Lautrec, Cheret, Cappiello, etc. You will appreciate our unique selection of Provencal accessories for home and family.
Keepers - Orvis
300 S. Talbot Street, 745-6388
Featuring men's and ladies clothing, gifts, and fly fishing tackle also view a fine selection of antique and contemporary decoys. 1-800-549-1872
Kidding Around
500 S. Talbot Street, 745-6328
Childrens new and gently used clothing & accessories. Featuring handmade dresses for Mother & Daughter and matching doll outfits. Special orders taken upon request.
The Mind's Eye
103 S. Talbot Street, 745-2023
St. Michaels most exciting gift gallery. Specializing in unique decorative accessories, whimsical antiques, and romantic garden objects d' art. Open year-round and evenings. Shipping available.
Mulberry Candle Shoppe
105 S. Talbot Street, 745-9951
Candles for everyone, for every occasion. Votives, buoy bells, lighthouse. Patio, garden and formal accessories. Minature train & gargoyle collectibles. "Let us light up your life".
Rings and Things
105 S. Talbot Street, 745-3881
Specializing in charms, chains, rings & costume jewelry. Gold, sterling silver or gold electroplate. Just in, "The St. Michaels Charm". Come in & browse.
Sailor of St. Michaels
214 S. Talbot Street, 745-2580
Recognized as a "Shopping Tradition" by local customers as well as visitors - offering quality and unique sportswear, accessories and gifts for men, women and children. Best assortment of tee shirts that become collectibles.
St. Michaels Candy Company
216 S. Talbot Street, 745-6060
Handmade chocolates, truffles, unique gift items, gourmet foods and accessories, chocolate crabs, Maryland made ice-cream and yogurt. Visit our "hot sauce department".
St. Michaels Pottery Warehouse
407 S. Talbot Street, 745-5919
Always exciting stock of lamps, pottery, porcelain, brass, baskets, candles and more. We offer quality service and merchandise at warehouse prices. Open daily all year.
Shaw Bay Classics
208 S. Talbot Street, 745-3377
Fine ladies apparel shop. Clothing for all occasions, fashion accessories, unusual jewelry, swimwear and coverups. The most complete Geiger of Austria Collection. Open daily.
Spring Cottage Nature Store
104 Railroad Avenue
Fantastic selection of flags. Unique collection of decorative items for the deck, yard and garden. Wide array of backyard birder supplies - baths, feeders and houses.
Sightseeing
Chesapeake Carriage Company
P.O. Box 458, 745-2527
Serving St. Michaels, Talbot County and beyond. Specializing in weddings, tours and carriage rides. "Let Chesapeake Carriage Horse You About the Town!"
Dockside Express Water Taxi & Van Service
P.O. Box 803, 886-2643
Specializing in full service land & water transportation, sunset, moonlight & nature cruises, harbor tours, guided walking tours & step on guide service. Berthed at Crab Claw Restaurant.
Patriot Cruises
P.O. Box 1206, 745-3100
Historic narrated cruises April-November. Special group lunch & dinner cruises, parties, business functions. Berthed at Museum. Cruises depart 11am/12:30pm/2:30/4:00 daily.
Billing Information
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Harbourtowne and Harbor Inn
CHECK OUT TIME FOR EVERYONE IS 11:00 a.m. Friday!!
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SPEAKERS--NON-FEDERAL EMPLOYEES. Your hotel expenses are fully covered except incidentals (e.g., phone calls, etc.). You must check in at Harbourtowne to receive your room assignment and key, and check out to return the key. If you are not staying both Wednesday and Thursday night, confirm this with the hotel staff at check in.
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REACTORS AND OTHER GUESTS, INCLUDING SPEAKERS WHO ARE FEDERAL EMPLOYEES. All reactors or other guests (including speakers who are federal employees), who are staying at either Harbourtowne or Harbor Inn must check in at Harbourtowne. The fee is $115 per night, per person, which includes all meals and lodging fees. Guests staying at Harbourtowne will receive keys and room assignments at Harbourtowne. Guests staying at Harbor Inn will need to register first at Harbourtowne; you will then proceed to Harbor Inn to receive your room key and register for hotel incidentals.
Federal Employees take note!!: Request reimbursement from your agency for "actual/necessary expenses" for Easton, MD.
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Best Western
Guests staying at the Best Western should:
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Register at Harbourtowne to pay for meals. The fee for meals for the entire conference is $82; AND
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Register at Best Western for lodging.
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Shuttle Information
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SHUTTLE INFORMATION BETWEEN HOTELS
Free shuttle service is available throughout the conference between Harbourtowne, the Harbor Inn, and the Best Western. Two shuttles will run continuously from:
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3:00 to 10:00 p.m. on Wednesday
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7:00 a.m. to 10:00 p.m. on Thursday, and
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7:00 a.m. to 3:00 p.m. on Friday
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SHUTTLE INFORMATION FROM HARBOURTOWNE TO BWI AIRPORT
Free shuttle service is available to BWI Airport at the end of the conference. The two shuttles will run at 2:00 p.m. and 4:00 p.m.
TAB 2: INTRODUCTION
Introduction
Welcome to the conference and Harbourtowne! We are glad that you arrived safely, and look forward to working closely with you over the next few days.
The conference, Beyond the Water's Edge: Charting the Course of Managed Care for People with Disabilities, is intended to draw together and present empirical research findings on the experience of people with significant disabilities in managed heath care, particularly how managed care plans affect access to care, service use, quality and cost.
This conference will be successful if it achieves three related goals:
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Educating a large group of academic researchers, government policy experts, state officials, health plan and consumer representatives regarding available research evidence on the effects of managed health care on the lives of people with disabilities.
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Identifying gaps in the knowledge base that need to be filled if managed care organizations are to learn how to effectively serve disabled populations.
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Stimulating new research to support more efficient and effective strategies for the financing, organization and delivery of health and long-term care services to people with significant disabilities.
This notebook contains an overview paper for the entire conference, followed by track papers highlighting what we consider to be some of the interesting questions and issues to guide the group in break out sessions. In addition, we have included presentation materials from authors, separated by track and session.
Many of the data in this notebook are new, and as such, have not been published yet. New data contained in this notebook should not be distributed unless the author personally agrees. The materials are compiled merely for purposes of discussion and debate. It is hoped that much of the new data will be included in the thematic issue of Health Affairs, on managed care and people with disabilities, that will be an eventual product of the research and evaluation data presented at this conference.
Whereas we have tried to make sure that all information is correct at the time of printing, we understand that there will be additional changes that will need to be made. Please forward corrections to us at our fax number 202-401-7733 so that future copies will be correct.
We hope you enjoy your two days in Harbourtowne. If there is anything we can do to make your stay more comfortable, please do not hesitate to let us know.
Conference Overview--Managed Care and People with Disabilities: Demographics, Trends and Policy Issues
Mary Harahan, Ruth Katz, Nancy Miller and Michele Adler
DRAFT: Citations will be included in the final version of this paper
I. INTRODUCTION AND BACKGROUND
This paper sets the stage for a national conference on managed care and disability sponsored by the Office of the Assistant Secretary for Planning and Evaluation in the U.S. Department of Health and Human Services. The conference is intended to draw together and present empirical research findings on the experience of people with significant disabilities in managed heath care, particularly how managed care plans affect access to care, service use, quality and cost.
The conference will be successful if it achieves three goals:
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Educating academic researchers, government policy experts, state officials, health plan and consumer representatives regarding available research on the effects of managed health care on the lives of people with disabilities.
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Identifying gaps in the knowledge base that need to be filled if managed care organizations are to learn how to effectively serve disabled populations.
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Stimulating new research to support more efficient and effective strategies for the financing, organization and delivery of health and long-term care services to people with significant disabilities.
II. PEOPLE WITH DISABILITIES: WHO ARE THEY?
Defining disability for purposes of managed care is complex. The number, age composition, and other characteristics of people with disabilities vary greatly depending on how disability is defined. In addition, while many people have chronic illnesses as a result of a particular health condition, only a subset will experience disability as a result.
First, let's look at alternative ways to define disability. According to the recently released 1994 Disability Supplement from the National Health Interview Survey (NHIS), there are as few as 11.6 million people of all ages with disabilities (if only long-term care needs are used) and as many as 59.4 million (if all measures are used). (See Table 1.)
Of the literally hundreds of ways to define disability, four major disability definitions are examined here. All disabilities result from a physical, mental, or emotional health condition. These four major definitions all refer to disabilities which are expected to last a least a year. It is possible for many overlaps to occur among the definitions. In fact, a sizable number of people are disabled according to all four definitions. The four major disability definitions are:
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Functional: Either (1) limitations in or inability to perform a variety of physical activities (i.e. walking, lifting, reaching); (2) serious sensory impairments (i.e. inability to read newsprint even with glasses or contact lenses); (3) serious symptoms of mental illness (i.e. frequent depression or anxiety; frequent confusion, disorientation, or difficulty remembering) which has seriously interfered with life for the last year; (4) long-term care needs (i.e. needing the help of another person or special equipment in order to perform basic activities and instrumental activities of daily living); (5) use of selected assistive devices (i.e. wheelchairs, scooter, walkers); (6) developmental delays for children identified by a physician (i.e. physical, learning); and/or (6) for children under 5, inability to perform age-appropriate functions (i.e. sitting up, recognizing walking).
The functional definition of disability is the most widely accepted and the most useful for many policy and research purposes. According to the functional definition, there are 47.6 million Americans with functional disabilities: 6.1 million children, 25.7 million working-age adults, and 15.8 million elderly. 11.6 million of these individuals have disabilities severe enough to require long-term care. Those who need long-term care include 400 thousand children, 5.3 million adults aged 18-64 and 5.9 million elderly persons.
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Work Disability: Refers to limitations in or the inability to work as a result of a physical, mental or emotional health condition. About 16.9 million working-age adults (18-64) reported a work disability.
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Perceived Disability: As stated in the ADA, includes those individuals who either reported that they considered themselves to have a disability or that others considered them to have a disability. Slightly over 19 million Americans (2 million children, 11.1 million adults aged 18-64, and 6 million elderly) are perceived by themselves or others as having a disability. The definition of perceived disability is useful for civil rights purposes. It is interesting to note that this figure is considerably lower than the number with functional or work disabilities.
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Disability Program Recipients: Includes persons covered by SSI, SSDI, Special Education or Early Intervention Services, and/or disability pensions. Altogether, 13.8 million people, including 4.7 million children and 9.1 million adults aged 18-64, received benefits from disability programs. Since these programs are not targeted on the elderly, those aged 65 or over were not included in these counts.
If all four definitions are used to define disability, the number of disabled persons in the U.S. increases from 47.6 million people to almost 60 million, of whom 9 million are children, 34.2 million are working-age adults, and 16.2 million are elderly.
The likelihood that a chronic health condition will result in disability varies greatly. In general, the more common a chronic condition, the lower the risk of a disability.
The most common chronic health conditions relate to mental health, mental retardation, cognitive impairment and learning disability.
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Mental Illness: According to the Disability Supplement, of the 23.5 million Americans reporting a mental illness, 5.1 million or 22 percent have long-term care needs, 9.9 million or 42 percent do not need long-term care, but have other functional disabilities, and 8.4 million or 36 percent have no functional disabilities at all.
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Mental Retardation and Other Developmental Disabilities: Of the 6.6 million people reporting mental retardation or a developmental disability, 2.7 million or 41 percent need long-term care, 3 million or 45 percent have a functional disability (but do not need long-term care), and 900 thousand or 14 percent have no functional disabilities.
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Cognitive Impairments: Of the 5.1 million adults who report either Alzheimer's disease, other related dementias, or who report serious problems with confusion, orientation, or memory, 2.2 million or 43 percent need long-term care, 2.4 million or 47 percent have functional disabilities but do not need long-term care, and 500 thousand or 10 percent have no functional disabilities.
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Learning disabilities: Of the 4.5 million people under age 65 who report a learning disability, 900 thousand or 20 percent need long-term care, 2.1 million or 47 percent have a functional disability (not including long-term care), and 1.5 million or 33 percent have no functional disabilities.
NOTE: All numbers in this Section are ASPE/DALTCP estimates from the 1994 Disability Supplement of the National Health Interview Survey.
| TABLE 1: PREVALENCE OF DISABILITY USING ALTERNATIVE DEFINITIONS: 1994 | ||||
|---|---|---|---|---|
| Total | Age 0-17 | Age 18-64 | Age 65+ | |
| US Population | 259,626,000 | 70,023,700 | 158,577,400 | 31,024,900 |
| DEFINITION 1--FUNCTIONAL DISABILITY | 47,601,405 | 6,099,411 | 25,675,901 | 15,826,093 |
| -- With Long-Term Care Needs | 11,583,000 | 392,990 | 5,332,610 | 5,857,400 |
| -- Without Long-Term Care Needs | 36,018,405 | 5,706,421 | 20,343,291 | 9,968,693 |
| DEFINITION 2--WORK DISABILITY | 16,949,000 | N/A | 16,949,000 | N/A |
| DEFINITION 3--PERCEIVED DISABILITY | 19,093,000 | 1,974,400 | 11,111,500 | 6,007,100 |
| DEFINITION 4--DISABILITY PROGRAM RECIPIENT | 13,775,000 | 4,691,700 | 9,083,300 | N/A |
| DEFINITION 1-(Functional) OR 2-(Work) OR 3-(Perceived Disability) OR 4-(Disability Program Recipient) | 59,436,000 | 9,018,700 | 34,235,400 | 16,181,900 |
NOTES ON DISABILITY:
| ||||
| SOURCE: ASPE/DALTCP Tabulations from 1994 Disability Phase I Supplement to the National Health Interview Survey, by Michele Adler and Bob Clark in 11/96 for forthcoming publications. | ||||
III. TRENDS IN THE USE OF MANAGED CARE
The concept of managing health care is not novel--primary care physicians, often seen as the central figure in a well functioning, primary care focused health care system--have long been charged with managing or coordinating the full range of health care needs for their patients. And managed care, in its more recent connotations of risk-bearing entities, still has roots back to the early part of this century. What seems heightened is the focus on the use of managed care to control health care utilization and costs, in contrast to other long standing goals of access and quality. Employers cite cost containment as a principal goal. And most State Medicaid activities focused on managed care have similarly been driven by concerns of costs, accompanied to varying degrees by efforts to link cost containment to an expansion of access. The Medicare program has suffered criticism, whether well founded or not, for not more aggressively encouraging beneficiaries' enrollment in health maintenance organizations.
Although most current discussions of managed care focus on health maintenance organizations and other risk-bearing arrangements, managed care runs a spectrum from a physician or other professional serving as a case manager to risk-bearing entities. A variety of arrangements, such as preferred provider organizations and point of service options, as well as activities, such as prior authorization and utilization review, fall in between. The availability of various provider arrangements differs by insurance status--private, Medicaid or Medicare.
Private Sector
The variety of survey estimates available makes it difficult to firmly fix the number of privately insured individuals enrolled in managed care. For example, a 1994 Foster Higgins survey, which includes only employers with 10 or more employees, reported that 42 percent of employees were enrolled in fee-for-service indemnity plans, 27 percent were in preferred provider organizations, 13 percent were in point of service plans, and 17 percent were in health maintenance organizations. Recently, the trend has been toward a continuing decline in fee-for-service enrollment as fewer employers offer that option, and a move from HMO to POS options within managed care.
Surveys consistently show that managed care penetration varies significantly by firm size. For example, in contrast to the Foster Higgins survey, in 1993, firms with fewer than 25 employees had 78 percent of employees in the fee-for-service system, HMOs covered 8.2 percent, with 3.6 percent in point of service plans. The remaining 8.9 percent of employees in small firms were enrolled in preferred provider organizations. Although a significant number of privately insured people remain in the fee-for-service system, little exists that is not managed in some form. A 1991 HIAA study estimated that at that time, only 5 percent of private insurance was not managed through utilization review or similar activities.
Public Sector--Medicaid
Use of managed care in the Medicaid program has grown rapidly in recent years. In 1983, 3 percent of Medicaid beneficiaries were enrolled in managed care. This is in contrast to 1995, when 11.6 million beneficiaries--almost one-third of beneficiaries--were enrolled in managed care. Growth has been particularly rapid in recent years.
Within the Medicaid program, managed care models include primary care case management, as well as prepaid models with full-risk plans, including both HMOs and health insuring organizations (HIOs), and limited risk prepaid health plans. HMOs have been used in the Medicaid program since 1983, while enrollment in primary care case management models began in 1986. By 1995, 63 percent of plans were full risk plans, 25 percent were partial risk plans, and 12 percent were primary care case management.
Although full and partial risk plans are the predominate provider type, a significant number of beneficiaries are receiving care in primary care case management systems. In 1995, 46 percent of enrollees were in full risk plans, 23 percent were in partial risk plans, and 31 percent were in primary care case management.
Enrollment of beneficiaries who are disabled into managed care systems has dramatically increased. As reported by GAO in a recent study, 17 States had enrolled beneficiaries with disabilities in State-wide or pilot prepaid managed care programs on either a voluntary or mandatory basis. (Note that the report excludes enrollment in the PACE project as well as the Minnesota Senior Health Options project, targeted for implementation in January 1997). Enrollment in these States ranged from less than 1 percent to 100 percent of beneficiaries with disabilities. Across the 15 States with available enrollment data, just over 400,000 beneficiaries with disabilities, or roughly 19 percent of eligible enrollees in those States, were enrolled in prepaid managed care.
Most States exclude their beneficiaries who are most vulnerable--those receiving institutional or home and community-based care under 1915(c) waivers--from participating in prepaid managed care. Of the 17 States, 12 States excluded beneficiaries receiving institutional care, both nursing facilities and intermediate care facilities for the mentally retarded. Ten States excluded beneficiaries receiving 1915(c) waiver services.
Virtually all States have excluded the provision of long-term care services within the capitation rate in their State-wide programs. With the notable exception of the District of Columbia's voluntary program serving children and youth with disabilities, most State efforts to integrate acute and long-term care through capitation models have been small scale demonstration projects.
Public Sector--Medicare
By the close of 1995, over 10 percent of Medicare beneficiaries were enrolled in HMOS; most of that enrollment, 8.8 percent, was in risk-based HMOS while 1.9 percent was in cost based plans. The Congressional Budget Office has estimated that 17 percent of Medicare beneficiaries will be enrolled in HMOs by the year 2002.
Enrollment of beneficiaries with disabilities in Medicare managed care is relatively sparse. According to tabulations from the 1993 Medicare Current Beneficiary Survey (MCBS), approximately 100,000 beneficiaries who are under age 65 and are disabled were enrolled in Medicare HMOs, 3.3 percent of this population. Analyses using the 1994 MCBS (the most recent year available) indicated that beneficiaries who are under age 65 and disabled, report functional limitations, fair or poor health status, or report five or more medical conditions are significantly less likely to be enrolled in an HMO. For example, while 33.9 percent of Medicare FFS beneficiaries report one or more ADL, 23.7 beneficiaries enrolled in HMOs report that number of functional limitations. And while 8.2 percent of Medicare beneficiaries in the FFS sector report their health status as poor, only 4.5 percent of HMO enrollees report their health status as poor.
IV. POLICY ISSUES
People with disabilities frequently face significant barriers in obtaining needed health care services. Many lack health insurance. Those who are insured rely heavily on public funding, through Medicare and Medicaid. Within the insured population, many are underinsured due to conditions on coverage such as pre-existing condition limitations. Further, many consumers with disabilities find that the services they need most, such as personal assistance or durable medical equipment, are not covered. Medical necessity criteria create additional barriers. Finally, because people with disabilities are disproportionately poor, out of pocket costs create an impediment to receiving care.
It is in the context of the current health care system for people with disabilities that policy makers are asking--what are the advantages and disadvantages of managed care solutions for serving people with disabilities? Can managed care address any of the significant health care barriers now faced by this population? What specific features of managed care systems appear most effective and how can they be put into practice? How can managed care systems effectively address and prevent problems of access and quality, in a cost conscious manner?
Managed health care arrangements potentially hold great promise for people with disabilities given the emphasis on preventative health care services, care coordination/management, flexibility in service delivery, continuity of care across settings and the ability to reduce or eliminate co-payments and deductibles. At the same time, the economic incentives inherent in managed care, in combination with a lack of knowledge and experience on the part of policymakers, plans and providers regarding how to make managed care work for disabled populations, could be potentially harmful.
The challenges and opportunities facing managed care systems as they expand to cover new, more vulnerable populations such as the SSI disabled and frail or chronically ill elderly Medicare beneficiaries are complex. For example:
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Disabled populations are significantly heterogeneous; definitions of disability are varied and represent vastly different perspectives and policy and service implications;
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The attitudes of disabled people, providers and policy makers about the meaning of disability can be significantly different; many disabled people emphasize what they can do rather than focusing on limitations: public policy tends to focus on identifying limitations as the criterion for receiving assistance;
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Disabled consumers frequently demand control over their own lives and the desire to exercise the maximum degree of choice possible; managed care systems, almost by definition put limits around personal choice;
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People with disabilities frequently need life long assistance from social and supportive services in addition to primary and acute care services; these services are rarely included in a managed care plan's benefits.
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People with disabilities frequently receive health and supportive services from multiple payment sources and programs; managed care models have to address the coordination of services across programs as well as within a single program or insurance plan. This requires the coordinated purchasing of services by payers as well as integrated service delivery by managed care plans.
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Payers, insurers and providers face great uncertainty in trying to calculate the costs and benefits of providing the services deemed most important by the disability community; for example, there is very little conclusive information on the efficacy of home health services, physical therapy, occupational therapy and other rehabilitation benefits, particularly what quantity of such services is necessary to maximize outcomes.
This section of the paper identifies the key policy questions which need to be addressed in defining how managed health care arrangements should relate to disabled populations. The underlying question is: can managed care work for people with disabilities? If the answer is yes, what are the special considerations in structuring financing, service delivery, quality assurance, and information systems so that people with disabilities have the best experience possible and costs are controlled? Through this paper and the conference for which it was prepared, ASPE seeks to apply research findings to the formulation of the answers.
As we contemplate these policy questions, it is important to do so from several perspectives--most notably, that of the consumer, policymaker, individual provider, managed care organization and of course, ultimately, the taxpayer. All have a stake in identifying issues and answering questions, but the issues of concern and the favored approach will vary considerably depending on point of view and the consequences. For example, how to define and manage the benefit package can be looked at from several perspectives. Payers may want to know how to insure that payments made to plans offer incentives to neither underserve or over serve their customers. Consumers may want a wide range of choices and easily accessible services with minimal prior authorization so that if out of plan services are the preferred ones, they are attainable. The managed care organization may be concerned about offering the highest quality services to a particular group of people with chronic disease and or disability without risking adverse selection if too many such people discover how good they are.
If managed health care arrangements are to succeed in serving people with disabilities, it will be critical that all relevant stakeholders have the information and tools they need to answer these questions and others like it. The remainder of this paper discusses key disability related policy issues.
The overarching issue is whether or not managed care arrangements can be made to work for people with disabilities and still reduce spending over the fee for service system. Conversely, should a strong fee for service system be maintained for people with special health care needs? If so, can the fee for service system be improved to meet the needs of people with disabilities and contain or reduce spending--without creating two separate systems, one for people with special needs and one for everyone else?
People with disabilities report that they frequently experience difficulty accessing high quality, individualized health care services. These complaints have arisen mostly from people in fee for service systems, because until recently, people with disabilities have not had much experience with managed care. As managed care gains more hold, consumers fear that problems they currently experience in the fee for service system will grow worse, and fragile, hard-gotten relationships with trusted providers will be disturbed--all in the name of cost savings.
The disability community has been vocal in its criticism of managed care, fearing that access and quality of care problems will be exacerbated. Nevertheless, the movement of states to mandate the participation of SSI populations in Medicaid managed care and the accelerating participation in Medicare risk contracting guarantees that many more disabled persons will become managed care enrollees. A key role for the policy research and evaluation communities is to assess how well managed care plans are able to serve vulnerable populations in comparison with more traditional fee for service arrangements and how the potential benefits of managed care can be maximized. Managed care, broadly defined, has the potential to be a positive force in shaping services for people with disabilities by increasing the range of treatment options, enhancing coordination and continuity of care, conserving scarce resources and using outcome data to improve treatment.
A second key question is how to make the financial incentives inherent in managed care compatible with the needs of people with disabilities. In other words, how can a viable managed care market be created in which plans truly compete for market share on the basis of price and quality, not on questionable enrollment strategies?
Financial incentives which would encourage health plans and providers to include people with significant disabilities in managed care are largely lacking in today's system. Health plans which seek to develop high quality programs for populations with special health care needs risk attracting a concentration of high cost persons. Unless a specialized payment source also accompanies their enrollment, plans will experience large financial loses causing them to raise premiums, ultimately driving out healthier, lower cost people. If plans are to be encouraged to effectively serve disabled populations, financial incentives must be created to reward this behavior. Risk adjustment strategies have been proposed as one solution to this dilemma and are being tested for both Medicare and Medicaid enrollees. The question is whether risk adjusters can be crafted to encourage plans to enroll people with disabilities and serve them well and also discourage plans from drawing down higher rates and large profits while avoiding disabled people with higher costs. The jury is out on this key question. It is clear that much more empirical work is needed before plans and payers are comfortable with setting premium rates to account for the potential costs of serving people with significant disabilities.
Should people with disabilities be incorporated into mainstream health plans or should plans specialize in serving vulnerable populations?
One approach to limiting risk to health plans for serving disabled populations is to develop specialized "carve outs" for high cost populations for whom risk sharing arrangements are difficult to create (e.g., persons with chronic mental illness, children with severe disabilities, the MR/DD population, HIV/AIDS). States have typically developed carve outs for a discrete set of specialty services; primary and acute care services usually remain with the state's mainstream plans and providers.
For many years, some states have carved out their behavioral managed health services to limit expensive and often unnecessary inpatient care and substitute early intervention and a much more comprehensive network of services in the community. The motivation was to both manage speciality services more effectively and to protect and insure a funding stream for the community providers of these services. More recently, several state programs are attempting to carve out new categories of the disabled population and place them in specialized managed care plans; e.g., the District of Columbia's Health Care Services for Children with Special Needs, an example of a major carve out of a special population, which integrates acute and long-term care services under a single provider with a capitated rate for Medicaid eligible children with disabilities; Rhode Island's CHOICES program, which will provide services to people with mental retardation and other developmental disabilities; and the Wisconsin ICARE program, a specialized care plan for people with severe disabilities.
There is not a lot of empirical information available to judge the efficacy of carve outs versus mainstream approaches to serving people with disabilities in managed care. From the viewpoint of the consumer, considerable skepticism has been expressed about equal access to care in a "separate but equal" health care system--many people with disabilities fear that care in a "disabled only" system will be severely constrained and of inferior quality. Issues related to potential violations of the Americans with Disabilities Act have been raised. It is also not clear that carve outs are successful strategies for maintaining adequate levels of funding to speciality services. The more visible and highly regarded the speciality program, the more it may attract very sick and high cost people, requiring more and more services and requiring upward adjustments in payment rates. This phenomenon may be difficult to defend to state legislators seeking Medicaid cost savings. Also proponents of main streaming believe it is easier to demonstrate the efficacy of specialized services in a more integrated plan where the expectation is that by providing them the need for acute services will be reduced.
Should the financing and delivery of acute services and long-term care be integrated to assure continuity of care, and if so, to what extent?
Many people with disabilities have acute and long-term care needs...particularly needs for home care, personal assistance services and rehabilitation services. In general managed care coverage does not include long-term care benefits which are largely funded through Medicaid (although increasingly, with respect to home health, through Medicare as well) and through out of pocket payments. Further, private health care insurance typically excludes long-term care coverage.
Among the potential benefits of integrating acute and long-term care services are: provision of a comprehensive service package that recognizes the dynamic interaction of the acute and chronic needs of people with disabilities; reduced fragmentation of services and more consistent, cost effective care across time, place and profession; and, potential for costs savings by substitution of less expensive home and community based services for hospital and nursing home care.
Models that integrate acute and long-term care typically have one or more of the following characteristics, although experience has shown that none of these alone or in combination ensures that a system is integrated:
- a combination of acute and long-term care financing and service delivery for an elderly or disabled population or subpopulation;
- an organized continuum of services and providers;
- incentives for cost containment such as: prepayment, full or partial capitation, case management fees, utilization review;
- a case management function designed to assure continuity of care over time and across separate service delivery systems; and
- specialized training for providers so they are aware of the full array of services and providers and know how to help consumers access them.
Achieving effective integration of acute and long-term care has proven enormously difficult both with respect to financing and service delivery. A particularly nettlesome problem is how to effectively finance and serve the dually eligible population...that is persons who are eligible for both Medicare and Medicaid within an integrated care model. Considerable attention needs to be paid to identifying and evaluating approaches to integrating services across funding streams as well as the feasibility of integrated funding.
Much of the research on the integration of acute and long-term care has been conducted through several federal demonstration projects (SHMO, PACE, Evercare etc.). A variety of other demonstrations are under development or in the early phases of implementation. Although all intend to provide integrated acute and long-term care services, the models are designed for different subsets of people with disabilities, and test a variety of benefit packages, case management models, payment approaches, and financing streams. Questions have been raised about the effectiveness of the current models in achieving service delivery coordination between primary care providers and community based providers. Evaluation results will be critical in an effort to develop effective, responsive models of managed care for people with disabilities.
How can the values of consumer choice and empowerment be reconciled with managed care service organization and delivery?
A fundamental value within the disability community is the concept of consumer choice. People with disabilities and their advocates articulate a need for self-determination. This is especially notable in the personal assistance services (PAS) arena for people with physical disabilities. Rather than rely on formal, agency-directed services, some consumers (particularly younger ones) are seeking flexible policies that allow them to hire, train, and--if necessary--fire the individuals who help with their daily living tasks. This is in direct contrast to the traditional personal care service mode, under which an agency employs, trains and assigns individual providers to a person.
As consumers with disabilities and their representatives contemplate moving into managed care, respecting choice and empowerment is a frequently raised theme. Should participation by people with disabilities in managed care always be voluntary? Many states are mandating the participation of welfare recipients and, increasingly, SSI recipients into managed care. What information do people with disabilities need to have to make informed choices with respect to plans and benefits? Should consumers be able to move at will in and out of a particular plan?
Can plans manage care, assure quality and control costs if enrolles are able to switch plans with almost no advance notice? This issue becomes more complex for plans serving individuals who are eligible for both Medicaid and Medicare, since Medicare allows consumers extensive flexibility to move among managed care and fee for service plans.
Another question relates to choice of providers. Generally, consumers enrolled in fee for service arrangements have more say than those in managed care about who will provide their primary and specialty services. For a person with a disability, for whom it may be very difficult to find a knowledgeable provider, choice issues are critical. For example, we have learned anecdotally that there is only a handful of gynecologists who know how to provide prenatal and childbirth services to women with paraplegia. To ensure healthy outcomes for both mother and child, it may be necessary for plans to have special arrangements to enable women with paraplegia to see these providers. Alternatively, plans may need to provide more training to expand the pool of qualified, available providers.
Most disabled consumers and their families strongly believe that they should be able to choose between fee for service and managed health care, as well as have a wide range of choices between managed care plans, if this is what they opt for. They also seek broad choices in individual providers.
Achieving consumer choice with respect to service benefits is somewhat more complex. How can concepts of choice and self determination be appropriately applied to acute and primary care...regardless of whether the consumer has a disability and whether the health care is a fee for service or managed care plan. Clearly, certain protocols must be followed in the practice of medicine and certain professional and technical skills are required. An individual does not typically self diagnose an infection and choose an antibiotic. On the other hand, under some circumstances, it may be perfectly reasonable for a person who needs to increase range of motion to decide not to visit a physical therapy center twice a week and choose instead to have the help of a family member for daily exercises, with monthly consults with a physical therapist.
Consumers, managed care organizations, policy makers and other stakeholders will need to agree on the boundaries of choice in the provision of acute and primary care. Consensus may be difficult between professionals and consumers and between consumer groups where younger disabled persons may be far better equipped to manage their health care than most frail older people.
There are several related issues in the arena of choice of providers. First, many physicians and other practitioners are unprepared to serve people with disabilities--even when the disability is unrelated to the reason for seeing the doctor. In order for consumers to have meaningful choice, there must be more than one or two providers from whom to choose. In addition, plans must be responsible for educating consumers and giving them information about quality and access, in order for consumers to make viable choices.
Finally, it is important to examine and reconcile how choice principles will apply to integrated care models. For instance, if a consumer is receiving cash to hire and direct his or her own personal care provider, how will that provider and the consumer interact with the case coordinator from the managed care organization where the consumer receives primary and acute care services?
How should accountability be institutionalized in a managed system of care?
Our ability to specify health care outcomes for people with disabilities is in a much less advanced stage than it is for non-disabled populations. Measures of effectiveness for impaired and disabled populations are almost universally lacking from today's efforts to develop quality assurance systems and performance measures. Combining quality assurance activities designed in a demonstration context, such as the quality assurances system under development for PACE, with efforts to include measures that monitor care for those with disabilities in ongoing programs, such as the addition of functional measures to Medicare HEDIS, are critical as we strive to more effectively assess the quality of care provided by managed care systems.
Further, the ability to compare how people with disabilities fare in the fee for service system relative to various managed care settings, is important but methodologically complex. The work of the Foundation for Accountability (Facct) is particularly important in this respect.
A most important key to accountability is likely to be the existence of educated and informed consumers and their families who have access to the information they need to select among plans and providers and the ability to leave plans with unacceptable levels of quality. Maximizing choice is probably the best option for achieving accountability and quality in the long run.
How can plan and provider capacity be developed to address the health and long-term care needs of people with disabilities?
Critical design questions must be addressed before managed care systems are fully prepared to serve people with disabilities and chronic conditions. Two key operational questions concern the design of benefit packages to ensure that specialized services are available and the development of a managed care workforce.
From the consumer's perspective, the success of managed care systems in serving those with disabilities hinges heavily on the breadth and flexibility of benefits and access to them. From the perspective of the provider, the benefits offered may seriously affect financial risk. Areas of particular concern include access to ongoing rehabilitation services (physical, occupational, and speech-language therapies), assistive technologies, and mental health supports. Adaptive equipment coverage is another key area of concern--surrounded by many questions from consumers: can a managed care plan accommodate my growing child as his or her equipment needs change? How can I be sure that my wheelchair or crutches will be customized to me, and not provided "off the shelf?" Another important consideration in designing service packages is whether and how special transportation needs will be addressed. Not surprisingly, although consumers are generally satisfied with the Oregon Health Plan, which includes the SSI disabled population in mainstream Medicaid managed care plans, these are some of the main concerns they cite with the plan. Others wonder whether it is even reasonable to expect the managed care plan to provide these and other services when these services are not covered under the fee for service program.
In addition to identifying and defining the services to be covered, managed care organizations aiming to serve people with disabilities must also address the issues of annual or lifetime caps to limit use of these services, the role of gatekeepers and primary care case managers in accessing these services, and, maybe most important, who should pay for them and how they should be paid for. In the example of rehabilitation services, current private and public plans are struggling with these very questions. Anecdotal evidence suggests that private managed care (and some fee for service) plans are increasingly limiting coverage for the therapies. Provider reluctance to cover long-term rehabilitation services is based on a lack of information about costs in combination with limited knowledge about the necessary intensity and duration of services needed to improve outcomes. This lack of information makes it difficult for providers to accept financial risk.
A related problem for plans as they make the necessary changes in order to serve a range of individuals with disabilities and chronic conditions is the challenge of developing a workforce that is prepared to address the full range of care needs of the consumer (and family) and coordinating hiring and training efforts to achieve this goal. Graduate programs in medicine, nursing, and therapy programs, among others, have tended not to focus on interdisciplinary work, or the interactive and interdependent role of health care provider and person with a disability, and in-service training programs often overlook the need. A recently reported study indicates that most medical schools have not even kept pace with the shift to managed care for the general population. As a result of the lack of preparation, individual professionals serving people with disabilities create their own networks of providers with whom they work, with varying degrees of success. But much work needs to be done to develop models of training and service delivery that embrace the values of communication and teamwork in serving people with disabilities who have multiple and complex needs. The field of geriatrics provides a framework that may be useful in designing educational and practice guidelines in this regard.
V. CONCLUSION
It is the hope of the sponsors of this conference that research presented over the three day meeting will lead to discussion and additional inquiry that advances our knowledge of managed care and its applications and implications for people with disabilities. Further, conference participants are encouraged to debate these policy issues thoroughly and identify additional concerns.
TAB 4: AGENDA
One Page Agenda
Full Agenda
WEDNESDAY, NOVEMBER 20, 1996
- 7:00-9:00pm Dinner and Keynote Address
- Speaker: Jack Ebeler, Department of Health and Human Services (Bio)
- Speaker: Mary Harahan, Department of Health and Human Services (1996 Report)
- Speaker: Theresa Varner, American Association of Retired Persons (Bio)
- Speaker: Robyn Stone, Department of Health and Human Services (Bio)
- Keynote Address: John Hockenberry, NBC News (Bio)
THURSDAY, NOVEMBER 21, 1996
- 8:00-10:15am PLENARY: Can Managed Care Serve People with Disabilities? The Policy Debate...The Need for Research
- Moderator: Trish Riley, National Academy for State Health Policy
- Panelist: Michael Bailit, Massachusetts Division of Medical Assistance
- Panelist: Allan Bergman, United Cerebral Palsy Associations
- Panelist: Sandra Harmon-Weiss, U.S. Healthcare
- Panelist: Robyn Stone, Department of Health and Human Services (Bio)
- 10:30am-12:30pm First Breakout Sessions
- TRACK I: Impact of Managed Care on Children with Disabilities
- TRACK II: Managing Acute Care
- TRACK III: Consumer Satisfaction
- TRACK IV: System Design Issues
- 12:45-2:00pm PLENARY: Funders Roundtable
- Moderator: Robyn Stone, Department of Health and Human Services
- Panelist: Betty Jo Berland, Department of Education
- Panelist: Mary Harahan, Department of Health and Human Services (1996 Report)
- Panelist: James Knickman, Robert Wood Johnson Foundation
- Panelist: Nancy Miller, Health Care Financing Administration (1996 Report)
- Panelist: Donna Regenstreif, John A. Hartford Foundation
- Panelist: Diane Rowland, Kaiser Commission on the Future of Medicaid
- Panelist: Stephen Somers, Center for Health Care Strategies
- 2:15-4:15pm Second Breakout Sessions
- TRACK I: Impact of Managed Care on Adults with Mental Illness
- TRACK II: Managing Long-Term Care
- TRACK III: Quality Measures in Managed Care Settings
- TRACK IV: Plan Models
- 7:00-9:00pm DINNER PRESENTATION: Dark Side of the Loon
- Speaker: Paul Spitzer, Cooperative Oxford Laboratory
FRIDAY, NOVEMBER 22, 1996
- 8:30-10:30am Third Breakout Sessions
- TRACK I: Impact of Managed Care on Adults with AIDS or Physical Disabilities
- TRACK II: Integrating Acute and Long-Term Care
- TRACK III: Quality Outcomes
- TRACK IV: Risk Adjustment/Rate-Setting
- 10:45am-12:15pm PLENARY: What Do We Know? Where Do We Go From Here?
- Moderator: Trish Riley, National Academy for State Health Policy
- Panelist: Brian Burwell, The MEDSTAT Group(1996 Report)
- Panelist: Judith Feder, Georgetown University
- Panelist: Robert Hurley, Virginia Commonwealth University
- Panelist: Shoshanna Sofaer, George Washington University
- Panelist: Sandra Tanenbaum, Ohio State University (1996 Report)
- 12:30-2:00pm LUNCHEON ADDRESS: Opportunities and Challenges for the Disabled in Managed Care
- Keynote Address: Bruce Vladeck, Health Care Financing Administration
TAB 5: List of Participants
Michele Adler, Disability Policy Analyst, Department of Health and Human Services, Office of Disability, Aging and Long-Term Care Policy, Room 424E, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-6172; FAX (202)401-7733, madler@osaspe.dhhs.gov (1996 Report)
Deborah Allen, Director, Division for Children with Special Health Care Needs, Department of Public Health, 250 Washington Street, Boston, MA 02108-4619, (617)624-5070, 624-5959; FAX (617)624-5990, allende@world.std.com (Bio) (Presentation)
Polly Arango, Director, Family Voices, P.O. Box 769, Algodones, NM 87001, (505)867-2368; FAX (505)867-6517, jbapea@usa.net
Arlene Ash, Ph.D., Research Professor, Boston University School of Medicine, 720 Harrison Avenue, Suite 1108, Boston, MA 02118, (617)638-8188; FAX (617)638-8026, aash@acs.bu.edu
Sara S. Bachman, Ph.D, Project Manager, The MEDSTAT Group, 125 Cambridge Park Drive, Cambridge, MA 02140, (617)492-9330; FAX (617)492-9365, sbachman%medstat@mcimail.com
Michael H. Bailit, Assistant Commissioner, Massachusetts Division of Medical Assistance, 600 Washington Street, Fifth Floor, Boston, MA 02111, (617)348-5510; FAX (617)348-8577, bailit@dma.state.ma.us
Matthew Barry, Senior Program Analyst, Health Resources and Services Administration, Room 11-11, Parklawn Building, 5600 Fishers Lane, Rockville, MD 20857, (301)443-1512; FAX (301)443-2173, mbarry@hrsa.ssw.dhhs.gov
Arne Beck, Ph.D., Research and Development Director, Kaiser Permanente, 10350 East Dakota Avenue, Denver, CO 80231-1314, (303)344-7347; FAX (303)344-7301
Nathaniel Beers, M.D., Alternate District Coordinator, Resident's Section, American Academy of Pediatrics, 3701 Connecticut Avenue, N.W., Washington, DC 20008, (202)966-1441; FAX (202)994-4681, nbeer@gwisz.circ.gwu.edu
William Benson, Deputy Assistant Secretary for Aging, Administration on Aging, Room 4760, W.J. Cohen Building, 330 Independence Avenue, S.W., Washington, DC 20201, (202)619-0556; FAX (202)617-7586
Allan I. Bergman, Director, State-Federal Relations, United Cerebral Palsy Associations, 1660 L Street, N.W., Suite 700, Washington, DC 20036, (202)973-7105; FAX (202)785-3508
Dr. Betty Jo Berland, Planning Officer, U.S. Department of Education, National Institute for Disability Rehabilitation Research, Room 3422, M.E. Switzer Building, 330 C Street, S.W., Washington, DC 20202, (202)205-9739; FAX (202)205-8515, betty_jo_berland@ed.gov
Mimi Bernardin, Senior Research Leader, The MEDSTAT Group, 125 Cambridge Park Drive, Cambridge, MA 02140, (617)492-9318; FAX (617)492-9365
Richard W. Besdine, M.D. Director, Health Standards and Quality Bureau, Health Care Financing Administration, 7500 Security Boulevard, Room S2-11-07, Baltimore, MD 21244, (410)786-6842; FAX (410)786-6857, rbesdine@hcfa.gov
Donald Blanchon, Vice President, Strategic Planning, Health Services for Children with Special Needs, 1800 M Street, N.W., Suite 425 South, Washington, DC 20036, (202)466-2145; FAX (202)466-8514
C. Jean Blaser, Ph.D., Division Manager, Department on Aging, 421 East Capitol Avenue, Suite 100, Springfield, IL 62701-1789, (217)785-3352; FAX (217)524-7629
Joan R. Bloom, Ph.D., Professor, University of California, Berkeley, 709 Warren Hall, Berkeley, CA 94720-7360, (510)642-4458; FAX (510)643-6981, jbloom@uclink2.berkeley.edu (Bio) (Presentation)
Paul J. Boben, Ph.D., Social Science Research Analyst, Health Care Financing Administration, 7500 Security Boulevard, Mail Stop C3-18-26, Baltimore, MD 21208, (410)786-6629; FAX (410)786-5515, pboben@hcfa.gov
Carmella Bocchino, M.B.A, R.N, Vice President, Medical Affairs, American Association of Health Plans, 1129 20th Street, N.W., Suite 600, Washington, DC 20036, (202)778-3222; FAX (202)778-3287, cbocchino@aahp.org
Jennifer Bonney, Social Science Research Analyst, Health Care Financing Administration, Room 351G, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-5636; FAX (202)690-8168, jbonney@hcfa.gov
Maureen Booth, M.A., Director, Managed Care Initiatives, University of Southern Maine, Edmund S. Muskie Institute of Public Affairs, 96 Falmouth Street, P.O. Box 9300, Portland, ME 04104-9300, (207)780-4851; FAX (207)780-4953, maureenb@usm.maine.edu
Chad Boult, M.D., M.P.H., Associate Professor, University of Minnesota Medical School, Department of Family Practice and Community Health, 825 Washington Avenue, S.E., Box 25, Minneapolis, MN 55414-3034, (612)627-4686; FAX (612)627-4314, boult001@maroon.tc.umn.edu
Tom Bradley, Principal Analyst, Congressional Budget Office, Room 436, Ford Building, Washington, DC 20515, (202)226-9010; FAX (202)226-2963, tbrad@cbo.gov
Ruth W. Brannon, Director, Washington Business Group on Health, 777 North Capitol Street, N.E., Washington, DC 20002, (202)408-9320; FAX (202)408-9332, brannon@wbgh.com
Richard J. Bringewatt, President/Chief Executive Officer, National Chronic Care Consortium, 8100 26th Avneue South, Suite 120, Bloomington, MN 55425, (612)858-8999; FAX (612)858-8992, 73764,443@compuserve.com
Hon. Richard Browdie, Secretary Pennsylvania Department of Aging, 400 Market Street, Seventh Floor, RCSOB, Harrisburg, PA 17101-2301, (717)783-1550; FAX (717)772-3382
Randall S. Brown, Ph.D., Senior Fellow, Mathematica Policy Research, Inc., P.O. Box 2393, Princeton, NJ 08543-2393, (609)275-2393; FAX (609)799-0005, rsb@mprnj.com
Jeffrey A. Buck, Ph.D., Associate Director, Organization and Financing, Substance Abuse and Mental Health Services Administration, Room 15-87, Parklawn Building, 5600 Fishers Lane, Rockville, MD 20857, (301)443-2440; FAX (301)443-1563, jbuck@samhsa.gov
Ngoc Bui-Tong, Project Manager, Division of Medical Assistance, 600 Washington Street, Boston, MA 02111, (617)348-5720; FAX (617)348-8577, buitong@dmasmtp.dma.state.ma.us
Larry Burt, Program Manager, Disabilities Prevention Program, Centers for Disease Control and Prevention, 4770 Buford Highway, Room F-29, Atlanta, GA 30341, (770)488-7081; FAX (770)488-7075, lrb1@cehod1.em.cdc.gov
Brian O. Burwell, Director, The MEDSTAT Group, 125 Cambridge Park Drive, Cambridge, MA 02140, (617)492-9302; FAX (617)492-9365 (Bio) (1996 Report)
William D. Clark, Senior Research Analyst, Health Care Financing Administration, ORD Division on Aging and Disability, 7500 Security Boulevard, Baltimore, MD 21244, (410)786-1484; FAX (410)786-5534, wclark1@hcfa.gov
Barbara Cooper, Acting Director, Health Care Financing Administration, Office of Research and Demonstrations, 7500 Security Boulevard, Mail Stop C3-20-11, Baltimore, MD 21244, (410)786-6507; FAX (410)786-6511
Carol Cronin, Senior Vice President, Health Pages, 19 May Avenue, Annapolis, MD 21403, (410)267-7793; FAX (410)267-9141, ccronin19.aol.com
John Cutler, Issues Analyst, American Association of Retired Persons, 601 E Street, N.W., Washington, DC 20049, (202)434-3562; FAX (202)434-3443, jcutler@aarp.org
Sharon Davis, Ph.D., Director, Research and Program Services, The Arc, 500 East Border Street, Suite 300, Arlington, TX 75060, (817)261-6003; FAX (817)277-3491, sdavis@metronet.com
Gerben DeJong, Ph.D., Director, NRH Research Center, National Rehabilitation Hospital, 102 Irving Street, N.W., Washington, DC 20010-2949, (202)466-1900; FAX (202)466-1911, gxd3@mhg.edu (Bio) (1989 Report) (1996 Report) (1996 Report)
Susan J. Denman, M.D., Senior Vice President, Medical Affairs, Philadelphia Geriatric Center, 5301 Old York Road, Philadelphia, PA 19141, (215)456-2092; FAX (215)456-2883
Dr. Larry Diamond, President, Senior Health Systems, Inc., 700 Massachusetts Avenue, Cambridge, MA 02139, (617)876-2828; FAX (617)876-2548
Barbara Dickey, Ph.D., Associate Professor of Psychology, Department of Psychology, Harvard Medical School, McLean Hospital, 115 Mill Street, Belmont, MA 02178, (617)855-2423; FAX (617)855-2948, dickey@world.std.com (Bio) (Presentation) (1996 Report)
Karen Donelan, Sc.D., Senior Research Associate, Harvard School of Public Health, Department of Health Policy and Management, 677 Huntington Avenue, Boston, MA 02115, (617)432-3829; FAX (617)432-4494, kdonelan@hsph.harvard.edu
Tony Dreyfus, Medicaid Working Group, 441 Stuart Street, Sixth Floor, Boston, MA 02116, (617)437-1550; FAX (617)437-0031, tdreyfus@bu.edu (Bio)
Joyce Dubow, Senior Policy Advisor, American Association of Retired Persons, 601 E Street, N.W., Washington, DC 20049, (202)434-3901; FAX (202)434-6480, jdubow@aarp.org
Jack C. Ebeler, Acting Assistant Secretary, Planning and Evaluation, Department of Health and Human Services, Room 415F, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-7858; FAX (202)690-7383, jebeler@osaspe.dhhs.gov
Susan Edgman-Levitan, P.A., Executive Director, The Picker Institute, 1295 Boylston Street, Suite 100, Boston, MA 02215, (617)667-2388; FAX (617)667-8488, sedgman@bidmc.harvard.edu
Gary Edwards, Ph.D., Executive Director, United Cerebral Palsy of Greater Birmingham, Inc., 2430 11th Avenue North, Birmingham, AL 35234, (205)251-0165; FAX (205)226-9107, ucpgb1@aol.com
Jennifer N. Edwards, Dr.P.H., Senior Associate, Center for Vulnerable Populations, Institute for Health Policy, Brandeis University, 415 South Street, Mailstop 035, Waltham, MA 02254, (617)736-3904; FAX (617)736-3985, edwards@binah.cc.brandeis.edu
Nancy Eustis, Ph.D., Professor, University of Minnesota, Humphrey Institute of Public Affairs, 301 19th Avenue South, Minneapolis, MN 55455, (612)625-4534, neustis@hhh.umn.edu
Bettina Experton, M.D., M.P.H., President, Humetrix, Inc., 4370 La Jolla Village Drive, Suite 400, San Diego, CA 92122, (619)546-4359; FAX (619)546-0244, 70373,3665@compuserve.com
Teresa Fama, Deputy Director, Chronic Care Initiatives in HMOs, RWJ Foundation National Program Office, 1129 20th Street, N.W., Suite 600, Washington, DC 20036, (202)778-3285; FAX (202)331-7487, 105207.1743@compuserve.com (Bio) (Presentation)
Judith Feder, Ph.D., Professor, Public Policy, Georgetown University, Institute of Health Care Research and Policy, 2233 Wisconsin Avenue, N.W., Suite 525, Washington, DC 20007, (202)687-0880; FAX (202)687-3118
Penny Hollander Feldman, Ph.D., Director, Center for Home Care Policy and Research, Visiting Nurse Service of New York, 107 East 70th Street, New York, NY 10021, (212)794-6348; FAX (212)794-6610
Angel Ferrell, Public Policy Intern, Department of Health and Human Services, Office of Disability, Aging and Long-Term Care Policy, Room 424E, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-6613; FAX (202)401-7733, aferrell@osaspe.dhhs.gov
Laurie M. Flynn, Executive Director, National Alliance for the Mentally Ill, 200 North Glebe Road, Suite 1015, Arlington, VA 22203-3754, (703)524-7600; FAX (703)312-7890, laurie@nami.org
Diana Fortuna, Senior Policy Analyst, Domestic Policy Council, Room 213 OEOB, The White House, Washington, DC 20502, (202)456-5570; FAX (202)456-7431, fortuna_d@al.eop.gov
Harriette B. Fox, President, Fox Health Policy Consultants, 1747 Pennsylvania Avenue, N.W., Suite 1200, Washington, DC 20006, (202)223-1500; FAX (202)785-6687 (Bio) (Presentation)
Patrick J. Fox, Ph.D., Associate Professor, Sociology, University of California, San Francisco, Institute for Health and Aging, Box 0646, San Francisco, CA 94143-0646, (415)476-9483; FAX (415)476-9482, pf1965@itsa.ucsf.edu
Peter D. Fox, Ph.D., President, PDF Incorporated, 8101 Connecticut Avenue, Suite N-706, Chevy Chase, MD 20815, (301)718-1015; FAX (301)951-0842
Andreas Frank, Social Science Analyst, Department of Health and Human Services, Office of Disability, Aging and Long-Term Care Policy, Room 424E, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-6443; FAX (202)401-7733, afrank@osaspe.dhhs.gov
Bruce M. Fried, Director, Office of Managed Care, Health Care Financing Administration, 7500 Security Boulevard, Mail Stop S3-02-01, Baltimore, MD 21244, (410)786-4287; FAX (410)786-0192
Lex Frieden, Senior Vice President/Professor, Baylor College of Medicine, Institute for Rehabilitation and Research, 1333 Moursund, Houston, TX 77030, (713)797-5283; FAX (713)799-7095, lfrieden@bcm.tmc.edu (Bio)
Robert B. Friedland, Ph.D., Director, National Academy on Aging, 1275 K Street, N.W., Suite 350, Washington, DC 20005, (202)408-3375; FAX (202)842-1150
Barbara Gage, Ph.D., Expert, Agency for Health Care Policy and Research, Center for Organization and Delivery Studies, 2101 East Jefferson Street, Suite 500, Rockville, MD 20852, (301)594-1410 x1522; FAX (301)594-2314, bgage@cghsir.ahcpr.gov
James F. Gardner, Ph.D., Chief Executive Officer, Accreditation Council, 100 West Road, Suite 406, Towson, MD 21204, (410)583-0060; FAX (410)583-0063
Connie Garner, Senior Policy Analyst, U.S. Department of Education, Office of Special Education and Rehabilitative Services, Room 3127, M.E. Switzer Building, 330 C Street, S.W., Washington, DC 20202, (202)205-8124; FAX (202)205-9252
Robert M. Gettings, Executive Director, National Association of State Directors of Developmental Disabilities Services, 113 Oronoco Street, Alexandria, VA 22314, (703)683-4202; FAX (703)684-1395, rgettings@aol.com
Christine Gianopoulos, Director, Bureau of Elder and Adult Services, 11 State House Station, Augusta, ME 04333, (207)624-5335; FAX (207)624-5361, christine.gianopoulos@state.me.us
Mary Jo Gibson, Manager, Health Policy Research, American Association of Retired Persons, Public Policy Institute, 601 E Street, N.W., Washington, DC 20049, (202)434-3896; FAX (202)434-6480
Marsha R. Gold, Sc.D., Senior Fellow, Mathematica Policy Research, Inc., 600 Maryland Avenue, S.W., Suite 550, Washington, DC 20024-2512, (202)484-4227; FAX (202)863-1763, mrg@mprnj.com
Howard Goldman, M.D., M.P.H., Ph.D., Professor, Psychiatry, University of Maryland School of Medicine, Department of Psychiatry, 645 West Redwood Street, Baltimore, MD 21201, (410)706-6669; FAX (410)706-0022 (Bio)
George Greenberg, Department of Health and Human Services, Office of Health Policy, Room 442E, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-7794; FAX (202)401-7321, ggreenbe@osaspe.dhhs.gov
Robert Griss, Director, Center on Disability and Health, 1522 K Street, N.W., Suite 800, Washington, DC 20005, (202)842-4408; FAX (202)842-2402
Leonard Gruenberg, Ph.D., President, DataChron Health Systems, Inc., 763 Massachusetts Avenue, Suite 7, Cambridge, MA 02139, (617)661-1133; FAX (617)876-7309, 103353,2743@compuserve.com (Bio) (Presentation)
Mary Guthrie, 3301 Northeast Fifth Avenue, Apt. #706, Miami, FL 33137, (305)571-8112
Thomas E. Hamilton, Director, Bureau of Long Term Support, Department of Health and Family Services, P.O. Box 7851, Madison, WI 53707, (608)266-9304; FAX (608)267-2913, hamilte@dhfs.org
Jennie Chin Hansen, Executive Director, On Lok, Inc., 1333 Bush Street, San Francisco, CA 94109, (415)292-8880; FAX (415)292-8745, jennie@attmail.com
Mary F. Harahan, Acting Deputy Assistant Secretary for Disability, Aging and Long-Term Care Policy, Department of Health and Human Services, Room 424E, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-6443; FAX (202)401-7733, mharahan@oaspe.dhhs.gov (1996 Report)
Sandra Harmon-Weiss, M.D., Vice President/Medical Director, U.S. Healthcare, 980 Jolly Road, Mail Stop 22B, Blue Bell, PA 19442, (215)283-6596; FAX (215)283-6614
Jennie Harvell, Program Analyst, Department of Health and Human Services, Office of Disability, Aging and Long-Term Care Policy, Room 424E, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-6443; FAX (202)401-7733, jharvell@osaspe.dhhs.gov
Tony Hausner, Ph.D., Senior Analyst, Health Care Financing Administration, Office of Managed Care, 7500 Security Boulevard, Baltimore, MD 21244, (410)786-1093; FAX (410)786-5010, thausner@hcfa.gov
Kevin D. Hennessy, Ph.D., Health Policy Analyst, Department of Health and Human Services, Office of Health Policy, Room 432E, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-7272; FAX (202)401-7321, khenness@osaspe.dhhs.gov
Susan N. Hill, Health Policy Analyst, Health Care Financing Administration, Room 325H, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-7063; FAX (202)690-6994
Bonnie Hillegass, AVP Healthcare Operations, P.O. Box 15645, Las Vegas, NV 89114-5645, (702)242-7574; FAX (702)242-7797
Michael F. Hogan, Ph.D., Director, Ohio Department of Mental Health, 30 East Broad Street, Eighth Floor, Columbus, OH 43266-0414, (614)466-2337; FAX (614)752-9453 (Bio)
John Hockenberry, Correspondent, NBC News, 30 Rockefeller Plaza, Room 510, New York, NY 10112, (212)664-6141; FAX (212)664-7073
Lynda Honberg, Health Resources and Services Administration, Room 14A-21, Parklawn Building, 5600 Fishers Lane, Rockville, MD 20857, (301)443-4588; FAX (301)443-1551
Mark C. Hornbrook, Ph.D., Program Director, Center for Health Research, Kaiser Permanente, Northwest Division, Portland, OR 97227-1098, (503)335-6746; FAX (503)335-2424, hornbrookma@chr.mts.kpnw.org (1996 Report)
Susan L. Hughes, D.S.W., Director, Program in Long-Term Care/Professor, Institute for Health Services Research and Policy Studies, Northwestern University, 629 Noyes Street, Evanston, IL 60208-4170, (847)491-5643; FAX (847)491-2202, s-hughes@nwu.edu
Robert E. Hurley, Ph.D., Associate Professor, Medical College of Virginia, Department of Health Administration, Box 980203, Richmond, VA 23298-0203, (804)828-1891; FAX (804)828-1894, rhurley@gems.vcu.edu
Lisa Iezzoni, M.D., Associate Professor, Medicine, Harvard Medical School, Beth Israel Hospital, 330 Brookline Avenue, Boston, MA 02215, (617)667-5871; FAX (617)667-4926, liezzoni@bih.harvard.edu
John K. Iglehart, Founding Editor, Health Affairs, 12008 River Road, Potomac, MD 20854, (301)983-9735; FAX (301)983-8215
Carol Irvin, Ph.D., Economist, Abt Associates, Inc., 55 Wheeler Street, Cambridge, MA 02138, (617)349-2502; FAX (617)349-2675, carol_irvin@abtassoc.com (Bio) (Presentation)
George J. Isham, M.D., Medical Director/Chief Health Officer, HealthPartners, P.O. Box 1309, Minneapolis, MN 55440, (612)883-6769; FAX (612)883-5380, george.j.isham@healthpartners.com
Joan S. Jacobs, M.P.H., Public Health Analyst, PHS Office of Minority Health, 5515 Security Lane, Suite 1000, Rockville, MD 20852, (301)443-9923; FAX (301)443-8280, jjacobs@osphs.ssw.dhhs.gov
Judith Miller Jones, Director, National Health Policy Forum, 2021 K Street, N.W., Suite 800, Washington, DC 20006, (202)872-1390; FAX (202)862-9837, jmjones@gwis2.circ.gwu.edu
Stanley B. Jones, Director, Health Insurance Reform Project, George Washington University, 2021 K Street, N.W., Suite 800, Washington, DC 20006, (202)835-8327; FAX (202)862-9837, sjones8689@aol.com
Diane Justice, Deputy Director, National Association of State Units on Aging, 1225 I Street, N.W., Suite 725, Washington, DC 20005, (202)898-2578; FAX (202)898-2583, staff@nasua.org
Robert L. Kane, M.D., Professor/Minnesota Chair in Long-Term Care and Aging, University of Minnesota School of Public Health, D-351 Mayo (Box 197), 420 Delaware Street, S.E., Minneapolis, MN 55455, (612)624-1185; FAX (612)624-8448, kanex001@maroon.tc.umn.edu
Ruth E. Katz, Director, Division of Disability and Aging Policy, Department of Health and Human Services, Office of Disability, Aging and Long-Term Care Policy, Room 424E, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-6613; FAX (202)401-7733, rkatz@osaspe.dhhs.gov (1996 Report)
Cille Kennedy, Ph.D., Associate Director, Disabilities Research, National Institute of Mental Health, Room 10-105, Parklawn Building, 5600 Fishers Lane, Rockville, MD 20857, (301)443-3648; FAX (301)443-4045
David Kidder, Ph.D., Managing Vice President, Abt Associates, Inc., 55 Wheeler Street, Cambridge, MA 02138, (617)349-2483; FAX (617)349-2675, david_kidder@abtassoc.com
James R. Knickman, Ph.D., Vice President, Robert Wood Johnson Foundation, P.O. Box 2316, Princeton, NJ 08543, (609)243-5959; FAX (609)987-8746, jrk@rwjf.org
Richard A. Knox, Medical Writer, Boston Globe, 27 Wellesley Park, Dorchester, MA 02124, (617)929-3078; FAX (617)929-2019, knox@nws.globe.com
Dennis L. Kodner, Ph.D., Vice President/Executive Director, Institute for Applied Gerontology, 6323 Seventh Avenue, Brooklyn, NY 11220, (718)630-2550; FAX (718)630-2559, 74764.2516@compuserve.com
Harriet L. Komisar, Assistant Research Professor, Georgetown University, Institute for Health Care Research and Policy, 2233 Wisconsin Avenue, N.W., Suite 525, Washington, DC 20007, (202)687-0880; FAX (202)687-3110
Andrew Kramer, M.D., Research Director, Center on Aging, University of Colorado Health Sciences Center, 3570 East 12th Avenue, Suite 300, Denver, CO 80206, (303)315-6031; FAX (303)315-4827, andy.kramer@uchsc.edu
Richard Kronick, Ph.D., Associate Professor, University of California, San Diego, Department of Family Medicine, 0622, La Jolla, CA 92093, (619)534-4273; FAX (619)534-4642, rkronick@ucsd.edu
K. Charlie Lakin, Ph.D., Director, Research and Training Center on Community Living, University of Minnesota, Room 214, Pattee Hall, 150 Pillsbury Drive, S.E., Minneapolis, MN 55455, (612)624-5005; FAX (612)625-6619, lakin001@maroon.tc.umn.edu
Sheila T. Leatherman, Executive Vice President, United HealthCare Corporation, Mail Route MN08-8093, P.O. Box 1459, Minneapolis, MN 55440-1459, (612)936-7373; FAX (612)936-0044, sleather@uhc.com
H. Stephen Leff, Ph.D., Senior Vice President, Human Services Research Institute, 2336 Massachusetts Avenue, Cambridge, MA 02140, (617)876-0426 x309; FAX (617)492-7401, leff@hsri.org
Dr. Joel M. Levy, Chief Executive Officer, Young Adult Institute, 460 West 34th Street, New York, NY 10001, (212)563-7474 x110; FAX (212)947-7524, jmlcares@yai.org
Charlie Liem, Chief, Office of External Affairs, Department of Elder Affairs, 4040 Esplanade Way, Suite 315, Tallahassee, FL 32399-7000, (904)414-2000; FAX (904)414-2008
Korbin Liu, Sc.D., Principal Research Associate, The Urban Institute, 2100 M Street, N.W., Washington, DC 20037, (202)857-8648; FAX (202)223-1149, kliu@ui.urban.org
Ruth Martin, 71 Wiggins Street, Princeton, NJ 08540, (609)683-4339; FAX (609)683-4339, ruthmartin@aol.com
William Marton, Demographer, Department of Health and Human Services, Office of Disability, Aging and Long-Term Care Policy, Room 424E, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-6443; FAX (202)401-7733, wmarton@osaspe.dhhs.gov
Katie Maslow, Alzheimer's Consultant, Alzheimer's Association, 1319 F Street, N.W., Suite 710, Washington, DC 20004-1106, (202)393-7737; FAX (202)393-2109, kmaslow@aol.com
Robert J. Master, M.D., Medical Director, Community Medical Alliance, 441 Stuart Street, Sixth Floor, Boston, MA 02116, (617)437-1400; FAX (617)437-7226
Elizabeth Mauser, Social Science Research Analyst, Health Care Financing Administration, Office of Research and Demonstrations, Division of Aging and Disability, 7500 Security Boulevard, Baltimore, MD 21244, (410)786-6665; FAX (410)786-5534, emauser@hcfa.gov
Nelda McCall, President, Laguna Research Associates, 455 Market Street, Suite 1190, San Francisco, CA 94105, (415)512-7480; FAX (415)512-7488, lagunar@aol.com
Bentson H. McFarland, M.D., Ph.D., Professor, Psychiatry, Oregon Health Sciences University, Department of Psychiatry, OP-02, Portland, OR 97201, (503)245-6550; FAX (503)494-6578, mcfarlandbe@chr.mts.kpnw.org (Bio) (Presentation) (1996 Report)
Thomas G. McGuire, Ph.D., Professor, Economics, Boston University, 270 Bay State Road, Boston, MA 02215, (617)353-2995; FAX (617)353-4449, tmcguire@bu.edu (Bio) (Presentation) (Report)
Margaret McManus, President, McManus Health Policy, Inc., 2 Wisconsin Circle, Suite 700, Chevy Chase, MD 20815, (202)686-4797; FAX (202)686-4791 (Bio) (Presentation)
Mark R. Meiners, Ph.D., Associate Director, University of Maryland, Center on Aging, Room 1240, HHP Building, College Park, MD 20742-2611, (301)405-2532; FAX (301)314-2025, mm56@umail.umd.edu
Nancy A. Miller, Director, Division of Aging and Disability, Health Care Financing Administration, 7500 Security Boulevard, Baltimore, MD 21244, (410)786-6648; FAX (410)786-6511 (1996 Report)
Dann Milne, Ph.D., Manager, Delivery System Development, Department of Health Care Policy and Financing, 1575 Sherman Street, Denver, CO 80203, (303)866-5912; FAX (303)866-2803, ndm@cdss.mhs.compuserve.com
Betty Mullin, Director, Chronic Care/Long-Term Care Planning, Group Health Cooperative, 521 Wall Street, ACC-2, Seattle, WA 98121, (206)448-4655; FAX (206)448-4438, bmullin@accgwx.ghc.org
Robert Newcomer, Professor, University of California, San Francisco, Department of Social and Behavioral Sciences, Box 0612, San Francisco, CA 94143, (415)476-1408; FAX (415)476-6552, rjn@itsa.ucsf.edu
Michael A. Nolin, Managed Care Coordinator, University of Maryland, Baltimore County, Center for Health Program Development and Management, 1000 Hilltop Circle, Baltimore, MD 21250, (410)455-6759; FAX (410)455-6850, nolin@umbc.edu
Dennis Nugent, Health Insurance Specialist, Health Care Financing Administration, 7500 Security Boulevard, Baltimore, MD 21244, (410)786-6633; FAX, dnugent@hcfa.gov
Ellen O'Brien, Research Analyst, Health Care Financing Administration, Room 325H, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-6313; FAX (202)690-6994, eobrien@hcfa.gov
Margaret E. O'Kane, President, National Committee for Quality Assurance, 2000 L Street, N.W., Suite 500, Washington, DC 20036, (202)955-5101; FAX (202)955-3599
Janet O'Keeffe, Dr.P.H., R.N., Senior Policy Advisor, American Association of Retired Persons, Public Policy Institute, 601 E Street, N.W., Washington, DC 20049, (202)434-3864; FAX (202)434-6402, jokeeffe@aarp.org R.
Heather Palmer, M.B., B.Ch., S.M., Director, Center for Quality of Care Research and Education, Harvard School of Public Health, 677 Huntington Avenue, Seventh Floor, Boston, MA 02115, (617)432-0779; FAX (617)432-3199, qcare@sph.harvard.edu
James M. Perrin, M.D., Associate Professor, Pediatrics, Harvard Medical School, Massachusetts General Hospital, WACC 715, Boston, MA 02114-3139, (617)726-8716; FAX (617)726-1886, perrin.james@mgh.harvard.edu
Bonnie Preston, Manager, Garfield Memorial Fund, Kaiser Permanente, 1 Kaiser Plaza, 23rd Floor, Oakland, CA 94612, (510)271-6394; FAX (501)271-6414, bonnie.preston@kp.org
Joan L. Quinn, Senior Vice President, Government Managed Care Programs, Blue Cross and Blue Shield of Connecticut, 370 Bassett Road, North Haven, CT 06473, (203)239-8241; FAX (203)985-7918
Donna I. Regenstreif, Ph.D., Senior Program Officer, The John A. Hartford Foundation, 55 East 59th Street, New York, NY 10022, (212)832-7788; FAX (212)593-4913, mail@jhartfound.com
Peter Reis, Financial Director, Positive Healthcare, AIDS Healthcare Foundation, 6255 Sunset Boulevard, 16th Floor, Los Angeles, CA 90028, (213)462-2273; FAX (213)962-8513
David B. Reuben, M.D., Director, Multicampus Program in Geriatric Medicine and Gerontology, UCLA Department of Medicine, Division of Geriatrics, A-665 Factor Building, Box 951687, Los Angeles, CA 90095-1687, (310)825-8253; FAX (310)794-2199, dreuben@med1.medsch.ucla.edu
Gerald Riley, Social Science Research Analyst, Health Care Financing Administration, 7500 Security Boulevard, Room C-3-24-07, Baltimore, MD 21244-1850, (410)786-6699; FAX (410)786-5534, griley@hcfa.gov
Trish Riley, Executive Director, National Academy for State Health Policy, 50 Monument Square, Suite 502, Portland, ME 04101, (207)874-6524; FAX (207)874-6527
Sandra K. Robinson, Acting Director, Agency for Health Care Policy and Research, Center for Quality Measurement and Improvement, 2101 East Jefferson Street, Suite 502, Rockville, MD 20852, (301)594-1349 x1314; FAX (301)594-2155, srobinso@po3.ahcpr.gov
Douglas Roblin, Health Economist, Kaiser Foundation Health Plan, Inc., 1 Kaiser Plaza, Oakland, CA 94612, (510)271-6418; FAX (510)271-5815
Joseph A. Rogers, Executive Director, National Mental Health Consumers' Self-Help Clearinghouse, 1211 Chestnut Street, Tenth Floor, Philadelphia, PA 19107, (215)751-1810 x273; FAX (215)636-6310, josephrogers@delphi.com
Margo L. Rosenbach, Ph.D., Executive Vice President, Health Economics Research, 300 Fifth Avenue, Sixth Floor, Waltham, MA 02154, (617)487-0200; FAX (617)487-0202, margo@her-cher.org (Bio) (Track I Presentation)
Diane Rowland, Sc.D., Executive Director, Kaiser Commission on the Future of Medicaid, 1450 G Street, N.W., Suite 250, Washington, DC 20005, (202)347-5270; FAX (202)347-5274
Paul Saucier, Muskie Institute, 49 Exeter Street, Portland, ME 04101, (207)780-4430; FAX, 73612.316@compuserve.com
William J. Scanlon, Ph.D., Director, Health Systems Issues, U.S. General Accounting Office, 441 G Street, N.W., NGB 500, Washington, DC 20548, (202)512-4561; FAX (202)512-5805, scanlonw.hehs@gao.gov
Robert E. Schlenker, Ph.D., Associate Director, Center for Health Services Research, University of Colorado, 1355 South Colorado Boulevard, Suite 306, Denver, CO 80222, (303)756-8350; FAX (303)759-8196, bob.schlenker@uchsc.edu
Robert J. Schmitz, Ph.D., Senior Economist, Abt Associates, Inc., 55 Wheeler Street, Cambridge, MA 02138-1168, (617)349-2491; FAX (617)349-2675, bob_schmitz@abtassoc.com
Dr. Katherine D. Seelman, Director, National Institute on Disability and Rehabilitation Research, U.S. Department of Education, 600 Independence Avenue, S.W., Washington, DC 20202-2572, (202)205-8134; FAX (202)205-8997, kate_seelman@ed.gov
Elizabeth A. Shenkman, Ph.D., Assistant Professor, College of Medicine, University of Florida, 5700 Southwest 34th Street, Suite 323, Gainesville, FL 32608, (352)392-5904 x222; FAX (352)392-8822, betsy_shenkman@qm.server.ufl.edu (Bio) (Presentation) (Report)
Cynthia Shirk, Project Officer, Health Care Financing Administration, Office of Research and Demonstrations/OSHRD, 7500 Security Boulevard, Baltimore, MD 21244, (410)786-6614; FAX (410)786-5515, cshirk@hcfa.gov
Linda A. Siegenthaler, Senior Economist, Agency for Health Care Policy and Research, Center for Primary Care Research, 2101 East Jefferson Street, Suite 502, Rockville, MD 20852, (301)594-1357 x1384; FAX (301)594-3721, lsiegent@po3.ahcpr.gov
Shoshanna Sofaer, Dr.P.H., Director, Center for Health Outcomes Improvement Research, George Washington University Medical Center, 1001 22nd Street, N.W., Suite 700, Washington, DC 20016, (202)467-2237; FAX (202)452-1847, inosos@gwumc.edu
Stephen A. Somers, Ph.D., President, Center for Health Care Strategies, Inc., 353 Nassau Street, Princeton, NJ 08540, (609)279-0700; FAX (609)279-0956, sas@chcs.org
Deborah Spitalnik, Ph.D., Executive Director/Associate Professor, Clinical Pediatrics and Family Medicine, University Affiliated Program of New Jersey, UMDNJ, RWJ Medical School, Brookwood II, 45 Knightsbridge Road, Second Floor, Piscataway, NJ 08855-6810, (908)235-5420; FAX (908)235-5059
Paul R. Spitzer, Ph.D., Cooperative Oxford Laboratory, 31672 Old Orchard Road, Trappe, MD 21673, (410)476-5163; FAX (410)226-5925
Barbara E. Staub, M.D., Pediatrician, White Bear Lake Clinic, 1430 Highway 96, White Bear Lake, MN 55110, (612)653-2145; FAX (612)653-2111 (Bio) (Presentation)
Ruth E.K. Stein, M.D., Professor/Vice Chairman, Pediatrics, Albert Einstein College of Medicine, Room 817, JACOBI, 1300 Morris Park Avenue, Bronx, NY 10461, (718)918-5304; FAX (718)918-5007, rstein@aecom.yu.edu (Bio)
Sharman K. Stephens, Director, Special Analysis Staff in the Associate Administrator for Policy's, Office Health Care Financing Administration, Room 325H, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-7063; FAX (202)690-6994, sstephens@hcfa.gov
Margaret G. Stineman, M.D., Associate Professor, Rehabilitation Medicine, University of Pennsylvania, Room 101, Ralston-Penn Center, 3615 Chestnut Street, Philadelphia, PA 19104-2676, (215)898-6272; FAX (215)573-2017, mstinema@mail.med.upenn.edu
Robyn I. Stone, Dr.P.H., Acting Assistant Secretary, Administration on Aging, Room 309F, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)401-4634; FAX (202)401-7741
Dena Stoner, Senior Policy Analyst, Health and Human Services Commission, P.O. Box 13247, Austin, TX 78701, (512)424-6521; FAX (512)424-6585, dena_s@hhsc.state.tx.us
Janet P. Sutton, Ph.D., Senior Research Associate, National Rehabilitation Hospital Research Center, 102 Irving Street, N.W., Washington, DC 20010, (202)466-1900; FAX (202)466-1911, jps2@mhg.edu (1996 Report)
Sandra J. Tanenbaum, Ph.D., Associate Professor, Ohio State University College of Medicine, 1583 Perry Street, Columbus, Ohio 43210, (614)291-6126; FAX (614)292-2375, tanenbaum.1@osu.edu (Bio) (1996 Report)
Tammy D. Terrell, Department of Health and Human Services, Office of Disability, Aging and Long-Term Care Policy, Room 424E, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-6613; FAX (202)401-7733, tterrell@osaspe.dhhs.gov
Irma Tetzloff, Executive Assistant, Governmental Affairs, Administration on Aging, 330 Independence Avenue, S.W., Washington, DC 20201, (202)619-3269; FAX (202)619-7586, itetzloff@ban-gate.aoa.dhhs.gov
Nancy R. Thaler, Deputy Secretary, Department of Public Welfare, Office of Mental Retardation, P.O. Box 2675, Harrisburg, PA 17105-2675, (717)787-3700; FAX (717)787-6583, padpwnt@aol (Bio)
Craig Thornton, Senior Fellow, Mathematica Policy Research, P.O. Box 2393, Princeton, NJ 08543-2393, (609)275-2371; FAX (609)799-0005, cvt@mprnj.com
Jane Tilly, Manager, Long-Term Care Policy Research, American Association of Retired Persons, Public Policy Institute, 601 E Street, N.W., Washington, DC 20049, (202)434-3865; FAX (202)434-6402, jtilly@aarp.org
Theodore L. Totman, Legislative Assistant, Senator Charles Grassley's Office, Room 135, Hart Building, Washington, DC 20510, (202)224-3744; FAX (202)224-6020
Judith V. Tyler, Senior Policy Analyst, Office of the Inspector General, 10925 Colbert Way, Dallas, TX 75218, (214)767-3310; FAX (214)767-2039, jvt@ospafec6.ssw.dhhs.gov
Theresa Varner, Director, Public Policy Institute, American Association of Retired Persons, 601 E Street, N.W., Washington, DC 20049, (202)434-3840; FAX (202)434-6480, tvarner@aarp.org
Brenda L. Veazey, Program Assistant, Department of Health and Human Services, Office of Disability, Aging and Long-Term Care Policy, Room 424E, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-6443; FAX (202)401-7733, bveazey@osaspe.dhhs.gov
Bruce C. Vladeck, Jr., Ph.D., Administrator, Health Care Financing Administration, Room 314G, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-6726; FAX (202)690-6262
E. Elaine Vowels, Ph.D., Director, D.C. Linkage and Tracking System, D.C. General Hospital, Pediatrics Building #10, Fourth Floor West Wing, 1900 Massachusetts Avenue, S.W., Washington, DC 20003, (202)727-8462; FAX (202)544-5945
Anne Wade, Social Science Research Analyst, Health Care Financing Administration, 7500 Security Boulevard, Mail Stop C3-18-26, Baltimore, MD 21244-1850, (410)786-4175; FAX (410)786-5515, awade2@hcfa.gov
Edward H. Wagner, M.D., M.P.H., Director, Center for Health Studies, Group Health Cooperative of Puget Sound, 1730 Minor Avenue, Suite 1600, Seattle, WA 98101, (206)287-2877; FAX (206)287-2871, wagnere@mpe.ghc.org
John E. Ware, Ph.D., Senior Scientist, New England Medical Center, The Health Institute, 750 Washington Street, Box 345, Boston, MA 02111, (617)636-8645; FAX (617)636-3229, john.ware@es.nemc.org
Sandra Welner, M.D., Primary Care Gynecology for Women with Disabilities, 8484 16th Street, Suite 707, Silver Spring, MD 20910, (301)587-6396; FAX (301)585-5467, welnersmd@aol.com
Sheryl White-Scott, M.D., Director, Adult Health Services, Westchester Institute for Human Development, 221 Cedarwood Hall, Valhalla, NY 10595, (914)285-8714; FAX (914)285-1973, sheryl_white@NYMC.edu
Nancy Whitelaw, Ph.D., Associate Director, Center for Health System Studies, Henry Ford Health System, One Ford Place, Suite 3A, Detroit, MI 48202, (313)874-5454; FAX (313)874-7137, nwhitela@smtpgw.ls.hfh.edu
Joshua M. Wiener, Ph.D., Principal Research Associate, The Urban Institute, 2100 M Street, N.W., Washington, DC 20037, (202)857-8652; FAX (202)223-1149, jwiener@ui.urban.org
Bob Williams, Commissioner, Administration on Developmental Disabilities, Room 351D, H.H. Humphrey Building, 200 Independence Avenue, S.W., Washington, DC 20201, (202)690-6590; FAX (202)401-9507
Ira B. Wilson, M.D., M.Sc., Scientist/Assistant Professor, Medicine, New England Medical Center, Primary Care Outcomes Research Institute, 750 Washington Street, NEMC #345, Boston, MA 02111, (617)636-8672; FAX (617)636-7988, iwilson@opal.tufts.edu
Shelly C. Wolff, Program Leader, Disability, General Electric Company, 3135 Easton Turnpike, Fairfield, CT 06461, (203)373-2834; FAX (203)373-3772, wolffs@central.corp.ge.com
Judith Wooldridge, Vice President, Mathematica Policy Research, P.O. Box 2393, Princeton, NJ 08543-2393, (609)275-2370; FAX (609)799-0005, jw@mprnj.com
David R. Zimmerman, Ph.D., Director, Center for Health Systems Research and Analysis, University of Wisconsin, Madison, 1163 WARF Building, 610 Walnut Street, Madison, WI 53706, (608)263-4875; FAX (608)263-4523, davidz@chsra.wisc.edu
Carolyn C. Zollar, Vice President, Public Policy/General Counsel, American Rehabilitation Association, 1910 Association Drive, Suite 200, Reston, VA 20191, (703)716-4063; FAX (703)648-3046
TAB 6: TRACK I: MANAGED CARE FOR CHILDREN AND ADULTS WITH DISABILITIES
Overview
Moderator Biographics
Brian O. Burwell
Brian Burwell is the Director of Healthcare Organization and Economics within the Research and Policy Division of The MEDSTAT Group. The MEDSTAT Group is a healthcare information company which provides databases, analytical software and consulting services to employers, managed care companies, insurers, providers, and government, with headquarters in Ann Arbor, MI. Mr. Burwell has been conducting healthcare services research for 17 years, with a career focus on Medicaid, disability and long-term care policy. He has published extensively on Medicaid eligibility policies for long-term care, home and community-based care waiver programs, Medicaid spend-down, asset transfers, community-based approaches to supporting persons with developmental disabilities, and managed care models for persons with disabilities. He is currently working with the Department of Health and Human Services in Delaware on a project to develop managed long-term care policy options for all the Department's long-term care populations.
Sandra J. Tanenbaum, Ph.D.
Sandra Tanenbaum is Associate Professor of Health Services Management and Policy at the Ohio State University College of Medicine. A political scientist by training, Dr. Tanenbaum's research focuses on the Medicaid program, disability policy, and clinical decision-making. She is the author of Engineering Disability: Public Policy and Compensatory Technology (Temple, 1986) and serves as Book Review Editor of the Journal of Health Politics, Policy and Law.
Managed Care for Children and Adults with Disabilities
Brian Burwell and Sandra Tanenbaum
INTRODUCTION
Managed care financing and delivery models have considerable potential for improving the value and quality of health care and supportive services provided to children and adults with disabilities. Managed care models that encourage flexibility in benefit coverage and which coordinate care across the full spectrum of the insurance benefit package are features that are particularly attractive to persons with disabilities. At the same time, however, managed care incentives to eliminate "inappropriate care" or care that is not "medically necessary" are of great concern to people with disabilities whose experience in obtaining access to needed health care services in the fee-for-service system is already problematic.
Both positive and negative effects of managed care for persons with disabilities are similarly reflected in the limited empirical research that has been conducted to date on the impacts of managed care on disabled populations. Some studies point to improvements in outcomes, while others have found significant reductions in service levels under managed care incentives. In brief, the jury is still out on how managed care models effect the health care status of persons with disabilities, and the challenge to the health care services research community is to monitor the enrollment of persons with disabilities into managed care systems closely, and to identify those factors which contribute to improved and worsened outcomes for these vulnerable populations.
CHILDREN AND ADULTS WITH DISABILITIES: WHO ARE THEY?
Part of the challenge in assessing the impact of managed care on persons with disabilities is that the population of children and adults with disabling conditions is extremely diverse, with broad-ranging differences in both types and levels of impairment. At the same time, managed care models are evolving into a variety of permutations that make the generalizability of managed care impact studies increasingly hazardous. In conceptualizing a research agenda for examining managed care impacts, it is critical that we begin with a fundamental understanding of the defined populations, and how the structure and incentives of managed care models may impact access, cost and quality outcomes for persons with severe and chronic disabling conditions.
Children with Disabilities
National survey data indicate that approximately one in ten children have a "severe chronic illness" (Neff and Anderson, 1995). This estimate obscures dramatic diversity in the characteristics of children with disabling conditions--many children with disabilities have conditions which do not result in health care use or costs significantly higher than the population of children without disabilities, while a significant minority of children with disabilities have severe and multiple conditions that require continuous and expert medical attention. Health care and supportive services for the population of children with special health care needs are also fragmented across a variety of financing and service settings that renders the transition from a fee-for-service framework to a managed care framework operationally cumbersome.
Importantly, within the population of children with high health care needs, there is a subset of children with extremely severe medical conditions that require continuous and highly specialized care. For example, within the target population of SSI children receiving services under the District of Columbia's Managed Care System for Disabled and Special Needs Children Demonstration, a Medicaid Section 1115 waiver program, children with Medicaid expenditures of over $50,000 per year constituted less than three percent of all SSI children in the District in the year prior to implementation of the demonstration program, yet they accounted for about 54 percent of all Medicaid spending for SSI children (Blanchon, 1996).
Childhood disability differs from disability in adulthood in that the nature and extent of the disability frequently changes during the developmental process. Many children experience improvements in functioning as they develop, and the disability may become less limiting with time. Other children with extremely severe medical conditions do not survive childhood at all. Moreover, the health care needs of children with disabilities is confounded over time by the interaction of the disability with the child's normal development, such as the onset of puberty. Consequently, access to appropriate pediatric and adolescent specialists may change frequently during the developmental process.
In regard to accessing health care, parents obviously take an active role in negotiating the health care system for their children. In brief, many parents take on the "coordination of care" role that is generally lacking in the fee-for-service system. Consequently, their interactions with the care coordination function of a managed care system may require a new accommodation of respective roles in managing the care of the disabled child. Managed care organizations are generally not used to the level of advocacy and health care system knowledge exhibited by parents of children with disabilities, and may not know how to positively incorporate that energy and knowledge into their internal care coordination systems.
A common concern of parents is the ability to maintain relationships with pediatric specialists, many of which have developed over the lifetime of the child, once the child is enrolled into a managed care plan. Consequently, in some Medicaid managed care initiatives, states require participating plans to continue to pay for ongoing physician-patient relationships, even if the specialty physician is not otherwise enrolled in the plan. This issue is of obvious concern to plans who feel that they are being paid to manage the care of the enrollee, but may not be given all the requisite tools to do so.
Children with disabilities differ from adults with disabilities in one other important respect--children are more likely to receive their health care through a fragmented financing system. Expansions in SSI and Medicaid eligibility for children with disabilities in recent years has meant that there are a growing number of children who have both private health care insurance and Medicaid coverage. Since the Medicaid benefit package is more comprehensive than private health insurance coverage, children and families often use their Medicaid coverage to finance services that are supplemental to their private insurance benefits, particularly home and community-based services and extended therapies. In addition, under the Individuals with Disabilities Education Act, local school systems are required to provide children with disabilities with educationally related services that often extend into the health care arena, particularly in the case of children with severe medical conditions. Lastly, under the Title V Program for Children with Special Health Care Needs, many states provide direct care services to children with disabilities on a categorical basis, not as part of the child's health insurance benefit. Since the implementation of managed care systems generally occurs within payers, not across payers, these multiple financing streams for children with disabilities create special challenges for the managed care marketplace.
Adults with Mental Illness and Substance Abuse Problems
Purchasers of health care services in both the private and public sectors have targeted services to persons with mental illness as prime candidates for managed care financing and delivery initiatives. In the private sector, many large companies have "carved-out" mental health and substance abuse benefits from their mainstream health care benefit programs, and have contracted with specialized vendors to administer these benefits. In the public sector as well, state Medicaid programs are building upon the infrastructure that has developed in managed behavioral health care to similarly "carve-out" at least a subset of mental health and substance abuse-related services covered under their own benefit packages to companies that specialize in the management of these services. On the research side, there is a larger body of research available on the impacts of managed mental health care than on how managed care impacts other services and/or populations.
While there has been significant penetration of managed care systems in the mental health/substance abuse market, it is important to recognize the differences in private and public markets as they relate to persons with mental health and substance abuse problems. In the private sector, purchasers finance mental health and substance abuse care for their employees, retirees and dependents. This population of workers and dependents is predominantly middle class and employed, with the concomitant array of mental health conditions that are most prevalent in this socio-demographic group. Depression and substance abuse disorders are diagnoses of high concern to private purchasers of health care, and the health care benefit programs of employers are structured to maximize value in the early identification and treatment of these conditions, with the objective of sustaining the productivity of their workforces.
In regard to coverage of mental health and substance abuse services for the dependents of employees, the goals are to provide coverage that is sufficiently attractive to recruit and retain a quality workforce (i.e. remaining competitive in the market for qualified workers) while limiting corporate expenditures for mental health and substance abuse care. Coverage of mental health and substance abuse care for adolescents with mental health conditions is often a major benefit issue for employers, since this population includes a subset of persons who account for a high percentage of total expenditures for these services.
In the public sector, the primary population of interest is persons with severe and persistent mental illnesses, particularly persons with disabilities associated with schizophrenia-related disorders. Approximately 30 percent of all adults under the age of 65 receiving SSI benefits, or about 1.5 million persons, qualified for SSI benefits on the basis of a mental disorder other than mental retardation (SSA, 1996). In addition, about 1 million persons with mental disorders received SSDI benefits, and are therefore insured under the Medicare program. As opposed to individuals receiving SSI benefits, persons receiving SSDI benefits have had a sufficient work history to obtain insured status under the Social Security disability system. On the whole, it is therefore reasonable to assume that SSDI beneficiaries have somewhat higher levels of functioning than persons receiving SSI.
Persons with severe and persistent mental illness have a broad range of medical, therapeutic, and supportive care needs, and a key issue in the application of managed care models to this population is what part of the care spectrum should be "managed." Although a number of state Medicaid programs have implemented mental health "carve-out" programs, it is important to recognize that states generally have only "carved-out" acute mental health services under these programs--inpatient care and outpatient follow-up care. Long-term supportive services, such as residential care programs, vocational training, day program services, and intensive case management services, have generally been excluded from the managed care contracts with carve-out vendors. Basic health care services are also usually provided by mainstream plans or the fee-for-service system.
The characteristics of persons with severe and persistent mental illness and their health and supportive service needs forcefully underscore the challenges of applying managed care models to the financing and delivery of services to this population. As a consequence, we are seeing a variety of managed care models emerging. Conceptually, one relatively simplistic way of classifying the service needs of this population is in three broad categories: (1) basic health care needs; (2) mental health-related services needed to deal with acute episodes of mental illness (short-term hospitalization, crisis intervention services); and (3) long-term supportive services intended to maintain individuals in independent or semi-independent community care settings.
As discussed above, most managed care initiatives for persons with severe and persistent mental illness have focused only on the management of one part of the total service continuum, i.e. the management of short-term hospitalizations and outpatient services. Basic health care services and long-term supportive services have, with few exceptions, not been made part of state managed care initiatives, as yet. A major reason for this segmentation of the total benefit package is related to infrastructure issues--states are building upon the infrastructure of managed behavioral health care vendors that have developed from demand created in the commercial marketplace. Another reason for this segmentation relates to the fragmentation of payments sources; Medicaid is generally the primary payer for acute mental health services for this population, while state Departments of Mental Health remain the primary payer for longer-term supportive services.
The limited scope of managed care initiatives for persons with severe and persistent mental illness has created "boundary" issues that affect the operationalization of these programs in critical ways, as well as how this population receives services. One fundamental issue is the boundary between mental health care and basic health care. Does it make sense for persons with severe mental illness to receive their primary health care through one system but have their "mental health" services managed by a separate system? If so, how is medication management coordinated across these dual systems? One major rationale for managed care is to coordinate care across a comprehensive benefit package for an enrolled population, and managed care initiatives which simply mirror the fragmentation of service delivery existent in the fee-for-service system are likely to fall short of this goal.
On the other hand, some state Medicaid programs have "carved-out" mental health services from managed care contracts for basic health care as a means to protect the population from the financial incentives of managed care to reduce services that may not be considered "medically necessary." There is considerable controversy in the commercial insurance market about the "savings" that have been achieved for health care purchasers by behavioral managed care vendors, and whether these savings are affecting mental health outcomes. Thus, in the public sector, mental health carve-outs have been used as a policy tool to protect mental health benefits from the incentives of managed care plans, most of whom have little experience in providing services to persons with severe and persistent mental illness. However, another factor in states' decisions to carve out mental health benefits has been advocacy by the specialized provider systems that serve this population to protect their market share.
Another boundary issue in designing managed care systems for persons with severe and persistent mental illness is whether to combine substance abuse programs with mental health services into an integrated managed care system. Although programmatically, there are strong reasons for bundling mental health and substance abuse benefits for this population in an integrated system, infrastructure issues and provider concerns often act to keep these services unbundled.
A final issue regarding the application of managed care models to persons with severe and persistent mental illness concerns the measurement of plan performance. What measures should purchasers (public or private) use to assess whether plans are doing a "good job?" Persons who support individuals with severe mental illness know that interventions of the highest quality can still lead to undesired outcomes in some individuals, while in other cases, people with mental illness somehow seem to get better or do okay despite inferior care or the absence of care. The relationship between good care and positive outcomes in this population is not straightforward, and the assessment of performance probably needs to measure average outcomes over sufficiently large samples of individuals, wherein the differentiation between inferior and superior care can be more reliability discerned.
Adults with Physical Disabilities and Persons with AIDS
The population of persons with severe and chronic physical disabilities, including persons with multiple sclerosis, cerebral palsy, muscular dystrophy, quadriplegia, and other conditions, encompasses a very broad range of disabilities and impairment levels. Persons with severe physical disabilities are often not well served by the fee-for-service health care system, and many experience the frustration of referrals to multiple specialists without any single physician taking overall responsibility for the oversight of their health care. If the care coordination functions of managed care models truly take hold, then managed care holds some promise for improving access and quality for persons with severe physical disabilities.
However, as with other disabled populations, many people with severe physical disabilities are skeptical that managed care organizations will provide them with access to comprehensive and coordinated medical care. Many worry that managed care organizations will be stringent in the allocation of resources in meeting their medical needs and will perceive them as "undesirable" enrollees, particularly if the cost of their care exceeds the average premium paid by their sponsor, be it an employer, Medicare, or Medicaid. For persons who require highly specialized care, many worry whether managed care plans will deny access to the most qualified specialists, and/or specialists with whom they have developed long-standing relationships.
On the purchaser side, private employers generally place little emphasis on ensuring that covered individuals with severe disabilities are adequately served in the managed care system. The disability programs of employers generally focus on short-term disability issues; the integrated management of their health insurance, workmen's compensation, and disability insurance programs; and rehabilitation initiatives which assist injured workers' to return to work as quickly as possible. The quality of health care provided to persons with severe and chronic conditions is generally not an issue of high concern to most private employers. Furthermore, the assessment of the performance of managed care plans by employers has largely focused on measures that are pertinent to large segments of their covered populations (e.g. prenatal care, immunizations, etc.) rather than on how plans treat individuals with rare conditions.
For persons with severe disabilities who do not have private insurance and are covered by Medicaid, it appears that mandatory enrollment in some kind of managed care system is increasingly inevitable. With completion of the enrollment of non-disabled Medicaid populations into managed care, states are now focusing their attention on the more difficult challenge of enrolling SSI recipients into managed care (Checkett, 1996). And unlike persons with severe mental illness, mental retardation and/or developmental disabilities, persons with severe physical disabilities generally do not have specific "sponsors" or "programs" within state government whose responsibility it is to look out for their welfare. Just as the needs of persons with physical disabilities often fall through the cracks in the current Medicaid system, there is equal danger that the needs of this population will be largely ignored in the headlong rush to achieve Medicaid savings through managed care approaches.
In contrast, persons with AIDS are receiving special attention in the development of Medicaid managed care models. Led by the model developed by the Community Medical Alliance in Boston, the concept of "specialized health plans" (SHPs) which target a single population type, is now being replicated in other states such as Maryland and New York. Specialized health plans are generally perceived as voluntary alternatives to mainstream managed care plans, rather than mandatory alternatives that persons with certain conditions would be required to enroll in. The development of specialized plans is not totally attributable to demand side factors. Another factor is that specialized provider networks with experience in providing health care services to specific populations want to be able to preserve their "product line" without having to diversify into being mainstream health plans.
The Community Medical Alliance model for managing the care of persons with AIDS places strong emphasis on the substitution of non-institutional care arrangements for institutional care, particularly during the terminal phases of the illness. The recruitment and training of medical care professionals that are committed to the treatment philosophy and culture of the Community Medical Alliance is another key component of the model.
Areas of Commonality Across Populations
Although children with severe disabilities, persons with severe and persistent mental illness, and adults with physical disabilities possess diverse characteristics that raise unique issues in the application of managed care models, there are some common characteristics shared by all of these populations. First, persons with severe disabilities of all types require access to specialty services that may be limited under managed care approaches. Closed panel plans may have few or no physicians with expertise in the care of conditions with low prevalence rates in the general population. Point-of-Service plans may allow enrollees to seek care outside of their networks, but at a higher cost to enrollees, who may have limited financial resources to utilize out-of-network providers.
Second, the health care costs of disabled populations are more predictable than the health care costs of non-disabled populations. Not only are they more predictable at the population level, but also, in many cases, at the individual level. This creates opportunities for health plans to maximize profitability by adopting business strategies to limit the enrollment (or increase disenrollment) of individuals whose health care costs are predictably above the payment rate made to the plan. Risk adjustment strategies which pay plans fairly for the expected costs of persons with disabilities, yet which still reward plans for efficient care, are critical to the application of managed care models to these populations, as well as to ensuring that persons with disabilities are provided quality care by the plans in which they are enrolled (Kronick et al, 1996). However, alternative mechanisms, other than risk adjusted capitated rates, for financially rewarding plans which enroll higher-cost individuals and providing quality services, also need to be explored. Risk-adjusted capitation may prove not to be the best solution to addressing these incentive issues, particularly given the technical and operational challenges of measuring risk and adjusting payments appropriately.
Third, the development of performance measures, which reliably assess the relative performance of plans in providing medical and supportive care to persons with disabilities of all types, is an area that requires extensive work and development. Workable approaches to eliciting the perspective of consumers, many of whom may have disabilities which impede traditional survey methods, is a key issue in the development of such measures.
Fourth, it is frequently the case that people with disabilities are receiving services from multiple payment sources and programs concurrently. The development of managed care models for these populations must respond to a set of needs that are broader than the financing and delivery of medical care. If care for these populations is to be truly integrated, then models need to be developed which consolidate the financing and delivery of health care services, rehabilitative services, long term care services, family supports, respite care, occupational supports, and personal counseling within integrated organizational structures. It may not be necessary for a single organization to possess all of these capabilities, but a managed care approach to these populations must include mechanisms for effectively coordinating the full array of medical and related services that are needed to help persons with disabilities maintain the highest level of independence possible.
What Does the Research Tell Us About the Impacts of Managed Care?
Empirical research which directly measures the health outcomes of persons with disabilities in fee-for-service versus managed care settings is extremely limited, and the research which has been conducted does not paint a consistent picture of the impacts of managed care. Research on the impacts of targeted managed care initiatives seems to paint a more positive picture, while general population studies of managed care impacts are more pessimistic. Also, considerably more research has been conducted of the impact of managed care on mental health populations than on populations with other types of disabilities.
Master et al (1996) describe improved outcomes among persons with severe disability and AIDS in a targeted Medicaid managed care program in Massachusetts. Positive outcomes included increased patient satisfaction, reduced inpatient hospital days, and improved decubitus ulcers and PCP. The study suggests that managed care can improve care for persons with severe disability through the use of innovative providers providing care in innovative settings, relative to the fee-for-service system. The results of this research may be questioned, however, given that the researchers also represent the senior management team of the managed care organization being studied. Similarly, Meyers et al (1987) found improved outcomes from managed care in a population of severely disabled adults in an independent living center, largely associated with increased resource allocation to care provided in the individual's home and centered around the person's individualized needs.
In an 11-year longitudinal study of persons with rheumatoid arthritis receiving care in fee-for-service settings versus prepaid group practice, Yelin et al (1996) found no evidence of differences in either the quantity of health care provided or in health care outcomes on either an annual or long-term basis across the systems of care.
Studies of populations in mainstream managed care plans seem less positive. An analysis of data from the Medical Outcomes Study (Ware et al, 1996) found that while health outcomes for the average patient did not differ between fee-for-service and managed care settings, health outcomes were decidedly poorer for patients who reported ill health at baseline. The study suggests that while managed care plans do quite well in maintaining the health of healthy patients, relative to fee-for-service, that people with higher medical needs fare less well in managed care, due to financial incentives among plans to reduce the level of resources applied to medical interventions. The findings of the Medical Outcomes Study support similar findings by the same research team ten years previously (Ware et al, 1986). Although the population of interest in the Ware study encompassed "chronically ill" persons, not persons with severe disabilities, it is reasonable to generalize the study findings to all populations with higher-than-average medical care needs. In another study of data from the Medical Outcomes Study, Safran et al (1992) found notable differences in dimensions of primary care provided to persons with chronic illness across fee-for-service plans, IPA-model plans, and traditional HMOs, but did not specifically associate these differing primary care paradigms with patient outcomes.
Research on the impacts of mental health managed care models is decidedly richer. The Medical Outcomes Study reported above found superior mental health outcomes in managed care for nonpoverty populations, but inferior outcomes in the poverty group (Ware et al, 1996). Wells et al (1990) found that one managed care network provided less intensive mental health services to their covered population but a higher quantity of services. Lurie et al (1992) found few differences in mental health outcomes among patients served in managed care versus fee-for-service with one exception--persons with schizophrenia showed superior outcomes in a fee-for-service setting. And in a study focusing on a population of persons with depression, Rogers et al (1993) reported that depressed patients declined, on average, in managed care settings, declines that were likely attributable to a drop-off in the prescription of anti-depressant drugs.
Other studies have reported more positive impacts of mental health managed care initiatives. Superior mental health outcomes under managed care, as well as reduced financial impacts on patients, were reported by Babigan et al (1992). Shern et al (1995) also reported greater reductions in problems, fewer unmet needs, and higher adherence to clinical protocols, among mental health clients in a managed care demonstration than in a comparison fee-for-service population.
A few studies have evaluated the impacts of mental health carve-out programs for Medicaid populations, and thus far, have generally reported favorable outcomes. Callahan et al (1995) conducted an evaluation of a Medicaid mental health carve-out in Massachusetts and reported that the carve-out vendor was successful in substantially lowering Medicaid costs for acute mental health services without any overall reduction in quality or access. Christianson et al (1995) also reported significant reductions in Medicaid expenditures for mental health services in the first year of a carve-out initiative, primarily due to reductions in inpatient admissions for mental health treatment, although mental health outcomes were not measured.
Studies that assess the impact of managed care on children with disabilities are very few, although a number of researchers have published on the potential dangers of managed care systems on children with disabilities. Fox et al (1993) reported findings from a survey of parents of children with disabilities, with mixed results. Parents were pleased with the reduced out-of-pocket costs associated with managed care systems, and with improved access to medical services, but at the same time reported increased difficulty obtaining access to specialty services and mental health care. The focus of managed care plans on requiring specialty care interventions to demonstrate rapid improvement was cited as a significant concern, and a barrier to care continuity.
Discussion: Is Managed Care for Children and Adults with Disabilities a Step Forward or a Step Backward?
Research on the impacts of managed care on children and adults with disabilities is decidedly mixed. The limited body of research published to date seems to suggest that the incentives of capitated financing mechanisms are not, in and of themselves, the primary determinants of outcomes. Rather, the research suggests that operational variables, i.e. how managed care models are applied, are equally important, if not more important, in determining how people with disabilities fare in the managed care world. Of particular interest is the nature of the managed care entity with whom the purchaser has contracted to provide care. Managed care organizations with missions to serve persons with disabilities, and organizations who provide specialized services, appear to achieve better outcomes for persons with disabilities than do mainstream plans which have no special focus on the needs of disabled populations.
As managed care models continue to evolve, and as purchasers increasingly pursue innovative managed care purchasing strategies, it will be increasingly important for researchers to help sort out which managed care models are associated with improved outcomes and reduced costs versus those managed care models which achieve reductions in health care costs only to the detriment of the populations they are intended to serve.
REFERENCES
Babigian, Haroutoun M., Olivia S. Mitchell, Phyllis E. Marshall, Sylvia K. Reed. 1992. A Mental Health Capitation Experiment: Evaluating the Monroe-Livingston Experience. Economics and Mental Health, ed. Richard G. Frank and Willard G. Manning, Jr. Baltimore: Johns Hopkins Press, pp. 307-331.
Bachman, Sara, Mimi Bernardin and Brian Burwell. 1996. Integrated Service Systems for Children With Disabilities. Unpublished.
Breakey, William and Donald Steinwachs. Forthcoming. Evaluation Baltimore Medicaid Mental Health Experiment.
Callahan, James J., Donald J. Shepard, Richard H. Beinecke, Mary Jo Larson, Doreen Cavanaugh. 1995. Mental Health/Substance Abuse Treatment in Managed Care: The Massachusetts Medicaid Experience. Health Affairs 14(3): 173-184.
Christianson, Jon B., Willard Manning, Nicole Lurie, Tamara J. Stoner, Donald Z. Gray, Michael Popkin, Sally Marriott. 1992. Utah's Prepaid Mental Health Plan: The First Year. Health Affairs 14(3): 160-172.
Fox, Harriette B., Lori B. Wicks, Paul W. Newacheck. 1993. Health Maintenance Organizations and Children With Special Health Needs: A Suitable Match? AJDC 147 (May): 546-552.
Horowitz, Sarah McCue and Ruth E. K. Stein. 1990. Health Maintenance Organizations vs., Indemnity Insurance for Children With Chronic Illness: Trading Gaps in Coverage. AJDC 144 (May); 581-586.
Kronick, Richard, Tony Dreyfus, Lora Lee, Zhiyuan Zho. 1996. Diagnostic Risk Adjustment for Medicaid: The Disability Payment System. Health Care Financing Review 17(3): 7-34. [Executive Summary]
Kaplan, Sherrie H. and Sheldon Greenfield. 1994. New Statewide Health Reform Initiatives.Milbank Quarterly 72(4): 695-699.
Lurie, Nicole, Ira Moscovice, Jon B. Christianson, Michael K. Popkin. 1992. Does Capitation Affect the Health of the Chronically Mentally Ill? JAMA 267(24): 3300-3304.
McFarland, Bentson H., Douglas A. Bigelow, Jay C. Smith, Mark C. Hornbrook, Ala Mofidi, Patrick Payton. 1995. A Capitated Payment System for Involuntary Mental Health Clients. Health Affairs 14(3): 185-196.
Master, Robert, Tony Dreyfus, Sharon Connors, Carol Tobias, Zhiyuan Zhou, Richard Kronick. 1996. The Community Medical Alliance: An Integrated System of Care in Greater Boston for People with Severe Disability and AIDS. Managed Care Quarterly 4(2): 26-37.
Mechanic, David, Mark Schlesinger, Donna D. McAlpine. 1995. Management of Mental Health and Substance Abuse Services: State of the Art and Early Results. Milbank Quarterly 73(1): 19-55.
Meyers, Allan R., Adrienne Cupples, Ruth I. Lederman, Laurence G. Branch, Marie Feltin, Robert J. Master, Doreen Nicastro, Mary Glover, Denise Kress. 1987. A Prospective Evaluation of the Effect of Managed Care on Medical Care Utilization Among Severely Disabled Independently Living Adults. Medical Care 25(11): 1057-1068.
Neff, John M. and Gerard Anderson. 1995. Protecting Children With Chronic Illness in a Competitive Marketplace. JAMA 274(23): 1866-1869.
Oliver, Michael. 1996. Understanding Disability: From Theory to Practice. New York: St. Martin's.
Rogers, William H., Kenneth B. Wells, Lisa S. Meredith, Roland Sturm, M. Audrey Burnam. 1993. Outcomes for Adult Outpatients With Depression Under Prepaid or Fee-for-Service Financing. Archives of General Psychiatry 50 (July): 517-525.
Safran, Dana Gelb, Alvin R. Tarlov, William H. Rogers. 1994. Primary Care Performance In Fee-for-Service and Prepaid Health Care Systems. JAMA 271(20): 1579-1586.
Schlesinger, Mark. 1986. On the Limits of Expanding Health Care Reform: Chronic Care in Prepaid Settings. Milbank Quarterly 64(2): 189-215.
Shern, David L., Sheila A. Donahue, Chip Felton, Genevive R. Joseph and Norman Brier. Partial Capitation Versus Fee-for-Service in Mental Health Care. Health Affairs 14(3): 208-219.
Stuart, Mary E. 1994. Redefining Boundaries in the Financing and Care of Diabetes: The Maryland Experience. Milbank Quarterly 72(4): 679-694.
Sturm, Roland, Catherine A. Jackson, Lisa S. Meredith, Winnie Yip, Willard G. Manning, William H. Rogers, Kenneth B. Wells. 1995. Mental Health Care Utilization in Prepaid and Fee-for-Service Plans Among Depressed Patients in the Medical Outcomes Study. Health Services Research 30(2): 319-340.
Sturm, Roland, Elizabeth A. McGlynn, Lisa S. Meredith, Kenneth B. Wells, Willard G. Manning, William H. Rogers. 1994. Switches Between Prepaid and Fee-for-Service Health Systems Among Depressed Outpatients: Results from the Medical Outcomes Study. Medical Care 32(9): 917-929.
Sturm, Roland, Lisa S. Meredith, Kenneth B. Wells. 1996. Provider Choice and Continuity for the Treatment of Depression. Medical Care 34(7): 723-34.
U.S. General Accounting Office. 1996.Medicaid Managed Care: Serving the Disabled Challenges State Programs. July, GAO/HEHS-96-136.
Ware, John, Jr., William H. Rogers, Allyson Ross Davies, George A. Goldberg, Robert H. Brook, Emmet B. Keeler, Cathy Donald Sherbourne, Patricia Camp, Joseph P. Newhouse. 1986. Comparison of Health Outcomes at a Health Maintenance Organization with Those of Fee-for-Service Care. Lancet (May 3): 1017-1022.
Ware, John E., Jr., Martha S. Bayliss, William H. Rogers, Mark Kosinski, Alvin R. Tarlov. 1996. Differences in 4-Year Health Outcomes for Elderly and Poor, Chronically Ill Patients Treated in HMO and Fee-for-Service Systems. JAMA 276 (13): 1039-1047.
Wells, Kenneth B., Boris M. Astrachan, Gary L. Tischler and Jurgen Unutger. 1995. Issues and Approaches in Evaluating Managed Mental Health Care. Milbank Quarterly 17(1): 57-75.
Wells, Kenneth B., M. Audrey Burnam and Patti Camp. 1995. Severity of Depression in Prepaid and Fee-for-Service General Medical and Mental Health Specialty Practices. Medical Care 33(4): 350-364.
Wells, Kenneth B., Willard G. Manning, Jr. and R. Burciaga Valdez. 1990. The Effects of a Prepaid Group Practice on Mental Health Outcomes. Health Services Research 25(4): 615-625.
Wells, Kenneth B., Roland Sturm, Cathy Sherbourne and Lisa Meredith. 1996. Caring for Depression. A Rand Study. (Uncorrected page proofs.) Cambridge: Harvard University Press.
Yelin, Edward H., Martin A. Shearn, Wallace V. Epstein. 1986. Health Outcomes for a Chronic Disease in Prepaid Group Practice and Fee for Service Settings: The Case of Rheumatoid Arthritis. Medical Care 24(3): 236-247.
Yelin, Edward H., Lindsey A. Criswell, Paul G. Feigenbaum. 1996. Health Care Utilization and Outcomes Among Persons with Rheumatoid Arthritis in Fee-for-Service and Prepaid Group Practice Settings. JAMA 276(13): 1048-1053.
Session 1: Impact of Managed Care on Children with Disabilities
Reactor Biographies
Ruth E.K. Stein, M.D.
Ruth Stein is Professor and Vice Chairman of the Department of Pediatrics and Director of General Pediatrics at Albert Einstein College of Medicine. She is also Pediatrician-in-Chief at Jacobi Medical Center. She has been involved in developing models of care for children with special health care needs for many years. Her research is on chronic physical disorders in childhood and their psychological and social consequences. From 1983 to 1995, she was also the Principal Investigator of the Preventive Intervention Research Center for Child Health at the Albert Einstein College of Medicine/Montefiore Medical Center. She recently spent a sabbatical at the United Hospital Fund examining issues for the pediatric population under managed care.
Nancy R. Thaler
Nancy Thaler has been Deputy Secretary for Mental Retardation in the Pennsylvania Department of Public Welfare since 1992. She served as the Director, Bureau of Community Programs, for six years prior to being appointed Deputy Secretary. Before her career in State government, she worked for 16 years in a large nonprofit agency in southeastern Pennsylvania, Ken-Crest Services. While with that agency, she served eight years as a direct care worker, including four years as a houseparent and another eight years in administrative positions.
As Deputy Secretary for Mental Retardation, Ms. Thaler is responsible for the State's services to people with mental retardation. These services affect 3,240 people in State institutions, and 63,000 people in the community.
Evaluation of the District of Columbia's Demonstration Program: Managed Care System for Disabled and Special Needs Children
Carol Irvin, Ph.D.
As a Health Economist at Abt Associates, Inc., Carol Irvin has conducted numerous studies on the use, costs, and outcomes of health care services provided under managed care and fee-for-service arrangements. In current work she is analyzing enrollment patterns among applicants to the Program for All-Inclusive Care for the Elderly (PACE)--a capitated day health center program for frail elders. Dr. Irvin is also currently involved in analyzing the impacts of a new pharmaceutical product on the use and costs of health care services and labor market participation among individuals with chronic progressive multiple sclerosis. In earlier work funded by the Health Care Financing Administration, she has done comparisons of care and customer satisfaction of families in Florida, Michigan, and Maine enrolled in Medicaid managed care and fee-for-service providers. She has also analyzed the impact on health care use and economic outcomes of a national capitation demonstration project among mine workers--a high risk industry population.
Dr. Irvin has also been actively researching health care issues pertaining to the maternal and child populations. Research in this area include assessing Missouri's 1988 Medicaid expansion and its impacts on enrollment patterns of pregnant women and infants, prenatal care, birth outcomes, and infant health care. Related work includes on-going analysis of the Community Integrated Service Systems (CISS) serving women and children and a series of analyses of the Special Supplemental Food Program for Women, Infants, and Children (WIC) program.
THE DEMONSTRATION
- Eligible Population
- Plan Structure
- Provider Network
- Benefit Plan
ENROLLMENT
- Enrollment Procedures
- Challenges to the Enrollment Process
- Current Enrollment Experience
COMPONENTS OF THE EVALUATION
- Analyses of Enrollment
- Implementation of the Demonstration
- Outcome Analyses
DATA TO BE COLLECTED
- Secondary Data Sources
- MMIS
- Plan encounter data
- SSI eligibility data
- Primary Data
- Key informant interviews
- Focus groups
- Client survey
- Medical record review
PRIMARY RESEARCH QUESTIONS
- Analyses of Enrollment
- Which children enroll?
- Which children are long-term enrollees?
- Implementation of the Demonstration
- What can other states and managed care plans learn?
- Outcomes Analyses
- What are the experiences of the District, the managed care plan, the providers, and the children and their families under this type of health care system?
Families' Out-of-Pocket Expenses When Caring for Children With Special Needs: A Preliminary Report Comparing Children in Medicaid and a Commercial Product Line-- Presentation Summary
Elizabeth A. Shenkman, Ph.D.
Elizabeth Shenkman is the Coordinator of Research and Program Evaluation at the Institute for Child Health Policy of the State University System of Florida, and an Assistant Professor of Pediatrics at the University of Florida. Dr. Shenkman is the Principal Investigator on the following research projects: Contractual Arrangements with Physicians: Implications for Pediatric Health Care, funded by the Robert Wood Johnson Foundation; Managed Care: Implications for Families' Out-of-Pocket Expenses When Caring for Children with Special Health Care Needs, funded by the Department of Health and Human Services, Assistant Secretary for Planning and Evaluation, Office of Health Policy; and the School Enrollment-Based Health Insurance (SEBHI) Program Evaluation, funded by the Florida Healthy Kids Corporation. In addition, she is the Co-Principal Investigator for the following project: Children with Special Health Care Needs Within Managed Care: the Department of Empirically-Based Models, funded by the Department of Health and Human Services, Maternal and Child Health Bureau.
BACKGROUND
- Concerns about children with special needs in managed care environments
- Limited data from managed care organizations about enrollees
- Strong financial burdens in fee-for-service system
- Will these burdens be greater in managed care?
PURPOSE
- Present preliminary information about families' out-of-pocket expenses when caring for children with special needs
- Two groups of children
- Commercially-insured through a special program
- Medicaid fee-for-service or primary care case management
- Continuing to collect data for both of these groups
THE THIRD PARTY PAYERS
- Commercial Product Line
- Insured through a special program providing subsidized premiums
- About 30,000 enrollees
- Comprehensive benefit package
- Private not-for-profit corporation negotiates contracts with health maintenance organizations
- Health maintenance organizations bear risk and maintain the provider network
- Currently four participating
- Primary care provider serving as gatekeepers
- Program enrollment is voluntary
- Medicaid Product Line
- About 49% of the children are enrolled in primary care case management
- Comprehensive benefit package
- Children covered varies according to Federal Poverty Level
- Medically Need Program available
THE BENEFIT PACKAGE
- Well child care visits and immunizations
- Primary and specialty physician office visits
- In-patient hospital care
- Surgical procedures
- Emergency services and transportation
- Prescriptions
- Vision screening and glasses
- Hearing screening and hearing aids
- Physical, occupational, speech therapy
- Mental health services
HOW WERE THE CHILDREN SELECTED?
- Identified initially from claims data from participating health maintenance organizations and Florida Medicaid
- Used International Classification of Diseases, 9th Revision
- High and low prevalence conditions included
- Screening questions used to identify those with greatest needs
- Because of a physical or mental condition, does your child require more supervision than other children of his/her age?
- Does your child require extra or specialized medical care, therapies, supplies, or medical equipment because of a special health care need?
- Has your child had his/her special health care need for 6 months or longer?
- Must meet a or b or c
OUT-OF-POCKET EXPENSES MEASURED
- Direct expenses--medical care expenditures for diagnosis, treatment, continuing care, rehabilitation and terminal care
- Other direct expenses--expenditures items or services such as respite care, special diets or formulas, medical supplies, special or additional clothing, and others
- Indirect expenses--time spent in providing care for the child and lost employment opportunities
CAREGIVERS' OUT-OF-POCKET EXPENSE SURVEY
- Panel of reviewers
- Field testing
- 45 to 60 minutes to administer as telephone survey
WHAT WAS CONSIDERED AN OUT-OF-POCKET EXPENSE
- If the item or service was paid for entirely or in part by:
- A parent or guardian
- Another family member residing in the household
- The child's supplemental security income check
- Co-payments categorized according to the expense incurred
OTHER CATEGORIES MEASURED:
- Child's functioning using the Functional Status Rating Scale short form
- Addresses mood, interest level, communication
- Diagnostic information
- Demographic information
DIAGNOSTIC CATEGORIES
- Array of diagnoses represented
- Used diagnostic categories to group the children
- Also used scores on Functional Status Rating Scale to describe the children
- Wide variation in functioning seen both within and between diagnostic groupings
SUMMARY AND RECOMMENDATIONS
- Highest expenses for families in "Other Direct" category
- Regressive patten of expenditures for both groups of children
- Benefit packages must consider broad array of services and items
- Significant caregiving time
- Health care cost savings can be achieved; but at what price to families?
FUTURE WORK
- Include influence of participation in State Title V Children with Special Health Care Needs Programs
- Explore unmet needs
- Explore lost employment opportunities
- Link to actual health care use data
| TABLE 1. Total Number of Children Identified | ||
|---|---|---|
| Category | Florida Medicaid | Commercially Insured |
| Total number of children screened for ICD-9-CM codes | 307,241 | 27,487 |
| Total number of children enrolled within the last three months of selecting the sample | 253,562 | 13,591 |
| Total number of children with at least one ICD-9-CM code enrolled in the last three months of selecting the sample | 84,315 | 1,916 |
| Percentage of enrollees with at least one ICD-9-CM code and enrolled within the last three months of selecting the sample | 33% | 14% |
| TABLE 2. Families Screened for Study Participation and Surveys Completed | ||
|---|---|---|
| Category | Florida Medicaid | Commercially Insured |
| Completed screening questions | 112 | 547 |
| Did not qualify | 12 (10%) | 128 (23%) |
| Qualified but refused to participate | 24 | 32 |
| Qualified and completed a survey | 76 | 387 |
| TABLE 3. Demographic Characteristics of the Study Sample | ||
|---|---|---|
| Category | Children Receiving Medicaid | Commercially Insured Children |
| Respondent Gender - Female - Male |
97% 3% |
95% 5% |
| Respondent Age | 37.43 ± 10.90 | 39.55 ± 9.99 |
| Child's Age | 9.23 ± 5.23 | 10.48 ± 6.21 |
| FSII (R) Score | 78.53 ± 18.69 (range 17 to 100) |
87.20 ± 15.33 (range 21 to 100) |
| Child's Racial Background - White - African-American - Other |
80% 15% 5% |
85% 8% 7% |
| Child's Ethnicity - Hispanic - Non-Hispanic |
11% 89% |
12% 88% |
| Family Income Average Family Income - less than $9,999 - $10,000 to 14,999 - $15,000 to 19,999 - $20,000 to 24,999 - $25,000 to 34,999 - $35,000 to 44,999 - $45,000 or more - Don't know/refused |
30% 17% 14% 12% 10% 7% 7% 2% |
13% 22% 19% 15% 12% 8% 5% 7% |
| Cash Assistance-SSI for Child - Used actual records to respond to questions - Use an estimate of expenses |
35% 35% 65% |
0% 47% 53% |
| TABLE 4. Children's Primary Diagnostic Categories and FSII(R) Scores | ||||
|---|---|---|---|---|
| Category | Children Receiving Medicaid (N=76) | Commercially Insured Children (N=387) | ||
| Percent Children | FSII(R) Mean Core and Standard Dev | Percent Children | FSII(R) Mean Core and Standard Dev | |
| Mental and Emotional Disorders | 16% | 67 ± 20 | 39% | 75 ± 22 |
| Respiratory System | 13% | 69 ± 206 | 40% | 90 ± 15 |
| Neurological | 25% | 76 ± 19 | 4% | 82 ± 18 |
| Musculoskeletal System | 17% | 86 ± 13 | 2% | 92 ± 10 |
| Special Sense Organs | 8% | 80 ± 18 | 4% | 86 ± 15 |
| Endocrine System | <1% | 71 ± 0 | 3% | 90 ± 12 |
| Cardiovascular | 4% | 88 ± 12 | <1% | 88 ± 0 |
| Digestive System | 3% | 88 ± 20 | <1% | 90 ± 0 |
| Multiple Body Systems | 6% | 88 ± 09 | 0% | NA |
| Genito-Urinary System | 1% | 76 ± 10 | 1% | 86 ± 18 |
| Hemic and Lympathic System | <1% | 67 ± 0 | 0% | NA |
| Neoplastic Diseases--Malignant | <1% | 100 ± 0 | <1% | 86 ± 0 |
| Immune System | 2% | 87 ± 13 | <1% | 87 ± 0 |
| Growth Impairment | 2% | 96 ± 7 | 0% | NA |
| TABLE 5. Direct and Other Direct Expenses for the Month and Year in Dollars | ||||
|---|---|---|---|---|
| Category | Children Receiving Medicaid | Commercially Insured Children | ||
| % Reporting Expense | Mean | % Reporting Expense | Mean | |
| Direct Expenses Per Month | 37% | 131.89 ± 393.35 | 87% | 28.59 ± 139.2 |
| Direct Expenses Per Year | 38% | 1,072 ± 1,4629.1 | 86% | 384.11 ± 1,582 |
| Other Direct Expenses Per Month | 89% | 162.57 ± 305.93 | 63% | 30.79 ± 69.8 |
| Other Direct Expenses Per Year | 89% | 1,444.1 ± 1,779.2 | 63% | 689.4 ± 2,502.6 |
| TABLE 6. Direct and Other Direct Expenses as a Percent of Family Income | ||||
|---|---|---|---|---|
| Category | Children Receiving Medicaid | Commercially Insured Children | ||
| % Reporting Expense | Mean | % Reporting Expense | Mean | |
| Direct Expenses Per Month | 37% | 4.87 ± 32.4 | 87% | 2.32 ± 10.38 |
| Direct Expenses Per Year | 36% | 4.33 ± 12.2 | 87% | 2.8 ± 12.78 |
| Other Direct Expenses Per Month | 89% | 12.79 ± 21.9 | 63% | 2.11 ± 6.20 |
| Other Direct Expenses Per Year | 88% | 11.25 ± 25.6 | 63% | 2.25 ± 10.98 |
| TABLE 7. Caregiving Time | ||
|---|---|---|
| Category | Percent Reporting | Mean Hours and Standard Deviation |
| Medicaid | 85% | 15.33 ± 9.19 |
| Commercially Insured | 48% | 8.76 ± 3.2 |
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The Managed Care Enhancement Project for Children with Special Health Care Needs
Deborah Allen
As the Director of the Division for Children with Special Health Care Needs of the Massachusetts Department of Public Health, Deborah Allen is responsible for assuring family-centered, community-based care for children with special health care needs and their families. Her division is the lead agency for implementation of Part H of the IDEA in Massachusetts and for the provision of case management services to SSI-eligible children. Ms. Allen is the Principal Investigator for the federally funded Managed Care Enhancement Project for Children with Special Health Care Needs. She is also responsible for two grants funded by Title IV of the Ryan White Care Act: MassCARE (Massachusetts Community AIDS Resource Enhancement), which focuses on pediatric and family care needs, and MCAP (the Massachusetts Women's HIV Care and Advocacy Project), which promotes identification and care of women with HIV prior to or early in pregnancy.
Ms. Allen has master's degrees in Health Policy and Management and Maternal and Child Health from the Harvard School of Public Health and is, as we speak, in the final stages of her doctoral research on "Predictors of Voluntary HIV Testing During Pregnancy," also at Harvard. She is absolutely committed to making this the last formal education she ever undertakes.
OUTLINE OF PRESENTATION
- Health care in Massachusetts
- MassHealth Managed Care
- The Managed Care Enhancement Project
- Needs assessment
- Interventions
- Evaluation
- Concluding thoughts
HEALTH CARE IN MASSACHUSETTS--A WHIRLWIND TOUR
- Extensive tertiary medical system
- Widespread influence of academic medicine
- Extensive CHC network
- Extensive HMO penetration
- No county health departments
- Limited clinical role of local health departments
- Comprehensive Medicaid program
MASSHEALTH OVERVIEW
- Target population - 450,000 Medicaid recipients
- All Medicaid clients except:
- Individuals with private insurance and Medicaid
- Individuals with Medicare and Medicaid
- Enrollment started April, 1992
SSI RECIPIENTS IN MASSHEALTH
- Special procedures for
- Outreach
- Enrollment
- Assignment
- For adults and children on SSI
MASSHEALTH COMPONENTS
- Health Benefits Advisor Program
- Primary Care Clinician Program
- Mental Health/Substance Abuse Program
- HMO Program
PCC PROGRAM
- Approximately 1300 practices
- Almost 2500 physicians
- Eligible providers are:
- Internists
- Pediatricians
- Family practitioners
- Ob-gyns
- Nurse practitioners
PCC PROGRAM OPERATIONS
- No capitation at present
- PCC receives $10 bonus per primary or preventive visit
- PCC responsible for:
- Primary care
- Specialty referrals
- Authorization of most medical services
- Mental health, substance abuse do not require PCC authorization
PCC PROGRAM ENROLLMENT
- Current enrollment approximately 290,000
- 80% of Medicaid enrollees in PCC program
- 80% of children with special health care needs in PCC program
HMO PROGRAM
- 8 vendors statewide
- 1 special contract for disabled individuals
- Enrollment is voluntary
- Current enrollment 81,000
MANAGED CARE ENHANCEMENT PROJECT OVERVIEW
- Four year grant ending Sept. 1997
- Funded by HRSA--Maternal and Child Health Bureau
- Joint Title V--Division of Medical Assistance administration
- Active, diverse advisory committee
MCEP GOALS
- Improve health status of children with special health care needs in MassHealth
- Improve quality of life for families of children with special health care needs in MassHealth
- Increase appropriate use of health resources for care of children with special health care needs while averting unnecessary costs
- Enhance understanding of optimal systems of care for children with special health care needs
MCEP NEEDS ASSESSMENT
- Utilization data
- Family survey
- Provider survey
- Family focus groups
- Provider focus groups
- National key informant interviews
FINDINGS ON UTILIZATION
- CSHCN claims reveal:
- Equal or greater use of primary care
- More use of
- Inpatient care
- Home health care
- Prescriptions
- DME
- Less use of
- Dental
- Than other children in MassHealth Managed Care
FAMILY SURVEY METHODS
- Inclusion criteria
- SSI enrollment or at least one EI claim
- At least one full year of Medicaid with < 45 day interruption
- Sample
- 1,000 families chosen at random
- Overselection of Spanish-speaking families
- Implementation
- Two mailings in English and Spanish
- 800 number for questions or if phone administration preferred
- Response
- 32% response rate
- 254 English surveys returned or completed by phone
- 67 Spanish surveys returned or completed by phone
FAMILY SURVEY FINDINGS
- High level of general satisfaction
- Areas for improvement
- Access to information
- Family supports
- Coordination of services
- Survey also revealed weak links between primary care and
- Schools
- Discharge planning
- Home care
PROVIDER SURVEY METHODS
- Target population
- Pediatricians, family practitioners
- Participating in Primary Care Clinician Plan
- Sample
- 906 physicians
- Implementation
- Initial attempt at phone administration
- Shift to administration by mail
- Response
- 31% response rate
- 196 surveys completed by mail
- 89 surveys completed by phone
PROVIDER SURVEY FINDINGS
- High level of general satisfaction
- Some areas of provider concern
- Coordination of care
- Information needs
- Time constraints
OTHER NEEDS ASSESSMENT STRATEGIES
- Confirmed and expanded upon needs assessment findings
- Identified possible interventions
INTERVENTIONS
- Special Care Coordinator
- 4 sites
- 3.5 FTE's
- Parent manual
- Focus on system "how to's"
- Parent role in writing, editing
- Enhanced provider education
- Enhanced customer service
- Enhanced PCC/case management linkage
EVALUATION OF SCC INTERVENTION
- Parent questionnaires
- Two points in time
- Comparison group
- Child functional status
- Family functional status
- Parent satisfaction
- Utilization
- Admissions
- ER use
- EPSDT compliance
- Over one year relative to comparison group
- Post-implementation PCC review
- Qualitative interviews at 4 sites
EVALUATION OF MANUAL
- Parent survey
- Use
- Strengths and weaknesses
- Usefulness
- Provider survey
- Use
- Strengths and weaknesses
- Impact on practice
CONCLUDING THOUGHTS
- Medicaid managed care offers opportunities to change system for the better
- To seize that opportunity must have relevant players in a given state at the table listening to each other
- Key elements to make managed care work for cshcn are being to emerge
- These elements must be addressed at each stage of implementation, from early planning to final evaluation
| TABLE 1. Costs of Care for CSHCN | |||
|---|---|---|---|
| Average per member per month | |||
| CSHSN Other children in MassHealth |
$360 $58 |
||
| Maximum per member per month | |||
| CSHSN Other children in MassHealth |
$26,519 $12,769 |
||
| TABLE 2. Service Types as Percent of Total Cost for CSHCN | |
|---|---|
| Home health | 23% |
| Inpatient care | 22% |
| Prescriptions | 13% |
| DME | 6% |
| Primary care visits | 6% |
| Specialty visits | 6% |
| ER, transportation, dental | <2% |
| Other | 13% |
Planning Grant: Services for Children with Chronic Illness and Disease in an HMO
Barbara E. Staub, M.D.
Barbara Staub has been at the White Bear Lake Clinic for 13½ years and enjoys her practice. As a general pediatrician, she sees a wide range of illness as well as doing a lot of preventive, well-child care. Dr. Staub's special interests are in chronic illness and disability.
Dr. Staub received her medical degree at the Albany Medical College in 1980. She did her pediatric internship and residency at the University of Minnesota Medical School and was board certified in 1986. Her other professional activities have been a Clinical Assistant Professor, Department of Pediatrics, University of Minnesota Medical School; and Fellow, American Board of Pediatrics.
A COLLABORATIVE PROJECT
- PACER Center
- University of Minnesota
- HealthPartners
STUDY OBJECTIVES
- Comprehensive assessment of the needs and services, and the costs of services for a pediatric population with chronic illness and disability in a managed care environment.
- Examine the interface between our managed care system and education and social services.
STUDY COMPONENTS
- Parental Evaluation
- Cost and Utilization Data
- Primary Care Physician Survey
- Community Advisory Board
PARENTAL ASSESSMENT
- Family Advisory Board
- Family Interviews
PARENT ADVISORY BOARD
- Case Management Services Desired
- Mental Health Services Desired
- Information Source About HP Policies Desired
PHYSICIAN SURVEY
- 29 Physicians Surveyed
- Time
- Benefits
- Care Coordination
COMMUNITY ADVISORY COUNCIL
- Case Management
- Agency's Perspective
- Family Perspective
- Improved Communication Between Agencies and Health Systems
- Monitoring of Short and Long-Term Outcomes
- Monitoring of Costs
HEALTHPARTNERS PROVIDES
- Access to Subspecialist Care
- Medical Care Management by Pediatrician
- Benefits which are Supplemented by other Sources
NEXT STEPS
- Provide Family-Centered Case Management
- Address Mental Health Needs
- Provide Comprehensive Assessment of Total Costs
- Create Outcome Measures
- Provide Coordination among Agencies Involved in these Children's Lives
| TABLE 1. The Sample by Condition and Age | |||
|---|---|---|---|
| Diagnoses | Ages 1-4 years | Ages 5-11 years | Ages 12-20 years |
| Cystic Fibrosis | 2 | 2 | 2 |
| Cerebral Palsy | 2 | 2 | 2 |
| Trisomy 21 | 2 | 2 | 2 |
| Muscular Dystrophy | 1 | 1 | 1 |
| Juvenile Onset Diabetes Mellitus | 1 | 1 | 1 |
| Myelomeningocele | 2 | 2 | 2 |
| Autism | 1 | 1 | 1 |
| Blind/Deaf | 2 | ||
| TABLE 2. Demographics Data | ||
|---|---|---|
| Ethnicity | N | % |
| White | 33 | 94.3 |
| Hispanic | 1 | 2.9 |
| Other | 1 | 2.9 |
| Parent Education | ||
| Vocational School | 3 | 8.6 |
| Some College | 14 | 40.0 |
| College | 12 | 34.3 |
| Graduate | 5 | 14.3 |
| Family Income | ||
| $20,000-40,000 | 13 | 37.1 |
| $40,000-70,000 | 15 | 42.9 |
| $70,000+ | 7 | 14.3 |
| TABLE 3. Impact: Does Child's Condition Affect Ability of Parent to be Employed? | ||
|---|---|---|
| Response | N | % |
| No | 25 | 71.4 |
| Yes | 10 | 28.6 |
| TABLE 4. Supplemental Funding/Insurance Source | ||
|---|---|---|
| Funding Source | Yes (receive) | No (did not receive) |
| TEFRA | 19 (54.3%) | 16 (45.7%) |
| SSI | 4 (11.4%) | 31 (88.6%) |
| Medicaid | 4 (11.4%) | 31 (88.6%) |
| Vocational Rehabilitation | 4 (11.4%) | 31 (88.6%) |
| WIC | 3 (8.6%) | 32 (91.4%) |
| Family Subsidy | 2 (5.7%) | 33 (94.2%) |
| Title V | - | 35 (100%) |
| AFDC | - | 35 (100%) |
| TABLE 5. Services Received and Payment Source | |||||
|---|---|---|---|---|---|
| Service | # Received | Payment Sources* | |||
| (N) | HP | TEFRA | School | Other | |
| OT | 19 | 3 | 3 | 16 | 1 |
| PT | 15 | 5 | 4 | 10 | 1 |
| Speech and Language | 13 | - | 4 | 10 | 1 |
| Skilled Nursing | 3 | 1 | 2 | 1 | 1 |
| Personal Care Attendant | 12 | - | 7 | 2 | 4 |
| Respiratory Therapy | 6 | 3 | 2 | 1 | - |
| Mental Health | 2 | 2 | - | - | - |
| Medication | 28 | 24 | 11 | - | 21 |
| DME | 12 | 9 | 6 | - | 8 |
| *Many families receive more than one payment source. | |||||
 |
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State Medicaid Managed Care Policies Affecting Children with Chronic or Disabling Conditions
Harriette B. Fox
Harriette Fox is the President of Fox Health Policy Consultants, a small Washington-based consulting firm specializing in the financing and delivery of maternal and child health services, and the co-director of the Maternal and Child Health Policy Research Center. She has had extensive experience managing projects examining Medicaid, private health insurance, and other financing arrangements to support services to children, with a particular focus on issues pertaining to managed care and health insurance reform. Her work has included analyses of Federal laws and policy options; evaluations of State Medicaid and maternal and child health programs; surveys of State and private industry insurance practices; and consultation to numerous State and private organizations. She has published extensively on the subject of health care financing and children. Before establishing Fox Health Policy Consultants in 1982, Ms. Fox was the Senior Program Analyst for the Select Panel for the Promotion of Child Health. She also had served as a consultant to the Institute of Medicine and the National Health Policy Forum.
Margaret McManus
Margaret McManus is President of McManus Health Policy, Inc., a small consulting firm which specializes in managed care and health insurance reform affecting children. She also co-directs a Maternal and Child Health Policy Research Center for Paul Newacheck and Harriette Fox, funded by the Federal Maternal and Child Health Bureau. For the past 15 years, Ms. McManus has consulted with the American Academy of Pediatrics' Committee on Child Health Financing and a variety of other national, State, and local organizations. She has recently assisted the Maternal and Child Health Bureau in convening a series of managed care work groups on definitions, capitation and risk adjustment, quality of care, and family participation. Ms. McManus has published extensively on the subject of health care financing and children. Most recently, with Harriette Fox, she has completed a report entitled, Medicaid Managed Care for Children with Chronic or Disabling Conditions: Improved Strategies for States and Plans.
| TABLE 1. State Medicaid Policies Regarding Children Served by Fully Capitated Plans DRAFT-Not for Publication |
||||
|---|---|---|---|---|
| State | Categorical Groups Enrolled | Voluntary or Mandatory Enrollment1 | Specific Exemptions for Non-institutionalized Special-Needs Children | Pediatric Services Carved Out of Managed Care Contracts2 |
| Arizona | AFDC, AFDC-related, SSI | Mandatory | Children receiving developmental disability services | Mental health and substance abuse (capitated), hospice, personal care, specialty services for CSHN-eligible children |
| California4 | AFDC, AFDC-related, SSI, Foster Care | Mandatory in 3 counties; voluntary in 17 counties; mandatory for AFDC only in one county | None | Mental health services for SED-eligible children, intensive substance abuse, early intervention, health-related special education, dental5(capitated), certain comprehensive case management, specialty services for CSHN-eligible children |
| Colorado | AFDC, AFDC-related, SSI, Foster Care | Voluntary | None | Intensive mental health, certain substance abuse, intensive ancillary therapies, dental, hospice, personal care |
| Delaware | AFDC, AFDC-related, SSI, Foster Care | Voluntary | None | Mental health, substance abuse, health-related special education, dental, prescription drugs |
| District of Columbia | AFDC, AFDC-related | Voluntary | None | Mental health, substance abuse, early intervention, health-related special education, dental, vision |
| Florida | AFDC, AFDC-related, SSI, Foster Care | Voluntary | Children receiving CSHN services | Intensive mental health, intensive substance abuse, hospice, dental5, vision5, personal care, multi-handicap assessments, specialized services for foster care children |
| Hawaii | AFDC, AFDC-related, Foster Care, Demonstration Eligibles | Mandatory | None | Mental health services for SED-eligible children (capitated), dental (capitated), personal care |
| Illinois | AFDC | Voluntary | None | Dental (capitated), vision, comprehensive case management |
| Indiana | AFDC, AFDC-related | Voluntary | None | Mental health, substance abuse, vision |
| Iowa | AFDC, AFDC-related6 | Voluntary | None | Substance abuse, health-related special education, dental, prescription drugs5, durable medical equipment5 |
| Maryland | AFDC, AFDC-related, SSI | Voluntary | None | Certain early intervention, certain health-related special education, hospice, personal care, certain EPSDT expanded benefits7 |
| Massachusetts | AFDC, AFDC-related, SSI | Voluntary | None | Dental, prescription drugs, vision, personal care, intensive durable mental equipment5 |
| Michigan | AFDC, AFDC-related, SSI, Foster Care | Voluntary | Children receiving CSHN services | Intensive mental health, health-related special education, certain dental, personal care |
| Minnesota | AFDC, AFDC-related | Mandatory in eight counties; voluntary in one county | Children who are determined to be seriously emotionally disturbed prior to enrollment, determined blind or disabled but not eligible for SSI, likely to be terminally ill, or receiving an adoption subsidy8 | Case management for SED-eligible children |
| Missouri | AFDC | Mandatory | None | Mental health services for SED-eligible children, intensive substance abuse, health-related special education, dental, prescription drugs, hospice, certain case management, EPSDT expanded benefits |
| New Hampshire | AFDC, AFDC-related, Foster Care | Voluntary | None | Intensive mental health, intensive substance abuse, intensive ancillary therapies, early intervention, health-related special education, dental, prescription drugs, intensive personal care, comprehensive case management, durable medical equipment |
| New Jersey | AFDC, AFDC-related, SSI, Foster Care | Voluntary | Children who have chronic debilitating conditions, language difficulties, or who have a provider relationship that would be substantially disrupted | Mental health, substance abuse, intensive ancillary therapies, health-related special education, personal care |
| New York | AFDC, AFDC-related, Foster Care (not in NYC) | Mandatory in one borough; voluntary elsewhere | Children receiving CSHN services, certain children who have specific medical needs that cannot be met through an HMO | Intensive mental health, intensive substance abuse, early intervention, health-related special education, dental5, vision5, hospice, personal care, comprehensive case management, durable medical equipment5 |
| North Carolina | AFDC | Voluntary | None | Mental health and substance abuse (both capitated), dental, vision, personal care |
| Ohio | AFDC, AFDC-related | Mandatory in two counties; voluntary elsewhere | None | Hospice |
| Oregon | AFDC, AFDC-related, SSI, Demonstration Eligibles | Mandatory in 28 out of 36 counties | Children who have an existing provider relationship that would be disrupted or who have specific medical needs that cannot be met through the HMO9 | Mental health in all but 3 counties, intensive substance abuse, health-related special education, dental5 (some capitated), personal care |
| Pennsylvania | AFDC, AFDC-related, SSI, Foster Care | Mandatory in one county; voluntary elsewhere | None | Certain intensive mental health, early intervention, personal care, specialized services for foster care children5, certain services for mentally retarded and developmentally disabled children |
| Rhode Island | AFDC, AFDC-related, Demonstration Eligibles | Mandatory | None | Intensive mental health, mental health services for SED-eligible children, intensive substance abuse, certain early intervention, certain health-related special education, dental, personal care, comprehensive case management, EPSDT expanded benefits |
| Tennessee | AFDC, AFDC-related, SSI, Foster Care, Demonstration Eligibles | Mandatory | None | Intensive mental health, personal care |
| Texas | AFDC, AFDC-related | Mandatory | None | Intensive mental health, early intervention, health-related special education, dental, vision, prescription drugs, comprehensive case management, durable medical equipment, EPSDT expanded benefits |
| Utah | AFDC, AFDC-related, SSI, Foster Care | Voluntary | None | Mental health (capitated), substance abuse, early intervention, health related special education, dental5, prescription drugs5, certain services for mentally retarded and developmentally disabled children |
| Virginia | AFDC, AFDC-related | Voluntary | None | Intensive mental health, health-related special education |
| Washington | AFDC, AFDC-related | Mandatory | Children whose distance from delivery sites makes enrollment impractical, who have language difficulties, who have an existing provider relationship that would be substantially disrupted, or who have a significant medical need that cannot be met through the HMO10 | Most mental health (capitated in some areas), substance abuse, early intervention, health-related special education, dental, eyeglasses, personal care, comprehensive case management |
| Wisconsin | AFDC, AFDC-related | Mandatory | None | Dental5 |
| AFDC-related = children who qualify for Medicaid because of their poverty-level status as regular or optional Medicaid eligibles as well as children whose families meet the AFDC income criteria but do not receive AFDC benefits. CSHN = state Title V program for children with special health care needs SED = state comprehensive community mental health services program for children and adolescents with serious emotional disturbances |
||||
|
||||
| SOURCE: Information was obtained by Fox Health Policy Consultants through telephone interviews with state Medicaid agency staff during the spring and summer of 1994 and was verified by the states as being accurate as of March 31, 1995. | ||||
| TABLE 2. Medicaid Services to Children Excluded from Contracts DRAFT-Not for Publication |
||
|---|---|---|
| Services Carved Out of Contracts | Number of States (n=29) | Percent of States |
| Dental services | 20 | 69% |
| Health-related special education services | 16 | 55 |
| Personal care | 15 | 52 |
| Some mental health services | 13 | 45 |
| Early intervention services | 10 | 34 |
| Case management | 9 | 31 |
| All mental health services | 9 | 31 |
| Vision services | 9 | 31 |
| Prescription drugs | 7 | 24 |
| Hospice | 7 | 28 |
| Durable medical equipment | 5 | 17 |
| EPSDT expanded benefits | 4 | 14 |
| Some ancillary therapies | 3 | 10 |
| CSHN specialty services | 2 | 7 |
| Specialized services for foster care children | 2 | 7 |
| SOURCE: Information was obtained by Fox Health Policy Consultants through telephone interviews with state Medicaid agency staff in March 1995, and was verified by the states as being accurate as of March 31, 1995. | ||
| TABLE 3. EPSDT Language in State Medicaid Managed Care Contracts Regarding Diagnosis and Treatment | ||||||
|---|---|---|---|---|---|---|
| State | Specifies and Explains the EPSDT Benefit1 | Includes Core Elements of OBRA '89 EPSDT Language | Incorporates Federal EPSDT Law or Rules by Reference | Incorporates State EPSDT Law or Rules by Reference | ||
| Requires services to correct or ameliorate identified defects, illnesses, or conditions | Requires services for both physical and mental health problems | Requires all federally allowable diagnostic, treatment, and other health care services | ||||
| Arizona | X | X | X | X | X | |
| California | X | X | ||||
| Colorado | X | X | ||||
| Delaware | X | X | X | X | X | |
| District of Columbia | ||||||
| Florida | X | X | X | X | ||
| Hawaii | X | X | X | X | X | |
| Illinois | X | X | X | X | ||
| Indiana | X | X | ||||
| Iowa | X | X | ||||
| Maryland | X | X | X | |||
| Massachusetts | X | X | X | X | X | |
| Michigan | X | X | ||||
| Minnesota | X | X | ||||
| Missouri2 | X | n/a | X | |||
| New Hampshire | X | X | X | X | X | |
| New Jersey | X | X | X | X | ||
| New York | X | X | X | X | ||
| North Carolina | X | X | X | |||
| Ohio | X | X | ||||
| Oregon3 | n/a | n/a | n/a | n/a | n/a | n/a |
| Pennsylvania | X | X | X | X | X | |
| Rhode Island2 | X | X | n/a | |||
| Tennessee | X | X | ||||
| Texas2 | X | n/a | X | |||
| Utah | X | X | X | X | ||
| Virginia | X | X | X | X | ||
| Washington | X | X | X | X | ||
| Wisconsin | X | X | X | X | X | X |
| TOTAL | 27 of 28 | 15 of 28 | 13 of 28 | 12 of 25 | 18 of 28 | 7 of 28 |
|
||||||
| SOURCE: Information is based on an analysis of contracts in effect in December 1995, performed by Fox Health Policy Consultants. Provider manuals, administrative rules, and other documents referenced in the state contracts were included in the analysis. | ||||||
| TABLE 4. Medical Necessity Language in State Medicaid Managed Care Contracts | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| State | Medical Necessity Defined in Contract | If included in contract, Criteria Used to Define Medical Necessity | |||||||
| General | Child-Specific | Includes Services for Preventive Purposes as well as Diagnostic and Treatment Purposes | Includes Treatments for a "Condition," "Disability," or "Handicap" in Addition to an "Illness or Injury" | Qualifies Terms Such as "Disability," "Handicap" or "pain" with "severe" of "significant" | Requires Conformance with Standards of Good Medical Practice or Prevailing Community Standards | Requires the most appropriate level of services that can be provided safely | Requires the Least Costly Alternative Treatment of Equal or Reasonably Equal Effectiveness | Requires Evidence of Effectiveness or Proven Medical Value | |
| Arizona | X | X | X | ||||||
| California | |||||||||
| Colorado | X | X | X | X | X | ||||
| Delaware | |||||||||
| District of Columbia | |||||||||
| Florida | X | X | X | X | X | X | X | ||
| Hawaii | X | X | |||||||
| Illinois | X | X | X | ||||||
| Indiana | |||||||||
| Iowa | X | X | X | X | |||||
| Maryland | X | X | |||||||
| Massachusetts | X | X | X | X | |||||
| Michigan | |||||||||
| Minnesota | X | X | X | X | X | ||||
| Missouri | |||||||||
| New Hampshire | X | X | X | ||||||
| New Jersey | |||||||||
| New York | X | X | X | X | |||||
| North Carolina | |||||||||
| Ohio | X | X | X | X | |||||
| Oregon | X | X | X | X | X | ||||
| Pennsylvania | |||||||||
| Rhode Island | X | X | |||||||
| Tennessee | X | X | X | ||||||
| Texas | |||||||||
| Utah | |||||||||
| Virginia | |||||||||
| Washington | X | X | X | X | X | ||||
| Wisconsin | X | X | X | X | X | X | X | ||
| TOTAL | 16 of 29 | 1 of 29 | 11 of 17 with definitions | 12 of 17 with definitions | 4 of 17 with definitions | 12 of 17 with definitions | 5 of 17 with definitions | 5 of 17 with definitions | 2 of 17 with definitions |
| SOURCE: Information is based on an analysis of contracts in effect in December 1995, preformed by Fox Health Policy Consultants. Provider manuals, administrative rules, and other documents referenced in the state contracts were included in the analysis. | |||||||||
Families' Out-of-Pocket Expenses When Caring for Children With Special Needs: A Preliminary Report Comparing Children in Medicaid and a Commercial Product Line
Elizabeth A. Shenkman, Ph.D.
INTRODUCTION
Despite the growing interest in enrolling children with special health care needs in managed care plans, remarkably little is known about the effects of managed care on this vulnerable group.1, 2 This lack of information is due, in part, to the fact that many private managed care organizations (MCOs) are unwilling to release person level use data so that analyses can be conducted on those enrollees who have special health care needs. In addition, states with Medicaid managed care plans have exempted some or all children with special needs from enrollment in these plans. Therefore very limited data from the public sector are available.3, 4
Many concerns have been raised about how children with special health care needs and their families will fare within a managed care environment. It is not known whether families will be able to obtain the services their children need in an environment where health care use and expenditures are closely monitored. Within the current fee-for-service system, families often face strong financial burdens both in terms of out-of-pocket expenses and caregiving time. These financial burdens are disproportionately borne by lower-income families.5 Some believe that placing children with special health care needs in managed care arrangements will result in even higher out-of-pocket expenses for families as they enter a system with stringent health care utilization management and potential financial disincentives to physicians to provide care or make referrals.6
PURPOSE
The purpose of this paper is to present preliminary information about families' out-of-pocket expenses when caring for children with special health care needs. Families' expenses for two groups of children are presented. The first group are commercially-insured children with special needs who are receiving care through private health maintenance organizations. The second group are children with special needs who are receiving care through Medicaid fee-for-service or primary case management programs.
The information in this paper is preliminary because we are continuing to collect data both for the Commercially insured and the Medicaid populations. In addition, we are presenting the findings from the survey data only. We have actual health care use data from the HMOs and Medicaid from their claims and encounter data bases for each child in the study. However, these data have not been completely analyzed and therefore are not included in this report.
METHODS
The Third Party Payers Participating in the Study
The Third Party Payers--Commercial: The commercially insured children participating in this study to date are insured through a special program designed to provide subsidized insurance premiums to previously uninsured children. Families with incomes below 130% of the federal poverty level (FPL) pay $5.00 per child per month; those between 131% and 185% of the FPL pay $15.00 per child per month; and those at 186% of the FPL or above paid the full premium of $50.00 per child per month. Approximately 30,000 children are currently enrolled. The benefit package is the same as that offered through Medicaid (Table 1). A key program feature is the provision of care through the private sector. The program is not intended to extend Medicaid coverage or to provide health care as a variation of the current Medicaid system for children in Florida. A private not-for-profit corporation negotiates contracts with HMOs to assume the financial risk and to provide health care services for the children. Four HMOs currently have contracts and deliver care through private physicians' offices and clinics in the children's communities. Both pediatricians and family practitioners serve as the children's primary care providers. Extensive specialty networks including tertiary care facilities are available through the HMOs. Program enrollment is voluntary.
The Third Party Payers--Florida Medicaid: The Medicaid Program in Florida offers coverage to the following children: (1) children less than one year of age and pregnant women at 134% to 185% of the FPL; (2) children one to six years of age at 101% to 133% of the FPL; and (3) children six to thirteen years at 100% of the FPL or below. Forty-nine percent of children receiving Medicaid are enrolled in the Medipass Program which is a Primary Care Case Management Program. Physicians provide care coordination for these children on a capitated basis. Any services provided beyond care coordination are reimbursed at a Medicaid fee-for-service rate. Catastrophic coverage is available through Florida Medicaid.
Sample Selection
Children were initially identified for possible inclusion in the study through the following steps:
-
Each HMO and Florida Medicaid provided child-specific health care use data including International Classification of Diseases, Clinical Modification, 9th Revision (ICD-9-CM) codes for each health care encounter.
-
In collaboration with two physicians from the University of Florida, Department of Pediatrics, we developed a list of ICD-9-CM codes that might indicate the child had a special health care need. The list was intentionally broad and included conditions of high and low prevalence (Appendix A).
- The health care use data bases were searched to identify those children who had at least one health care visit during which an eligible ICD-9-CM code was identified. We then identified those children with an eligible ICD-9-CM code who were enrolled within three months preceding the sample selection. We wanted to include those who were recently enrolled so that the survey data and health care use data were as contemporaneous as possible.
Table 2 shows the number of children identified across each HMO and Florida Medicaid for possible inclusion in the study. As expected, significantly more children were identified as possibly having a special health care need through the Medicaid data base than through the private HMO data bases (33% versus 14%).
-
Once the commercially insured children were identified from the data bases, we contacted a census of all those potentially eligible and administered a series of screening questions to determine final eligibility into the study. The screening questions were used to ensure that we only included those children who had moderate to severe health care needs. The following screening questions were used:
- Because of a physical or mental condition, does your child require more supervision than other children of his/her age?
- Does your child require extra or specialized medical care, therapies, supplies or medical equipment because of a special health care need?
- Has your child had his/her special health care need for 6 months or longer?
Those children whose families answer yes to question a or b and c will be included in the study. That is, a family who has a child (1) requiring increased supervision or has a child who requires specialized medical care, therapies, supplies, or medical equipment because of a special health need; and (2) the child has had the condition for 6 months or longer were included in the study.
Questions about activities of daily living (ADLS) were not used as initial screening questions because, based on our past work, a significant number of children may have special health care needs with no ADL deficits. For example, a child with mental retardation could have many needs for educational interventions and supervision resulting in additional financial and caregiving burdens on the families; yet have no ADL deficits.
Table 3 shows the number of parents with commercially insured children meeting the ICD-9-CM criteria who were contacted, the number who met the screening question criteria, and the number who participated in the survey.
-
Because so many children in the Medicaid data base had an ICD-9-CM code that might qualify them for inclusion in the study, we obtained a simple random sample of the Medicaid enrollees to contact. The same screening questions described in Step 4 also are being used to determine final study eligibility for the Medicaid population. We randomly selected 5,500 children, administered screening questions to 112 parents to date, and obtained 76 completed interviews (Table 3). We expected to find not only a greater number of children with special health care needs in the Medicaid data base, but also more children with significant health care needs when compared to the HMO population. As expected, more children in the Medicaid data base met the screening questions for inclusion into the study when compared to the pediatric HMO population (23% versus 10%).
-
At the present time, we have completed surveys for 387 children in the commercial product line and 76 children participating in the Medicaid Program. The data for these children are presented in this report. As previously mentioned, we are continuing to conduct surveys among the Medicaid enrollees and also among children who are receiving health insurance through other commercial product lines offered by the HMOs with whom we are working.
Measures of Caregivers' Out-of-Pocket Expenses
We developed the Caregivers' Out-of-Pocket Expense (COPE) Survey to assess the following dimensions for expenses:
- Direct Expenses--medical care expenditures for diagnosis, treatment, continuing care, rehabilitation and terminal care. Expenses for the following services are included in this category: physical therapy, occupational therapy, speech therapy, skilled nursing (registered nurse/ licensed practical nurse), personal attendant, respiratory therapy, specialized day care, counseling, doctor's visits in clinic or office, hospital care, medications and home medical equipment.
- Other Direct Expenses--expenditures for the following items or services: respite care, special diets or formulas, medical supplies, special or additional clothing, diapers not normally used at the child's age, transportation costs, educational services related to the child's special health care need, assistive technologies, transportation related to the child's special health care needs, emergency transportation, purchase of a car or van related to the child's special health care needs, and home modifications.
- Indirect Expenses--time spent in providing care for the child and lost employment opportunities.
Survey items initially were developed based on a literature review of expenses families incur when caring for children with disabilities.7, 8, 9 A panel of reviewers reviewed the first two drafts of the surveys for content. Reviewers included: a generalist pediatrician from an academic health center who specializes in caring for children with special health care needs, a family economist, a health care economist, two state Title V Children with Special Health Care Needs (CSHCN) Program Directors, two families who have children with special health care needs, and two policy analysts from the former Congressional Office of Technology Assessment. Following the content reviews, the survey was revised and field tested with 60 families. Based on the field testing, a final version of the survey was developed and used in this research.
This phase of our research focuses on families reported direct and other direct expenses. Families were determined to have incurred direct or other direct out-of-pocket expenses if the respondent indicated that the child received the particular service or item and it was paid for either entirely or in part by the parent or guardian, another relative residing in the household, or the child's Supplemental Security Income (SSI) check. The respondent was asked what the out-of-pocket expense was for the preceding month and for the preceding year for each service or item the child received. He or she also was asked if the expenditure for the month was typical or not and if the dollar amount provided was based on actual records or an estimate.
If the family was required to pay a co-payment for a service and the payment was made according to the criteria described in the preceding paragraph; the dollar amount was attributed to the particular category for which the co-payment was required. For example, in the commercially insured population, families are required to pay a $3.00 co-payment for an acute care visit to their primary care provider. The $3.00 co-pay would be described as an out-of-pocket expense for a doctor's visit. Thus out-of-pocket expenses could represent a co-payment for a particular service or item; an expenditure for a service or item not covered in the benefit package; or a service or item that was covered by the benefit package but the maximum amount allowed for payment was exceeded and the family had to begin paying.
Measures of Child's Functional Status
We used the Functional Status Rating Scale [FSII(R)], short form, to assess the children's level of functioning. The FSII(R) assess a child's functioning in the areas of social behavior, sleeping, eating, and activities.10 The instrument also was specifically designed to detect changes in a chronically ill child's functioning across time. The short version contains 14 items and has an alpha coefficient of 0.80. An alpha coefficient measures the degree to which the items on an instrument measure the same concept.11 The alpha coefficient of .80 means that the items on the FSII(R) are consistently measuring the same concept.
The instrument is scored from 0 to 100 with 100 representing the highest functioning. The developers established concurrent validity by correlating the FSII(R) measures with established measures of morbidity such as days in hospital and school absences. The correlations were moderate ranging from .24 to .47. A copy of the items are contained in Appendix B.
Demographic Measures
We gathered information about the family's race and ethnicity, respondent's age, total family income, and participation in the SSI Program for children. In addition, we asked about the child's age and diagnosis.
Data Analysis
Descriptive data only are presented for this phase of the study. Specifically we will describe the following:
- The children's demographic characteristics.
- The diagnoses (grouped together into diagnostic categories) and the FSII(R) scores by diagnostic category of the children in the HMOs and Medicaid.
- The amount families spent on direct and other direct expenses expressed both in dollar amounts and as a percentage of family income for children in the HMOs and Medicaid.
- The amount families spent on direct and other direct expenses expressed both in dollar amounts and as a percentage of family income by diagnostic category for children in the HMOs and Medicaid.
- The dollar amount spent for specific services and items (i.e. physical therapy, supplies, medications, and others) for children in the HMOs and Medicaid.
RESULTS
The Study Sample
Children enrolled in Medicaid varied from children in the commercial program on several characteristics (Table 4). A higher percentage of children in Medicaid were African-American (15% versus 8%) and from lower income homes. Thirty percent of the Medicaid enrollees reported an average family income of less than $9,999 per year compared to only 13% of the commercially insured. However, overall both groups had low incomes with 15% or less of the respondents reporting a family income over $35,000 per year. In addition, children in the Medicaid program had significantly lower scores on the FSII(R) than the commercially insured children (p<.01). When reporting out-of-pocket expenses, it is important to note that a higher percentage of families in the commercially insured group when compared to the Medicare group used actual records rather than recall to report their expenses.
More than 70 different diagnoses are represented in this study. Given the diverse array of diagnoses, children were classified into categories (Table 5). We used the Social Security Administration's diagnostic categories that are contained in their medical listings of impairments. Children in Medicaid had a broader range of diagnoses and more severe diagnoses than children in the commercially insured group. The most striking example can be found in the respiratory category. Ninety-two percent of the commercially insured children in the respiratory category had a diagnosis of asthma compared to only 2% of the children receiving Medicaid. Children who received Medicaid and were classified in the respiratory category had diagnoses including: ventilator dependency, cystic fibrosis, and chronic respiratory failure.
The greatest similarity in diagnoses was found in the category of mental and emotional disorders. Attention deficit disorder (ADD) or attention deficit hyperactivity disorder (ADHD) were the most frequently occurring conditions with 80% of the commercially insured children and 74% of the children in Medicaid in this category having one of these two diagnoses. Depression and mental retardation were also seen in this category for both groups.
In addition to classifying into diagnostic groups, we obtained FSII(R) scores on each child. Prior research has documented that there is wide variability in functioning both between and within diagnoses; therefore classifying children according to their functioning as opposed to a diagnostic label is a valuable approach. The children's FSII(R) score by diagnostic category is contained in Table 5. With the exception of neoplastic diseases, children in Medicaid had lower scores for each diagnostic category when compared to commercially insured children. For both groups, children with mental and emotional disorders had the lowest scores in functioning. However, these low scores may reflect the fact that the instrument used contains many items that could be indicative of a mental or behavioral problem such as items referring to the child's mood, cheerfulness, and crying behavior. Few of the items specifically refer to limitations in physical activity.
The Amount Families Spend on Direct and Other Direct Out-of-Pocket Expenses
Given the higher functional status scores of children in the commercially insured program, it is not surprising that families incurred less out-of-pocket expenses in both absolute dollar amounts and in terms of the amount spent as a percent of family income when compared to Medicaid enrollees. Tables 6 and 7 illustrate the amount families spent out-of-pocket on direct and other direct expenses. Cross-tabulations of families' out-of-pocket expenses by income level reveal that families with incomes below $14,999 per year spend a disproportionate amount of their income on caring for their children when compared to families with incomes above that amount. While the average amount of out-of-pocket expenses as a percent of family income was only about 2% for the commercially insured, these expenses represented 12% of family income for those reporting incomes below $14,999. A similar regressive pattern was noted for Medicaid recipients with families at the lowest income levels paying as much as 32% of their income to care for their children with special needs.
Families with children in the commercial insurance program spent about equal amounts of money per month on direct and other direct expenses. However, families who had children in the Medicaid program spent greater amounts of money on other direct expenses. These other direct expenses included items and services that are not traditionally covered by Medicaid or other third party payers. Table 8 describes specific expenditures by third party payer category. Families incurred expenses for medications, special diets, assistive technologies, and respite care that are not contained in the Medicaid benefit package. Those families who received supplemental security income (SSI) reported spending this money on these and other items that were described in the "other direct expense" category. Ninety percent of families reported using the child's SSI check for one or more of the items or services in this category.
An important but often neglected area of out-of-pocket expenses to the family is that of indirect expenses or the time families spent caring for the child and lost employment opportunities. For this report, we calculated the average amount of time in hours that families reported spending in caregiving activities for their children with special needs. The number of hours spent in caregiving was obtained through the following methods:
- Obtaining a listing of each person residing in the household, the person's age and relationship to the child with special needs;
- For each person 18 years of age or older, asking if that person spent any time providing care to the special needs child, and if so the number of hours spent providing that care; and
- Summing the number of caregiving hours across all members of the household who indicated that provided care.
We obtained the following results:
- Eighty-five percent of families whose children were receiving Medicaid reported spending time in specific caregiving activities. They reported spending an average of 15.33 hours per day (± 9.19; range 0 to 24 hours) in care provision.
- Forty-eight percent of families whose children were commercially insured reported spending time in specific caregiving activities. On average, these families spent 8.76 hours per day (± 3.2; range 0 to 11 hours) providing care.
We have several more items about families caregiving activities and the impact that this has had on their employment. These data will be analyzed in future work.
SUMMARY
The data contained in this report are preliminary. We are gathering more survey data from Medicaid and from other commercial product lines. However, some patterns are noted in these data that have important implications when designing health care programs and financing mechanisms for children with special health care needs.
Families incur significant out-of-pocket expenses when caring for their children. Lower income families bear the heaviest financial burden with expenses as high as 32% of their total income. While families with children in the HMOs have less expenses than those families with children in Medicaid, they still bear out-of-pocket expenses that take the heaviest toll on the lowest income groups. Benefit packages must be designed that consider the broad array of services required by children with special health care needs including respite care and educational technologies.
Moreover, the impact on the family in terms of their time must be considered. Perhaps health care expenditures can be minimized but at great personal cost to families. Particularly for families receiving Medicaid, more than half of their day can be spent providing care to their children with special needs. The economic impact of this activity must be considered.
Often it is difficult to compare out-of-pocket expenses between different third party payers due to differences in benefit packages. In this phase of our study, all of the children received the same benefits. Although this is a preliminary report, differences in out-of-pocket spending can largely be attributed to differences in the children's health status. Children in Medicaid had much lower scores on functioning when compared to children in the commercially insured group.
Further analytic work will be conducted using regression techniques to more fully describe the factors influencing out-of-pocket expenses. In addition, we will include the children's health care use data from the claims data bases as well as measures of the time families spend in caregiving.
NOTES
- Ireys, HT. "Children with Special Health Care Needs: Evaluating Their Needs and Relevant Service Structures." Paper commission by the Institute of Medicine. Baltimore, MD: Johns Hopkins University, November 1994.
- Batavia, AI. "Health Care Reform and People with Disabilities." Health Affairs. 1993; 12:40-55.
- Ireys, HT. "Children with Special Health Care Needs: Evaluating Their Needs and Relevant Service Structures." Paper commission by the Institute of Medicine. Baltimore, MD: Johns Hopkins University, November 1994.
- Butler, P, RL Mollica, and T Riley. Children's Health Plans. Portland, ME: National Academy for State Health Policy, 1993.
- Rasell, E, J Bernstein, and K Tang. "The Impact of Health Care Financing on Family Budgets." Challenge. November-December 1993:12-21.
- Newacheck, PW, DC Hughes, JJ Stoddard, and N Halfon. "Children with Chronic Illness and Medicaid Managed Care." Pediatrics. 1994; 93:497-500.
- Newacheck, PW, and N Halfon. "The Financial Burden of Medical Care Expenses for Children." Medical Care. 1986; 24:1110-1117.
- Jacobs, P, and S McDermott. "Family Caregiver Costs of Chronically Ill and Handicapped Children: Method and Literature Review." Public Health Reports. 1989; 104:158-163.
- Leonard, B, JD Brust, and JJ Sapienza. "Financial and Time Costs to Parents of Severely Disabled Children." Public Health Reports. 1992; 107:302-312.
- Stein, REK, and DJ Jessop. Manual for the Functional Status II(R) Measure. New York: Albert Einstein College of Medicine of Yeshiva University, 1991.
- Aday, L. Designing and Conducting Health Surveys. San Francisco, CA: Jossey-Bass, 1991.
| TABLE 1. Summary of Medicaid Benefits in Florida* | |
|---|---|
| Category | Reimbursement |
Durable Medical Equipment
|
The lesser of the amount billed or the established maximum Medicaid fee. |
Home Health Care Services
|
The lesser of the amount billed or the maximum allowable |
Hospice Care
|
Medicaid allowable rate |
| Hospital Services--Inpatient | 45 day limit |
| Hospital Services--Outpatient | $2.00 co-payment for Medicaid |
| Laboratory | Medicaid allowable rate |
Eye Care
|
$3.00 co-payment Covered every two years with a $10.00 co-pay. Only Medicaid frames. |
| Physician Services | $2.00 co-payment for Medicaid; $3.00 co-payment for commercial product line. |
| Podiatry Services | $2.00 co-payment for Medicaid. Certain limitations. |
| Prescription Drugs | 31 day supply with a $2.00 co-pay; $3.00 co-pay for commercially insured |
| Occupational Therapy Services | One treatment per day; reassessments every 6 months; minimum treatment period; Medicaid allowable rate |
| Physical Therapy Services | One treatment per day; reassessments every 6 months; minimum treatment period; Medicaid allowable rate |
| Respiratory Therapy Services | One therapy per day; minimum treatment period of 30 minutes; reassessment every 6 months; Medicaid allowable rate |
| Speech Therapy | One therapy per day; minimum treatment period of 30 minutes; reassessment every 6 months; Medicaid allowable rate |
| Mental Health | 20 visits per year with $5.00 co-pay |
| Extended Care | Varies by type of extended care required |
| Transportation | Emergency transport covered in full |
| *Does not include all benefits offered such as special waivers, birth centers, nursing homes. | |
| TABLE 2. Total Number of Children Identified From the Health Care Use Data Bases Using Selected ICD-9-CM Codes | ||
|---|---|---|
| Category | Florida Medicaid |
Commercially Insured |
| Total number of children screened for ICD-9-CM codes that may reflect a special health care need | 307,241 | 27,487 |
| Total number of children enrolled within the last three months of selecting the sample | 253,562 | 13,591 |
| Total number of children with at least one ICD-9-CM code indicating a possible special health care need enrolled in the last three months of selecting the sample | 84,315 | 1,916 |
| Percentage of enrollees with at least one ICD-9-CM code indicating a possible special health care need and enrolled within the last three months of selecting the sample | 33% | 14% |
| TABLE 3. Families Screened for Study Participation and Surveys Completed | ||
|---|---|---|
| Category | Florida Medicaid |
Commercially Insured |
| Completed screening questions | 112 | 547 |
| Did not qualify | 12 (10%) | 128 (23%) |
| Qualified but refused to participate | 24 | 32 |
| Qualified and completed a survey | 76 | 387 |
| TABLE 4. Demographic Characteristics of the Study Sample | ||
|---|---|---|
| Category | Children Receiving Medicaid |
Commercially Insured Children |
Respondent Gender
|
97% 3% |
95% 5% |
| Respondent Age | 37.43 ± 10.90 | 39.55 ± 9.99 |
| Child's Age | 9.23 ± 5.23 | 10.48 ± 6.21 |
| FSII(R) Score | 78.53 ± 18.69 (range 17 to 100) |
87.20 ± 15.33 (range 21 to 100) |
Child's Racial Background
|
80% 15% 5% |
85% 8% 7% |
Child's Ethnicity
|
11% 89% |
12% 88% |
Average Family Income
|
30% 17% 14% 12% 10% 7% 7% 2% |
13% 22% 19% 15% 12% 8% 5% 7% |
Cash Assistance-SSI for Child
|
35% 35% 65% |
0% 47% 53% |
| TABLE 5. Children's Primary Diagnostic Categories and FSII(R) Scores | ||||||||
|---|---|---|---|---|---|---|---|---|
| Category | Children Receiving Medicaid (N=76) | Commercially Insured Children (N=387) | ||||||
| Percent Children |
FSII(R) Mean Score & Standard Deviation | Min. | Max. | Percent Children |
FSII(R) Mean Score & Standard Deviation | Min. | Max. | |
| Mental and Emotional Disorders** | 16% | 67 ± 20 | 18 | 100 | 39% | 75 ± 22 | 18 | 100 |
| Respiratory System | 13% | 69 ± 206 | 50 | 100 | 40% | 90 ± 15 | 46 | 100 |
| Neurological | 25% | 76 ± 19 | 28 | 100 | 4% | 82 ± 18 | 24 | 100 |
| Musculskeletal System | 17% | 86 ± 13 | 31 | 100 | 2% | 92 ± 10 | 53 | 100 |
| Special Sense Organs | 8% | 80 ± 18 | 42 | 100 | 4% | 86 ± 15 | 44 | 100 |
| Endocrine System | <1% | 71 ± 0 | 71 | NA | 3% | 90 ± 12 | 20 | 100 |
| Cardiovascular | 4% | 88 ± 12 | 71 | 100 | <1% | 88 ± 0 | 88 | NA |
| Digestive System | 3% | 88 ± 20 | 43 | 100 | <1% | 90 ± 0 | 90 | NA |
| Multiple Body Systems* | 6% | 88 ± 09 | 67 | 100 | 0% | NA | NA | NA |
| Genito-Urinary System | 1% | 76 ± 10 | 64 | 100 | 1% | 86 ± 18 | 42 | 100 |
| Hemic and Lympahtic System | <1% | 67 ± 0 | 67 | NA | 0% | NA | NA | NA |
| Neoplastic Diseases--Malignant | <1% | 100 ± 0 | 100 | NA | <1% | 86 ± 0 | 86 | NA |
| Immune System | 2% | 87 ± 13 | 71 | 100 | <1% | 87 ± 0 | 87 | NA |
| Growth Impairment | 2% | 96 ± 07 | 85 | 100 | 0% | NA | NA | NA |
| * Includes Down Syndrome, multiple body dysfunction, and catastrophic congenital anomalies ** Includes mental retardation |
||||||||
| TABLE 6. Direct and Other Direct Expenses for the Month and Year in Dollars | ||||||||
|---|---|---|---|---|---|---|---|---|
| Category | Children Receiving Medicaid | Commercially Insured Children | ||||||
| % Reporting Expense | Mean | Min. | Max. | % Reporting Expense | Mean | Min. | Max. | |
| Direct Expenses Per Month Direct Expenses Per Year |
37% 38% |
131.89 ± 392.25 1072 ± 14629.1 |
0 0 |
3050 5780 |
87% 86% |
28.59 ± 139.2 384.11 ± 1582 |
0 3.00 |
2562 6200 |
| Other Direct Expenses Per Month Other Direct Expenses Per Year |
89% 89% |
162.57 ± 305.93 1444.1 ± 1779.2 |
0 0 |
3077 9680 |
63% 63% |
30.79 ± 69.8 689.4 ± 2502.6 |
0 1.00 |
660 2890 |
| TABLE 7. Direct and Other Direct Expenses for the Month and Year Expressed as a Percent of Family Income | ||||||||
|---|---|---|---|---|---|---|---|---|
| Category | Children Receiving Medicaid | Commercially Insured Children | ||||||
| % Reporting Expense | Mean | Min. | Max. | % Reporting Expense | Mean | Min | Max. | |
| Direct Expenses Per Month Direct Expenses Per Year |
37% 36% |
4.87 ± 32.4 4.33 ± 12.2 |
0 0 |
698.0 128.95 |
87% 87% |
2.32 ± 10.38 2.8 ± 12.78 |
0 .10 |
146.4 1698.7 |
| Other Direct Expenses Per Month Other Direct Expenses Per Year |
89% 88% |
12.79 ± 21.9 11.25 ± 25.6 |
0 0 |
129.8 487.0 |
63% 63% |
2.11 ± 6.2 2.25 ± 10.98 |
0 .04 |
72.0 1587.6 |
| TABLE 8. Specific Expenses in Dollars for Children in Medicaid and Commercially Insured | ||||
|---|---|---|---|---|
| Category | Children Receiving Medicaid | Commercially Insured Children | ||
| Percent Incurring Expense | Cost/Month in Dollars Mean and Standard Deviation | Percent Incurring Expense | Cost/Month in Dollars Mean and Standard Deviation | |
| Physical Therapy | 1% | 70.0 ± 98.9 | <1% | 175 ± 168.5 |
| Occupational Therapy | 1% | 71.0 ± 97.6 | 0% | 0 |
| Speech Therapy | 1% | 50.1 ± 86.5 | <1% | 15.0 ± 21.2 |
| Skilled Nursing | 0% | 0 | <1% | 600 ± 848.6 |
| Personal Attendant | <1% | 400.0 ± 0 | <1% | 85 ± 0 |
| Respiratory Therapy and Supplies | 1% | 45.0 ± 35.3 | 9% | 7.5 ± 26.4 |
| Day Care | 2% | 147.25 ± 97.2 | <1% | 50.0 ± 70.7 |
| Counseling | 3% | 25.2 ± 21.7 | 22% | 7.8 ± 13.7 |
| Doctors Visits | 11% | 82.1 ± 123.78 | 88% | 8.5 ± 27.6 |
| Hospital | 4% | 500.0 ± 1,110.0 | 9% | 16.5 ± 80 |
| Respite Care | 11% | 85.7 ± 226.8 | 2% | 59.3 ± 119.2 |
| Medications | 24% | 31.0 ± 52.7 | 90% | 10.3 ± 31.5 |
| Special Diet | 14% | 110.5 ± 98.7 | 6% | 94.0 ± 132.6 |
| Medical Supplies | 17% | 24.6 ± 32.7 | 11% | 6.5 ± 10.7 |
| Special Clothing | 18% | 62.8 ± 54.1 | 5% | 30.1 ± 31.5 |
| Home Medical Equipment | 7% | 31.4 ± 60.9 | 7% | 16.9 ± 54.9 |
| Diapers | 38% | 61.8 ± 66.3 | 3% | 31.33 ± 45.7 |
| Assistive Technologies | 3% | 339.1 ± 328.2 | 0% | 0 |
| Educational Services | 2% | 37.1 ± 38.9 | 2% | 21.6 ± 41.8 |
| Additional Phone Charges | 24% | 20.0 ± 25.1 | 10% | 13.4 ± 24.0 |
| Additional Utility Bills | 13% | 56.4 ± 58.7 | 11% | 45.8 ± 48.9 |
| Higher Health Insurance Premiums | 1% | 167.6 ± 143.0 | 2% | 21.5 ± 27.7 |
| Additional Health Insurance | 1% | 237.6 ± 217.2 | <1% | 16.6 ± 28.7 |
| Transportation to Doctor | 31% | 41.4 ± 63.9 | 58% | 7.5 ± 15.2 |
| Emergency Transportation | 0% | 0 | 0% | 0 |
| Home Modifications | 7% | 52.1 ± 103.6 | 5% | 23.6 ± 65.2 |
APPENDIX A. ICD-9-CM CODES USED TO IDENTIFY CHILDREN FROM THE CLAIMS/ENCOUNTER DATA
| Code | Condition |
|---|---|
| 042 | Human Immunodeficiency Virus (HIV)/AIDS
|
142
|
Malignant Neoplasm of Major Salivary Glands
|
155
|
Malignant Neoplasm of Liver and Intrahepatic Bile Ducts
|
158
|
Malignant Neoplasm of Retroperitoneum and Peritoneum
|
170
|
Malignant Neoplasm of Bone and Articular Cartilage
|
171
|
Malignant Neoplasm of Connective and Other Soft Tissue
|
189
|
Maligant Neoplasm of Kidney and other Unspecified Urinary Organs
|
190
|
Malignant Neoplasm of Eye
|
192
|
Malignant Neoplasm of Other Unspecified Parts of Nervous
|
196
|
Secondary and Unspecified Malignant Neoplasm of Lymph Nodes
|
197
|
Secondary Maligant Neoplasm of Respiratory and Digestive System
|
200
|
Lymphosarcoma and Reticulosarcoma
|
201
|
Hodgkin's Disease
|
202
|
Other Malignant Neoplasms of Lymphoid and Histiocytic Tissue
|
204
|
Lymphoid Leukemia
|
205
|
Myeloid Leukemia
|
206
|
Monocytic Leukemia
|
207
|
Other Specified Leukemia
|
208
|
Leukemia of Unspecified Cell Type
|
210
|
Benign Neoplasm of Lip, Oral Cavity, and Pharynx
|
213
|
Benign Neoplasm of Bone and Articular Cartilage
|
| 215 | Other Benign Neoplasm of Connective and Other Soft Tissue |
| 216 | Benign Neoplasm of Skin |
225
|
Benign Neoplasm of Brain and Other Parts of Nervous System
|
228
|
Hemangioma and Lymphangioma, any site
|
229
|
Benign Neoplasm of Other and Unspecified Sites
|
237
|
Neoplasm of Uncertain Behavior of Endocrine Glands and Nervous System
|
250
|
Diabetes Mellitos, Type I [insulin dependent type] [IDDM] [ juvenile type], uncontrolled
|
277
|
Other and Unspecified Disorders of Metabolism
|
282
|
Hereditary Hemolytic Anemias
|
292
|
Drug Psychoses
|
293
|
Transient Organic Psychotic Conditions
|
294
|
Other Organic Psychotic Conditions (Chronic)
|
295
|
Schizophrenic Disorders [0=unspecified] [1=subchronic] [2=chronic] [3=subchronic with acute exacerbation]
|
296
|
Affective Psychoses
|
299
|
Psychoses with Origin Specific to Childhood
|
300
|
Neurotic Diseases
|
301
|
Personality Disorders
|
302
|
Sexual Deviations and Disorders
|
306
|
Physiological Malfunction Arising from Mental Factors
|
307
|
Special Symptoms or syndromes, Not Elsewhere Classified
|
308
|
Acute Reaction to Stress
|
309
|
Adjustment Reaction
|
310
|
Specific Nonpsychotic Mental Disorders Due to Organic Brain Damage
|
312
|
Disturbance of Conduct, Not Elsewhere Classified
|
313
|
Disturbance of Emotions Specific to Childhood and Adolescence
|
314
|
Hyperkinetc Syndrome of Childhood
|
315
|
Specific Delays in Development
|
| 316 | Psychic Factors Associated with Diseases Classified Elsewhere |
| 317 | Mild Mental Retardation |
318
|
Other Specified Mental Retardation
|
| 319 | Unspecified mental retardation |
330
|
Cerebral Degenerations Usually Manifest in Childhood
|
331
|
Other Cerebral Degenerations
|
343
|
Infantile Cerebral Palsy
|
344
|
Other Paralytic Syndromes
|
345
|
Epilepsy
|
369
|
Blindness and Low Vision
|
370
|
Keratitis
|
389
|
Hearing Loss
|
394
|
Diseases of Mitral Valve
|
395
|
Diseases of Aortic Valve
|
396
|
Diseases of Vitral and Aortic Valves
|
493
|
Asthma
|
| 494 | Bronchiectasis |
| 580 | Acute Glomerulonephritis |
581
|
Nephrotic Syndrome
|
584
|
Acute Renal Failure
|
| 585 | Chronic Renal Failure |
| 586 | Renal Failure, Unspecified |
| 587 | Renal Sclerosis, Unspecified |
588
|
Disorders Resulting From Impaired Renal Function
|
589
|
Small Kidney of Unknown Cause
|
714
|
Rheumatoid Arthritis and Other Inflammatory Polyarthropathies
|
741
|
Spina Bifida
|
744
|
Congenital Anomalies of Ear, Face, and Neck
|
745
|
Bulbus Cordis Anomalies and Anomalies of Cardiac Septal Closure
|
746
|
Other Congenital Anomalies of Heart
|
747
|
Other Congenital Anomalies of Circulatory System
|
748
|
Congenital Anomalies of Respiratory System
|
749
|
Cleft Palate and Cleft Lip
|
750
|
Other Congenital Anomalies of Upper Alimentary Tract
|
751
|
Other Congenital Anomalies of Stomach
|
754
|
Certain Congenital Musculoskeletal Deformities
|
758
|
Chromosomal Anomalies
|
765
|
Disorders Relating to Short Gestation and Unspecified Low Birth Weight
|
766
|
Disorders Relating to Long Gestation and High Birth Weight
|
770
|
Other Respiratory Conditions of Fetus and Newborn
|
771
|
Infectious Specific to the Perinatal Period
|
800
|
Fracture of Vault of Skull
|
801
|
Fracture of Base of Skull
|
802
|
Fracture of Face Bones
|
803
|
Other Unqualified Skull Fractures
|
806
|
Fracture of Vertebral Column with Spinal Cord Injury
|
| 807 | Fracture of Rib(s), Sternum, Larynx, and Trachea |
940
|
Burn Confined to Eye and Adnexa
|
941
|
Burns of Face, Head, and Neck (include all 5th digit code)
|
942
|
Burn of Trunk (include all 5th digit codes)
|
943
|
Burn of Trunk (include all 5th digit codes)
|
944
|
Burn of Trunk (include all 5th digit codes)
|
945
|
Burn of Trunk (include all 5th digit codes)
|
946
|
Burns of Multiple Specified Sites
|
947
|
Burn of Internal Organs
|
948
|
Burns Classified According to Extent of Body Surface Involved
|
949
|
Burn, Unspecified
|
| 995.5 | Child maltreatment syndrome |
APPENDIX B. ITEMS USED TO MEASURE FUNCTIONAL STATUS
Enter child number and first/last name of child with special health care needs listed in Section 1, #16.
Child Number:__________ First Name:__________ Last Name:__________
FUNCTIONAL STATUS II (R) 14-ITEM VERSION (English)
Here are some statements that mothers have made to describe their children. Thinking about __________ (INDEX CHILD), during the last two weeks did he/she...
| PART 1 | PART 2 | ||||||
|---|---|---|---|---|---|---|---|
| Never of Rarely | Some of the Time | Almost Always | Fully | Partly | Not At All | ||
| 17. Eat well | 0* | 1* | 2___ | 2 | 1 | 0___ | FS1 |
| 18. Sleep well | 0* | 1* | 2___ | 2 | 1 | 0___ | FS2 |
| 19. Seem contented and cheerful | 0* | 1* | 2___ | 2 | 1 | 0___ | FS3 |
| 20. Act moody | 0 | 1* | 2*___ | 2 | 1 | 0___ | FS4 |
| 21. Communicate what he/she wanted | 0* | 1* | 2___ | 2 | 1 | 0___ | FS5 |
| 22. Seem to feel sick and tired | 0 | 1* | 2*___ | 2 | 1 | 0___ | FS6 |
| 23. Occupy himself/herself | 0* | 1* | 2___ | 2 | 1 | 0___ | FS7 |
| 24. Seem lively and energetic | 0* | 1* | 2___ | 2 | 1 | 0___ | FS8 |
| 25. Seem unusually irritable or cross | 0 | 1* | 2*___ | 2 | 1 | 0___ | FS9 |
| 26. Sleep through the night | 0* | 1* | 2___ | 2 | 1 | 0___ | FS10 |
| 27. Respond to your attention | 0* | 1* | 2___ | 2 | 1 | 0___ | FS11 |
| 28. Seem unusually difficult | 0 | 1* | 2*___ | 2 | 1 | 0___ | FS12 |
| 29. Seem interested in what was going on around him/her | 0* | 1* | 2___ | 2 | 1 | 0___ | FS13 |
| 30. React to little things by crying | 0 | 1* | 2*___ | 2 | 1 | 0___ | FS14 |
Copyright 1981
Ruth E.K. Stein, M.D.
Catherine K. Riessman, Ph.D.
Dorothy Jones Jessop, Ph.D.
Managed Care Enhancement Project for Children with Special Health Care Needs: Family and Primary Care Clinician Needs Assessment Methods and Description of Survey Respondents
METHODS
A needs assessment was conducted to gain a better understanding of the needs and concerns of families of children with special health care needs enrolled in MassHealth Managed Care and primary care clinicians (PCCs) in the MassHealth Primary Care Clinician Plan. Surveys, which focussed on issues identified by the project Advisory Committee, were utilized to identify the needs and concerns of families and PCCs. Focus groups were then held in order to clarify and enhance survey data. Focus groups also provided a forum in which participants could generate ideas and recommendations for potential interventions to address their concerns. The results of the assessment were used to guide the development of appropriate interventions to enhance the care of children with special health care needs in MassHealth Managed Care.
Criteria Used for Defining MassHealth Population of Children with Special Health Care Needs
In order to identify the population of children with special health care needs enrolled in MassHealth Managed Care, the following criteria were used: Children with special health care needs were defined as those children aged 18 and under who were enrolled continuously (with no more than a 45 day break in eligibility in FY 94) in the MassHealth Managed Care program, and who were either (1) receiving SSI or (2) receiving AFDC and had at least one Early Intervention claim in FY 94.
Surveys
Surveys were sent to a random sample of families of children with special health care needs enrolled in MassHealth and PCCs in the MassHealth PCC Plan. All families were sent both English and Spanish versions of the survey. Three hundred twenty-one family surveys (including 67 Spanish versions of the survey) and 285 PCC surveys were returned. This represents a 32% and 31% response rate, respectively. Analysis of family survey data did not reveal any significant differences in the responses of English and Spanish respondents. Analysis of PCC survey data did not reveal any significant differences in satisfaction or needs between PCCs with high and low proportions of children with special health care needs in their practice, or between PCCs in different practice types.
Focus Groups
Four family and two PCC focus groups were conducted. The family focus groups were held in Lawrence, Boston, Hyannis and Holyoke. The Holyoke focus group was conducted in Spanish. The PCC focus groups, which were comprised of PCCs from a variety of practice types and cities and towns throughout Massachusetts, were conducted as conference calls.
DESCRIPTION OF SURVEY RESPONDENTS
Family Respondents
321 families completed the family survey (32% response rate). The mean age of respondents' children was 9.7 years, with 2.5% under 3 years of age and 52% between 3 and 10 years of age. There was no significant difference in age or race between respondents and non-respondents. When asked to describe their child's current special health care needs, 6% described the need as a physical limitation only, 12.5% described the need as one that requires help with every day activities, and 33% described the need as one resulting in difficulty with social relationships only. The remaining respondents reported a combination of different types of needs.
PC Respondents
285 PCCs completed the PCC survey (31% response rate). 59% were from group practices, 17% were solo practitioners, and 24% were from outpatient departments or community health centers. Of the 285 respondents, 194 were eligible to complete the entire survey. (91 reported that they either did not provide primary care for Medicaid enrolled children under age 18 or did not provide care for children with special health care needs, and were therefore instructed not to continue beyond the first few survey questions.) Therefore, 194 surveys were used for analysis. When asked to describe their patient population by estimating the proportion of children with special health care needs that fall into various categories, the average responses were as follows:
- chronic disease or physical disability category: 39.4% of caseload
- cognitive impairment category: 30.0% of caseload
- mental health or behavior impairment category: 32.4% of caseload
When asked to estimate the proportion of their entire caseload comprised of children with special health care needs, the mean response was 10.4% (range between 1% and 100%). 60% reported that less than 10% of their caseload was comprised of children with special health care needs.
Managed Care Enhancement Project for Children with Special Health Care Needs: Primary Care Clinician Survey--Mail Survey
| This publication can be viewed in the PDF version of this document. An HTML version is not available at this time. |
Managed Care for Children with Special Health Needs: Parent Survey
| This publication can be viewed in the PDF version of this document. An HTML version is not available at this time. |
Overall Findings of Needs Assessment
An analysis and integration of survey and focus group data revealed overall satisfaction of families and primary care clinicians (PCCs) of children with special health care needs to be generally high. However, when satisfaction with different aspects of care is compared, both families and PCCs reported being less satisfied in some areas than in others. These areas, information, family supports, and coordination of care (in particular, coordination of care regarding home health services, hospitalization and discharge planning, and school health services) were identified by both families and PCCs as areas that present opportunities for improvement.
This summary report includes key findings of the family needs assessment, followed by key findings of the primary care clinician needs assessment.
FAMILY NEEDS ASSESSMENT
Three hundred twenty-one family surveys were completed, and four family focus groups were held. Tables I-IV describe key survey findings. Table V is a summary of the family needs assessment and incorporates key findings of both the survey and focus groups.
The family survey measured overall parent satisfaction in five different areas of care. Table I describes the responses to the five overall satisfaction questions. Most respondents reported being satisfied in most areas in most areas measured. However, when comparing the responses to the overall satisfaction questions, we see that the provision of information and the availability of supports to help parents care for their children with special health care needs stand out as areas in which fewer parents reported themselves "very satisfied." This comparison, in conjunction with the knowledge that patient satisfaction surveys generally reflect a somewhat positive or favorable bias, suggests that the provision of information and availability of family supports are areas that may benefit from improvement.
Parents reported some types of information and supports to be more accessible than others. Tables II and III list parents' ratings of the accessibility of different types of information and supports.
Although overall satisfaction with primary care physicians' coordination of medical care was high (94%), respondents reported primary care physician involvement to be low in several critical areas of care coordination: discharge planning, home care, and school health services. These areas are highlighted in Table IV. These responses are in striking contrast to the responses in other areas measured regarding the primary care physician's role in care coordination. Other areas of care coordination measured revealed primary care physician involvement to be always/usually present for at least 87% of respondents.
One suggested explanation for parents' high level of overall satisfaction with primary care physicians' coordination of medical care, despite low primary care physician involvement in these areas, is that parents may not view communication and coordination with hospital discharge planning, home care, and schools as part of the role of their child's primary care physician and therefore do not attribute them as contributing to their satisfaction (or dissatisfaction) with the way in which the primary care physician coordinates their child's care.
In order to gain further insights regarding the problems of information, support, and care coordination, parents were asked to elaborate on these areas in focus groups. Highlights of the focus group discussions are described in Table V (on the following page), along with a summary of key findings from the parent survey.
Summary of Family Needs Assessment
Parents of children with special health care needs identified the availability and accessibility of information, family supports and care coordination, particularly coordination of care surrounding hospitalization, discharge planning, home care and school health services, as areas that could benefit from improvement. Focus group discussions confirmed these survey findings. They also provided anecdotal information from parents about concerns regarding uncovered or under-covered services. Areas in which parents felt there to be gaps in services included durable medical equipment; dental health services; mental health services; transportation; and interpreter services.
The problems of family supports and gaps in services are not unrelated to those of information and care coordination. Interventions that improve the dissemination of information to both families and primary care physicians may also address the problem of limited access to family supports and perceived gaps in services.
PRIMARY CARE CLINICIAN NEEDS ASSESSMENT
Surveys were received from 285 PCCs: 194 surveys were used for analysis. (91 PCCs were not eligible to complete the entire survey and were therefore excluded from analysis.) Two PCC focus groups were held. Table VI describes selected survey results. Table VII summarizes the PCC needs assessment by incorporating key findings of both the survey and focus groups.
Overall PCC satisfaction in three areas measured by the survey was high. Most respondents reported being satisfied in most of the specific areas measured. In general, respondents reported that "making a difference," and watching a patient progress, grow and develop were key factors contributing to their satisfaction. However, when probed, several areas emerged as areas in which there is room for improvement. Table VI includes a summary of these findings.
Primary Care Clinicians identified several areas of care that could benefit from improvement. The areas identified were those related to care coordination and information regarding the care of children with special health care needs. A summary of key findings of the PCC needs assessment, highlighting PCC concerns, is presented in Table VII.
Summary of PCC Needs Assessment
PCCs identified coordination of care of children with special health care needs, mostly related to the provision of home care services, hospital discharge planning, specialists, schools and parents, as an area in need of improvement. Coordination of care was described as particularly difficult for those children with multiple needs who are serviced by many agencies. PCCs also identified a lack of information--or difficulty in accessing information--regarding the care of children with special health care needs as a problem both for themselves and for parents. In addition, PCCs reported a concern that time limitations prevent them from meeting all of the needs of the child and family. Interventions that improve the dissemination of information and strategies to improve care coordination may, in fact, reduce this problem of time limitations.
| TABLE 1. Survey Findings on Overall Parent Satisfaction | ||||
|---|---|---|---|---|
| Satisfaction with... | Very Satisfied | Somewhat Satisfied | Somewhat Dissatisfied | Very Dissatisfied |
| The way in which their child's primary care physician provides medical care | 71% | 23% | 4% | 2% |
| The way in which child's primary care physician coordinates the medical care their child receives | 71% | 23% | 4% | 2% |
| Support parent receives for their role in caring for their child with special health care needs | 70% | 22% | 6% | 2% |
| Information parent receives on medical care for their child with special health care needs | 56% | 31% | 9% | 4% |
| Support available to help parent provide care for their child with special health care needs | 53% | 31% | 10% | 6% |
| TABLE 2. Survey Findings on Parent Information | ||
|---|---|---|
| Type of Information: Frequency with which Parent can Obtain Information If Needed | Always/ Usually |
Sometimes/ Never |
| Information on child's conditions | 87% | 13% |
| Information on child's developmental needs | 87% | 13% |
| Information on diagnostic procedures or tests performed on child | 86% | 14% |
| Information on MassHealth Managed Care enrollment procedures | 71% | 29% |
| Information on rights within MassHealth Managed Care if parent has a problem or disagrees with child's physician | 71% | 29% |
| Information on MassHealth Managed Care benefits | 70% | 30% |
| Information on research and latest medical discoveries related to child's special health care needs | 68% | 32% |
| Information on other programs that might help their child or family | 60% | 40% |
| TABLE 3. Survey Findings on Family Supports | ||
|---|---|---|
| Type of Support: Ease or Difficulty with which Parent can Find and Obtain Support If Needed | Very/ Somewhat Easy |
Very/ Somewhat Difficult |
| Mental health counseling for other children in the family | 80% | 20% |
| Mental health counseling for parent | 78% | 22% |
| Support with school enrollment or early intervention services | 78% | 22% |
| Assistance coordinating different medical appointments and therapies that child may need | 78% | 22% |
| Mental health counseling for child with special health care needs | 74% | 26% |
| Locating family-to-family support groups | 70% | 30% |
| Assistance finding and arranging for respite care | 68% | 32% |
| TABLE 4. Survey Findings on Coordination of Care | ||
|---|---|---|
| Area of Care Coordination: Frequency of Primary Care Physician Involvement | Always/ Usually |
Sometimes/ Never |
| Communication with School or Early Intervention Program: when requested to do so by parent, primary care physician communicates with staff of child's early intervention program or school | 73% | 27% |
| Discharge Planning: primary care physician plays an active role in the discharge planning process when child is hospitalized | 72% | 28% |
| Home Care: primary care physician (or staff) makes arrangements for home care when it is needed | 70% | 30% |
| Communication with Home Care Providers: primary care physician (or staff) communications regularly with home care providers about the care child receives | 67% | 33% |
| TABLE 5. Summary of Family Needs Assessment | ||
|---|---|---|
| Issue | Survey Findings | Focus Group Findings |
| Information | Types of information parents have needed but had the most difficulty obtaining include information on:
|
Several parents identified the need for all information to be simplified so that more parents could understand it. Types of information noted include:
|
| Family Support | Types of supports parents have needed but have had difficulty obtaining include:
|
Several parents recommended that parents have a Parent/Patient Advocate to provide support. Again, they referred to problems with school health services. The role of the Advocate would be:
|
| Care Coordination | Specific areas of care coordination that need improvement include:
|
Focus group participants consistently mentioned school health services as a major problem. Problems noted included availability of services as well as parents' limited knowledge of services actually provided to their children.
Focus group discussions confirmed that, while many parents are unhappy with coordination and information related to school health services, they do not necessarily expect their child's primary care physician to play a role in coordinating their child's treatment at school. |
| TABLE 6. Survey Findings on PCC Satisfaction | |||||
|---|---|---|---|---|---|
| Satisfaction with... | Very Satisfied | Somewhat Satisfied | Somewhat Dissatisfied | Very Dissatisfied | Most Common Factors Associated with Dissatisfaction |
| The relationships PCC has with parents of patients with special health care needs | 57% | 35% | 7% | 1% |
|
| The relationships PCC has with specialists to whom they refer children with special health care needs | 45% | 49% | 6% | 0% |
|
| Their role as a Primary Care Clinician for children with special health care needs | 36% | 53% | 11% | 0% |
|
| TABLE 7. Summary of PCC Needs Assessment | |
|---|---|
| Issue | Key Survey and Focus Group Findings |
| Coordination with Specialists |
|
| Coordination with Home Care and Hospital Discharge Planning |
|
| Coordination with Schools |
|
| Information |
|
| Parent Role |
|
Session 2: Impact of Managed Care on Adults with Mental Illness
Reactor Biographies
Howard H. Goldman, M.D., M.P.H., Ph.D.
Howard Goldman is Professor of Psychiatry at the University of Maryland, School of Medicine at Baltimore, where he is Director of Mental Health Policy Studies. From 1983-1985 he served as Assistant Institute Director at the NIMH, where he was responsible for mental health care financing policy and related research. He continues to consult to the Federal Government on health care finance, including his service in 1993 on the President's Task Force on Health Care Reform.
As Assistant Director of NIMH, he worked with the Social Security Administration (SSA) on the revision of the mental impairment standards for the disability program. Subsequently, he consulted to the American Psychiatric Association on a SSA contract to assess the reliability and validity of those standards. Dr. Goldman has written several articles in the professional literature on the SSA disability program and recently conducted a published review of measures of functional assessment. He also consulted to Westat on the design of the Disability Examination Study for SSA, and he is a member of the National Academy of Social Insurance Policy Panel on Disability.
Dr. Goldman is a frequent contributor to the professional literature in mental health services research and economics. His resume lists ten books, 20 monographs and reports, and over 150 articles and chapters. Dr. Goldman's editorial board appointments have included Health Affairs, Journal of Mental Health Administration, Psychiatric Services (formerly Hospital and Community Psychiatry), and the American Journal of Psychiatry. In addition, he has just completed the fourth edition of his textbook for medical students, Review of General Psychiatry.
Michael F. Hogan, Ph.D.
Michael Hogan has served as Director of the Ohio Department of Mental Health since March 1991. He was Commissioner of Mental Health in Connecticut from 1987-1991 and was credited with leading that State to a fourth place ranking among the State mental health systems in 1990--tied with Ohio. Previously, he served as a Regional Director and State Hospital Superintendent in Massachusetts, and was responsible for administering mental health and mental retardation programs in Western Massachusetts.
Dr. Hogan holds a bachelor's degree from Cornell University and a Ph.D. from Syracuse University. He is President of the Board of the National Association of State Mental Health Program Directors (NASMHPD) Research Institute and serves on the National Advisory Council, which approves NIHM research grants. He has authored a text and numerous book chapters and papers on mental health care, with his most recent publications focussed on The Organization and Financing of Mental Health Care and Managing the Whole System Under Managed Care. He is married and has three sons.
Severely Mentally Ill HMO Members
Bentson H. McFarland, M.D., Ph.D.
Bentson McFarland is Professor of Psychiatry, Public Health and Preventive Medicine at Oregon Health Sciences University and Adjunct Investigator at the Kaiser Permanente Center for Health Research in Portland, Oregon. He received his M.D. degree and a Ph.D. in biostatistics from the University of Washington in Seattle. He conducts research on mental health services, pharmacoeconomics, and pharmacoepidemiology.
RESEARCHERS
- Bentson H. McFarland, M.D., Ph.D.
- Richard E. Johnson, Ph.D.
- Mark C. Hornbrook, Ph.D.
BACKGROUND: MEDICAL OUTCOMES STUDY
- Depressed psychiatric patients disenrolled from HMO sooner than comparable fee for service patients
- No HMO controls
OBJECTIVES
- Enrollment duration
- Service use
- Cost of care
SEVERELY MENTALLY ILL HMO MEMBERS
- Specialty mental health users
- Diagnosis of schizophrenia or bipolar disorder
- Cohort #1
- Outpatient records 1986-1987
- Follow-up through 1990
- Cohort #2
- Inpatient records 1990-1991
- Follow-up through 1995
CONTROLS (AGE AND SEX MATCHED)
- Membership
- Pharmacy users
- Diabetic patients
SEVERELY MENTALLY ILL SURJECTS (COHORT #1)
- N = 250
- Age = 32
- Male = 50%
- Schizophrenia = 32%
- Prior state hospital use = 41%
PREDICTORS OF LONGER ENROLLMENT FOR SEVERELY MENTALLY ILL SUBJECTS (COHORT #1)
- Prior enrollment duration (p < .006 )
- Community mental health center use (p < .05 )
Note: HMO costs of care not predictive of enrollment duration
CONCLUSIONS
- Severely mentally ill HMO members maintain HMO enrollment (as do other ill HMO members)
- Community mental health center use associated with longer enrollment
- HMO costs of care not related to enrollment duration
| TABLE 1. Utilization and HMO Costs During Follow-Up (Cohort #1) | ||
|---|---|---|
| Severely Mentally Ill | Controls | |
| Community mental health center | 40% | 5% |
| State hospital | 12% | 1% |
| Exceeded mental health benefit | 12% | 0% |
| TABLE 2. Enrollment Duration (Cohort #1) | |
|---|---|
| Days in HMO | |
| Diabetic patients | 1,424 |
| Severely mentally ill | 1,263 |
| Pharmacy controls | 1,236 |
| Membership controls | 1,023 |
| TABLE 3. Enrollment Duration (Cohort #2) | |
|---|---|
| Days in HMO | |
| Diabetic patients | 1,256 |
| Severely mentally ill | 1,158 |
| Pharmacy controls | 861 |
| Membership controls | 175 |
Colorado's Early and Preliminary Experience with Capitation for the Severely and Persistently Mentally Ill Adults
Joan R. Bloom, Ph.D.
Joan Bloom is Professor of Health Policy and Administration at the University of California, Berkeley in the School of Public Health. She received her doctorate in Sociology of Education at Stanford University. She is a Co-Investigator at the Center for Mental Health Services Research. In addition, she is an Affiliated Investigator at the Northern California Cancer Center and a Consultant for the Stanford University Medical Center. Her research interests include organizational studies and community services focused on the delivery of medical and mental health services. She has had a long-standing interest in prevention and early detection of chronic disease. She is currently the Principal Investigator of two NIH funded studies: (1) the Colorado Capitation Study in which mental health services are being capitated for the Medicaid eligible population in the State of Colorado funded by the National Institute of Mental Health; and (2) Young Women with Breast Cancer, funded by the National Cancer Institute in which ethnically diverse, newly diagnosed younger women in the greater Bay Area are assessed and provided with a psychosocial support intervention. She is also involved in a longitudinal study focused on work redesign of hospital nurses. She serves on the Board of Directors of the Northern California Cancer Center and on the editorial boards of Cancer Prevention, Epidemiology and Biomarkers and International Journal of PsychoOncology. She serves on the Breast and Cervical Cancer Advisory Committee for the State of California and is Chair of their Evaluation Committee.
Dr. Bloom's teaching interests include organizational sociology, health care management, and program planning and evaluation. She teaches courses in program planning and evaluation, and master and doctoral level courses in organizational studies plus a variety of seminars.
RESEARCHERS
- University of California, Berkeley
- Joan R. Bloom, Ph.D.
- Teh-wei Hu, Ph.D.
- Jaclyn W. Hausman, M.P.H., M.P.P.
- Neal Wallace, M.P.A.
- Richard Scheffler, Ph.D.
- MEDSTAT, Washington, DC
- Brian Cuffel, Ph.D.
COLORADO'S MENTAL HEALTH SYSTEM
- Seventeen Community Mental Health Centers (CMHCs) provide the majority of outpatient services.
- Two state hospitals provide short and long term psychiatric services.
- Additional emergency services are provided in private facilities.
FEATURES OF CAPITATION PROGRAM
- Pilot program.
- Fully capitated--inpatient and outpatient.
- Carve-out.
- Covers all Medicaid beneficiaries needing mental health services.
- August/September 1995 program began.
SPECIFIC AIMS:
- Consumer Outcomes:
- Do consumer outcomes differ?
- Access and Utilization:
- Does access and utilization of mental health services change?
- Cost:
- Does the cost of services differ?
- Cost-Effectiveness:
- Does cost-effectiveness differ?
- Implementation and Innovation:
- Does capitation facilitate innovation in public mental health systems?
SUBJECT CHARACTERISTICS
- Medicaid Eligible
- Gender (50% female, 50% male)
- Diagnosis:
- Schizophrenia OR
- Bipolar Affective Disorder OR
- Any diagnosis and 24-hour care episode in previous year
- Cost (High cost/Low cost)*
*Only for 1994 sample
ORGANIZATIONAL CHANGE MEASURES:
- Community Program Philosophy Scale
- Organizational Culture Questionnaire
- Organizational Structure Survey
- Key Informant Interviews
| TABLE 1. Research Design | |||
|---|---|---|---|
| Targets for Each Cell | 1994 | 1995 | New to System |
| Model 1* | 128 | 64 | 64 |
| Model 2* | 128 | 64 | 64 |
| Comparison - FFS | 128 | 64 | 64 |
| Model 1 = Stand Alone/Alliance CMHC Model 2 = Joint venture between FP managed care firm and Stand Alone/Alliance CMHC |
|||
| TABLE 2. Status of Consumer Interviews: 9/1/96 | |||
|---|---|---|---|
| Wave 1 (Baseline) |
Wave 2 | Wave 3 | |
| Completed Interviews | 684 | 521 | 232 |
| Refused | 116 | 13 | 3 |
| Deceased | n/a | 5 | 4 |
| Unable to Locate | 53 | 11 | 1 |
| Non-Response | 35 | 7 | 0 |
| Too Ill | 7 | 3 | 3 |
| Contacted to Date | 895* | 560 | 243 |
| Success Rate | 76% | 93% | 95% |
| * An additional 361 individuals were assigned for a total of 1265, however, these potential subjects were deemed inappropriate for a variety of administrative and clinical reasons. | |||
| TABLE 3. Socio-Demographic Characteristics of Sample for Each Group | |||
|---|---|---|---|
| Characteristic | Model I (%) |
Model II (%) |
F.F.S. (%) |
| Gender Male Female |
48.5 51.5 |
49.4 50.6 |
47.9 52.1 |
| Ethnicity White Black Hispanic |
67.7 4.0 6.1 |
46.9 4.9 19.8 |
45.8 18.8 8.3 |
| Age 21-35 36-50 51-65 65+ |
43.4 41.4 13.1 2.0 |
25.9 46.9 19.8 7.4 |
31.9 53.2 6.4 8.5 |
| Diagnosis Schizophrenic Bipolar-Affective Disorder Other |
|||
| High Cost Client | 31.3 | 39.5 | 52.1 |
| TABLE 4. Utilization of Mental Health Services for Each Model Before and Following Implementation of Capitation* | ||||||
|---|---|---|---|---|---|---|
| Characteristic | Model I | Model II | FFS | |||
| Pre- | Post- | Pre- | Post- | Pre- | Post- | |
| Inpatient Outpatient Day Treatment Crisis Intervention Individual Therapy Group Therapy Case Management |
||||||
| * 6 months prior to six months following capitation as of November 1996. | ||||||
| TABLE 5. Costs Per Unit of Payment (Mean and Variance) for Mental Health Services for Each Model Before and Following Implementation of Capitation* | ||||||
|---|---|---|---|---|---|---|
| Characteristic | Model I | Model II | FFS | |||
| Pre- | Post- | Pre- | Post- | Pre- | Post- | |
| Inpatient Outpatient Day Treatment Adult Treatment Crisis Intervention Individual Therapy Group Therapy Case Management Total Costs |
||||||
| * 6 months prior to six months following capitation as of November 1996. | ||||||
| TABLE 6. Outcomes of Mental Health Services for Each Model Six Months Before and Six Months Following Implementation of Capitation* | ||||||
|---|---|---|---|---|---|---|
| Characteristic | Model I | Model II | FFS | |||
| Pre- | Post- | Pre- | Post- | Pre- | Post- | |
| Health Status (MOS SF36) Physical Functioning Bodily Pain General Health Social Functioning Mental Health |
||||||
| Mental Health Symptoms (BPRS) |
||||||
| Functional Status GAF Score Family Contact Daily Activity Social Contact |
||||||
| Quality of Life Ever Homeless Housing Adequacy |
||||||
| Finances Self-reported Income Income Adequacy Average Adequacy |
||||||
| * Results as of November 1996. | ||||||
 |
 |
The Effects of Private Sector Mental Health Carve-Outs
Thomas G. McGuire, Ph.D.
Thomas McGuire is a Professor of Economics at Boston University. He has authored or edited three books and more than 100 published articles on health and mental health economics and policy. In 1983, his book, Financing Psychotherapy, received the Elizur Wright Award from the American Risk and Insurance Association recognizing an outstanding contribution to the literature on risk and insurance. He received the Carl Taube Award for outstanding contributions to mental health services research from the American Public Health Association in 1991. He has served as co-chair of three NIMH-sponsored conferences on economics and mental health, and has been the Research Director of a training program in economics and mental health at the Heller School at Brandeis University since 1981.
Dr. McGuire is the recipient of two sequential five-year Research Scientist Awards from the National Institute of Mental Health to study payment and financing of mental health services. Currently, he is also a recipient of an Investigator Award in Health Policy from the Robert Wood Johnson Foundation (joint with Richard Frank) to study reform of the organization and financing of mental health and substance abuse.
PRESENTATION NOT AVAILABLE AT TIME OF PRINTING. PLEASE REFER TO THE BACKGROUND PAPER COSTS AND INCENTIVES IN A MENTAL HEALTH AND SUBSTANCE ABUSE CARVE OUT.
The Massachusetts Mental Health System Change
Barbara Dickey, Ph.D.
Barbara Dickey is Associate Professor, Department of Psychiatry, Harvard Medical School and Director of Mental Health Services Research at McLean Hospital. She has been studying the costs and outcomes of care for the seriously mentally ill in different treatment settings for many years, including studies of hospital alternatives, community-based systems and comprehensive treatment models that integrate acute and long-term care for the psychiatrically disabled. She has been a frequent contributor to the professional literature and has recently co-edited a book on measuring behavioral health outcomes in clinical practice. With NIMH funding, she recently completed a cost-effectiveness study of housing and treatment for adults who are homeless and mentally ill and she is current the Principal Investigator of an NIMH study of managed care in Massachusetts.
PRESENTATION NOT AVAILABLE AT TIME OF PRINTING. PLEASE REFER TO THE BACKGROUND PAPER MANAGING THE CARE OF SCHIZOPHRENIA.
Costs and Incentives in a Mental Health and Substance Abuse Carve Out
Ching-to Albert Ma and Thomas G. McGuire
Draft; preliminary and unfinished
DO NOT QUOTE OR CIRCULATE
ACKNOWLEDGEMENT
Financial support from National Institute of Drug Abuse Cooperative Agreement 1-P50-DA10233-01 and grant K05-MH01263 from the National Institute of Mental Health is gratefully acknowledged. We thank our research assistant Didem Bernard for her excellent help. We are grateful to the Group Insurance Commission of the Commonwealth of Massachusetts for allowing us access to the data.
ABSTRACT
This paper examines the overall change in costs of mental health and substance abuse services in a carve out program initiated in 1993 by the General Insurance Commission (GIC) of the Commonwealth of Massachusetts. Claims data for two years before (July 1991-June 1993) and two years after (July 1993-June 1995) the carve out were obtained from the GIC. These data were accompanied by an eligibility file for the four-year sample period. The exact financial arrangements in the vendor-payer contract are examined and described. The paper provides a full description of incentives, including multi-year contract renewals, and the payments and incentives associated with the administrative portion of the payments. We use those incentives to generate hypotheses about the effects of managed care on patterns of service use and cost.
The paper quantifies the changes in costs between the two years before the carve out and the two years after. By examining patterns of services in a population of continuously enrolled individuals, we eliminate selection-related changes in characteristics of the population.
The paper's main contribution is to describe and decompose the effect of managed care for mental health and substance abuse and to relate the observed effects to the incentives in the contract. We show the total plan and employee payments by month of service date for all major categories of expenditures, such as inpatient, other residential, and office visits. Trends in medical care prices will be used to adjust the data. Our basic decomposition therefore show impact by type of services, and show this separately for plan and employee-paid costs.
Our findings indicated significant savings after the carve out. Total and plan costs reduced by 50% to 70% over the four-year period. The pattern of cost reductions are similar with respect to outpatient and inpatient services, as well as to mental health and substance abuse services. The estimated average price of a mental health outpatient visit increased over time in the sample period, whereas that of a substance abuse outpatient visit decreased slightly.
INTRODUCTION
Many big employers and payers have contracted with specialty management firms to administer the delivery of mental health and substance abuse (MHSA) benefits to their enrollees. This so-called MHSA "carve out" appears to be a most significant recent development, and has led to a new "behavioral healthcare" industry consisting of firms specializing in this service. Oss (1994) estimates that in 1994 over 50 million people in the U.S. are in some carve out program. "Risk-based" contracts, in which the specialty vendor (usually a for-profit corporation) bears some or all of the financial risk associated with MHSA services, are used in about half of all carve out programs. The rapidly growing use of separate carve-out contracts has been stimulated by reports of very favorable cost experience for many payers, with some savings reported to be in the range of 40 percent or more (Frank, McGuire and Newhouse 1995).
From an employer's or a payer's point of view, a carve out contract addresses the longstanding issues of moral hazard and adverse selection associated with insurance for mental health services (McGuire 1981; Frank, Huskamp, McGuire and Newhouse forthcoming; Frank, Glazer and McGuire 1996). Moral hazard is contained by the techniques associated with managed care--price negotiations, provider network selection and monitoring, prior authorization and utilization review. Adverse selection can be addressed by unification of the financial risks associated with mental health within a single contract; by pooling all persons in the same contract, no plans compete to avoid costly MHSA users.
Although the carve out approach offers these potential advantages in principle, the practical importance of this new form of insurance contract remains to be established. Favorable experience of innovative firms need not be a good predictor of what happens to the typical employer. First, if payers who first adopted carve out methods for MHSA services management are those with below average management efficiency in their previous existing plan ("low-hanging fruit" in the language of the industry), then the effectiveness of carve outs may be much less for payers with well-run plans (Frank, McGuire and Newhouse 1995). Second, the experience of a particular payer and population is often influenced by many specific factors, some of which may not apply to other payers. Therefore, it appears important to study the diversity of payer and population characteristics, vendors' management techniques, and the actual contracts between them carefully, before generalizations are made.
We contribute to the accumulating evidence on carve outs and managed care by reporting on the experience of the MHSA carve out of a major employer in Massachusetts--the Commonwealth itself. In this first paper in a continuing project on this case, we relate the incentives in the contract to the aggregate experience. First, we describe the MHSA carve out contract between the Commonwealth of Massachusetts and the vendor, and identify its incentive implications. Second, we analyze insurance claims data for two-year periods before and after the carve out. We examine the association between the contract incentives and the actual cost outcomes, and use the period before the carve out as a benchmark for comparison. Before-and-after comparisons can be problematic because the underlying population can change. We have therefore selected for detailed analysis a group of enrollees who are continuously covered for the entire four-year data period, and examine the actual use and cost experience for them before and after the carve out.
BACKGROUND AND LITERATURE REVIEW
A behavioral health carve-out program was initiated in 1993 by the GIC of the Commonwealth of Massachusetts. The largest private payer in the state with an enrollment base of about 120,000, the GIC is responsible for providing health insurance to state and some local employees and their dependents. The GIC contracted with a combination of traditional indemnity insurers as well as HMOs since the middle of the 1970s. Between fiscal years 1989 and 1992, the State Hancock Plan, administered by John Hancock Mutual Life Insurance Company, was the indemnity plan for GIC enrollees. This managed fee-for-service plan included preadmission certification, utilization and concurrent reviews, second opinions and discharge planning, as well as pharmacy provider networks as managed-care features. These provisions applied to all areas of medical care, including MHSA services. In addition, GIC contracted with 14 HMOs (staff/group and network models) and offered them as enrollment options to employees.
The GIC voted to change its health benefit plans in late 1991. The stated goal was to improve the value of services to employees given the overall expenditure level, increase enrollment in managed care, and reduce risk fragmentation and adverse selection problems (Group Insurance Commission, Request for Proposal, 1992, p.1-3). To achieve this, the GIC retained services of a management consulting firm to assist with the evaluation of its existing benefits program, and the search for alternative benefit designs. One of the consultant's recommendations adopted by the GIC was the development of a separate MHSA carve-out progarm for enrollees. By a proposal request and subsequent biddings and negotiations, GIC selected a behavioral health care firm, Options Mental Health, Inc., from among five applicants, to set up a managed care mental health network of physicians and providers, and to manage mental health and substance abuse care on a partially at-risk basis.
The trade press contains many favorable reports of the experience of employers with carve out plans. Battagliola (1994) summarizes the experience of IBM which implemented a behavioral health carve out in 1991. In 1989, IBM was spending $106 million on MHSA benefits for its employees and dependents; this was going up at 10 percent per year, and consuming 15 percent of all health benefit costs. The carve out (with Value Behavioral Health [VBH]) consisted of a PPO with differential in-network and out-of-network cost sharing, expansion of alternative treatments, strengthening of an Employee Assistance Plan (EAP), and utilization review. By 1993, IBM's mental health costs had fallen to $59.2 million and only 10 percent of health benefit costs. Clearly, something happened here! The article provides some information about enrollment changes (the number of employees was falling by 3-4 percent per year in the later years of the data), prices (inpatient cost per day fell by 40% between the pre and post periods), and benefit changes, but understanding what happened is difficult because no information is provided on the nature of the contract between IBM and VBH, or on the composition of the expenditure changes. Finally, it is worth mentioning that IBM began the initiative with a very generous plan and very high rates of spending per employee, approximately $660 per employee per year on MHSA, more than double the national average for the period. Reducing costs by 30 percent (in real terms) still leaves IBM far above average rates of spending.1
The formal research literature on carve outs is just emerging. Grazier et al. (1993) examine outpatient utilization data one year before and one year after implementation of a PPO point-of-service plan with a benefit change for 4,220 continuously enrolled, active employees. Overall the rate of outpatient use went up slightly, but the visits per user fell slightly. The employer/vendor contract was "administrative services only" or ASO, so the vendor bore no explicit financial risk associated with utilization.
Frank and McGuire (1996) describe the experience of a carve out plan for MHSA in Massachusetts Medicaid with aggregate data from one-year pre and three and a half years post institution of a behavioral healthcare carve out. Price reductions for inpatient care and the virtual elimination of inpatient treatment for substance abuse appear to have been the main mechanism generating savings of approximately 25 percent per enrollee in real terms. The reduction in services was experienced virtually entirely by the disabled Medicaid beneficiaries. AFDC enrollees saw their costs (adjusted for medical price inflation) go up slightly over the course of the contract. The one-year contracts between the state and the vendor, Mental Health Management of America (MHMA) were almost entirely ASO contracts, and gave the vendor small incentives to reduce costs. Massachusetts began the period ranking third among the state in terms of overall health care spending for per Medicaid beneficiary. [ref]
DATA: ELIGIBILITY AND CLAIMS FILES
Data for this project come from eligibility and health claims files, covering the period July 1991 through June 1995, and provided to us by MEDSTAT. Identifying information about the contract holder was scrambled so that claims data could be merged with eligibility information without identifying contract holders. The eligibility data allow us to calculate the average number of Primary Insured Participations, or PIPs for each month. A PIP is essentially a contract holder.2 Family contracts may cover more than one individual. We use relation, sex and date of birth information to identify individuals.
For some analyses we use a subsample of PIPs consisting of those covered by the GIC for the entire four-year sample period.3 The purpose of identifying this "continuously covered" population was for a better control of sample characteristics. All of these individuals have been covered by the GIC before and after the carve out. Cost outcomes of the continuously covered subsample will be compared to those of the entire sample. About 40,000 individuals are in our continuously covered population.
In the post carve out period after July 1993 we sought information about any claim for MHSA that would be covered by the carve out contract. Inpatient and other residential care was included in the sample. For outpatient care, we extracted any claim with a mental health procedure. A comparable selection criteria was used for the pre period as well, to make utilization in the pre period comparable to utilization in the post period.4
The claims data contain several cost related fields. The contract between GIC and Options is driven by the amount that the GIC has to pay, so some of our analysis will be based on the payments by GIC reported on the claim. Claims also contain information about payment amounts that are the responsibility of the beneficiary such as copayments and deductibles. Finally, covered charges represent the total negotiated price that Options has arrived at with the provider. Normally, the sum of GIC payments, beneficiary payments, and other payer obligations (if any) will be covered charges. Providers also report charges, but we will not use this information in this paper.
Units of services such as length of stay (LOS) and visits on some outpatient claims are also reported on claims. Price per unit will be calculated by dividing covered charges by the appropriate units.
Claims data for the last two months in the sample period appear to be incomplete, apparently because of delays in the submission and processing of claims. We requested data as of November 1995, allowing three months past the final service date, but this was not long enough to accumulate almost all claims for the last quarter of data. For this reason, we discarded the claims data for the last three months in the sample period, and instead base the last year's figures on seasonally adjusted nine-month data.
By any standard the data show a very significant cost reduction after the carve out. Table 1 summarizes the findings for the entire enrolled population; all prices and costs are in current year dollars. For this population, the total net payment from GIC for all MHSA services was about $9.32 million for fiscal year 94 (July 1993-June 1994), and $7.29 million for fiscal 95. These compare to $16.93 million in fiscal 92 and $14.87 million in fiscal 93, the two years before the carve out. The average GIC payment per PIP per month for the four years between 1992 and 1995 were, respectively, $20.32, $17.84, $9.52, and $7.49. The average GIC payment per enrollee per month for these years were, respectively, $13.91, $12.22, $6.04, and $4.76.
Table 2 presents similar cost figures for the continuously covered population, and all price and cost figures are in constant 1995 dollars, with medical price index adjustment. Here the total GIC payment between 1992 and 1995 were, respectively, $10.45, $8.47, $4.60, and $3.89 millions. The average payments per PIP per month were, respectively, $32.41, $26.24, $14.26, and $12.08; per enrollee per month figures were, respectively, $22.03, $17.84, $9.70, and $8.22. Overall various indicators of "costs" have decreased between 50% and 70% in four years. We also find that total costs of MHSA services--the total paid by GIC, enrollees, as well as any third parties--show a similar pattern. Thus, the savings were not simply achieved by shifting costs from the GIC to enrollees or another payer.
Table 3 categorizes the plan and total costs of the continuously enrollees according to inpatient versus outpatient services: inpatient costs declined by about 50% while outpatient costs by more than 60%. The breakdown of these changes according to MHSA care are illustrated in Table 4.
THE CONTRACT BETWEEN THE GIC AND OPTIONS
To understand the contract between Options and the GIC, it is useful to provide some background about the proposal request and negotiation processes. In the Request for Proposal (RFP), each potential bidder was provided with a summary of the plan enrollment, costs, and utilization pattern data for two years before the RFP was released. For each of the two years, the data included hospital admission and outpatient visit rates per 1,000 enrollees, number of hospital days per 1,000 enrollees, costs per hospital admission and outpatient visit, and costs per employee. These data were given for MHSA services, both separate and combined, for all employee groups.5 Utilization pattern data, such as distribution of admissions by diagnosis and outpatient visits, readmission rates, patterns of large claims, were also provided.
The GIC and its consultants first used the data to establish a set of benchmark projections of costs and savings. Each potential vendor was asked to provide its own set of projections, and the two sets of projections were compared and evaluated after the bids were submitted.6 Finally, Options was selected as the winner, and the details of the final MHSA contract were decided.
We now describe the contracts between the GIC and Options. The initial contract was for a one-year duration, and began in July 1993. It was expected at the time that the contract renewal for a second year would happen when the initial contract expired. We will briefly describe the benefit and coverage design. Detailed descriptions of the financial arrangements between GIC and Options will then be provided.
Important dimensions of the new benefit plan for MHSA were dictated by the GIC in the RFP. The MHSA carve out would be a managed care plan, nominally similar to the "managed care" in the previous Hancock plan, but expected to be more aggressive. The GIC specified the in-network and out-of-network benefits, goals for provider networks, and even the utilization levels (10, 20, 30 visits) at which the vendor should be intervening in the care process. Implementation of these features were of course to be left to the vendor. Benefits to enrollees choosing in-network care in the point-of-service plan were expanded from coverage before the carve out. Providers were to be precertified by Options before being admitted to the network. Whether an enrollee receives care from a network provider or not, precertification must be obtained from Options by calling a toll-free telephone number before care began (except for emergencies). A Clinical Case Manager was responsible for precertification. Options must be notified within 24 hours of any hospitalization, whether emergency (life-threatening), urgent, or routine. Complaints and grievances were reviewed by Options representatives, as are disagreements with clinical determinations.7
Financial aspects of the carve out that are relevant to enrollees are as follows.8 Generally, in-network coverage for inpatient services is complete with no deductibles; out-of-network inpatient coverage is 80% of allowed charges, with a 60 days limit per year and with a two-admission or two-episode lifetime limit on substance abuse treatments. In-network outpatient visits are free for the first four, subject to a $20 copayment for the fifth to twenty-fifth, and subject to a $40 copayment thereafter. Out-of-network outpatient coverage is 50% of allowed charges, and subject to a maximum of 15 visits per year. In-network out-of-pocket expenses are limited to $1,000 per individual and $2,000 per family. Finally, the lifetime benefit maximum is $1 million.
Benefits and cost sharing in the MHSA carve out program were substantially better for the enrollees than their previous plan. Before the carve out, mental health inpatient coverage at a general hospital was complete for 120 days (after a $150 deductible), then 96% after annual deductible. But mental health coverage at a psychiatric hospital was complete for only 60 days, and at 80% thereafter with a limit of 300 days. Perhaps, the most striking difference was that before the carve out, substance abuse coverage at a substance abuse facility was at 80% and only up to $10,000 a year after deductible. Outpatient MHSA coverages were respectively at 50% and 80%, with respective limits of $1,500 and $2,500 per year after deductible. The annual benefit limit was $500,000; lifetime, $1,000,000. The benefits after the MHSA carve out represented significant improvements, especially for in-network care.
The financial contract between the GIC and Options consisted of two main parts. First, for the fiscal year beginning July 1993, each month Options received from the GIC a fee (the ASO fee), which was calculated by multiplying the number of PIPs by $3.43. Second, this rate would be adjusted upward by 5% in the second year unless otherwise agreed upon by the GIC and Options.9 The contract for fiscal 1993-4 also specified a target claims cost of $20.72 per month per PIP. Besides serving as a benchmark to evaluate cost effectiveness of the contract, it would be used to adjust the ASO fee. In the actual implementation, for the fiscal year beginning July 1994, the ASO was revised to $3.17 per month per PIP, and the target level lowered to $15.39 per month per PIP.
For the fiscal year beginning July 1993, the target was established at $20.72 per month per PIP. The $20.72 refers to the portion of costs paid by the GIC, and does not include enrollee cost sharing. At the end of the fiscal year, the actual claims costs would be compared with the aggregate claim target (aggregate, because the rate was stated in terms of per month per PIP), and the ASO fee would be reduced by an amount equal to 20% of the excess of actual claims over the target, but this reduction would not be more than 20% of the ASO fee for the contract year. For example, if the claims cost turned out to be $21.72 per month per PIP, then the ASO fee would be reduced by $0.2 (20% of $21.72-$20.72) per month per PIP. The maximum cost overrun for which Options's ASO was reduced was $(20.72+3.43)=$24.15. For fiscal year 1995-6, the target was reduced to $11.19 per month per enrollee, but the ASO fee was raised to $5.18 per enrollee per month. The adjustment of the ASO fee according to the excess of claims costs over target remained unchanged.
Besides the adjustment of the ASO fee according to the discrepancy between actual claims cost and the target, Options was required to satisfy performance targets. During the first year, the set of performance guarantees consisted of five items, but expanded to sixteen in the second. The following is a sample from those in both years:10
- At least 90% of enrollees surveyed by an independent contractor should be satisfied with the services they received.
- Options should deliver reports by due dates.
- Options should guarantee claims financial accuracy to be no less than 99%; payment accuracy, 97%; procedural and coding accuracy, 95%.
- In the event that any of these guarantees was not met, Options must pay a penalty to GIC equal to 2% of the ASO fee for each guarantee violation, but the maximum of such penalty payment could not exceed 23% of the ASO fee.
It is important to keep in mind that the overall benefit package was expanded substantially after the carve out. In particular, coverage for in-network outpatient care was greatly improved. If enrollees' copayment and deductible remain unchanged, this coverage improvement must tend to increase use. Furthermore, even if use did not increase due to the benefit expansion, the improvement in coverage for in network care would tend to shift costs to the GIC from other payers whohave contracts with the GIC enrollees. Thus, Options would have to implement some cost savings measure simply to be able to maintain costs to the GIC at existing levels. Indeed, the initial claims target of $20.72 per PIP was such a level that savings by Options would just offset any cost increasing effects of the benefit expansion.
INCENTIVES IN THE CONTRACT
First consider the explicit incentives in the first year of the contract, and focus on the financial penalty and rewards associated with the claims target. Up to 20% of the ASO fee could be refunded to the GIC in case the actual cost was higher than the target level. The ASO fee to Options was the result to negotiations, and was paid regardless of the costs actually incurred in administration; thus, it was a type of prospective payment. The ASO fee included a profit allowance, but the actual profit or loss might be higher or lower depending on the costs actually incurred by Options.
Clearly, Options would attempt to economize on its own administrative expenses. If controlling MHSA costs requires Options' resources, such resources would only be provided if Options is properly motivated. Indeed, the carve-out contract does contain explicit incentives for Options to control MHSA service costs. The most explicit of such incentives is associated with the claims target. The ASO fee could be reduced by up to 20% in response to costs accumulating above the claims target. To such a small company, this probably represented a significant amount of potential earnings. Nevertheless, most of the financial risks remain with the GIC. In spite of the fact that the contract is written in terms of a per PIP per month payment, the contract is very far from being a "capitation" contract in which risk is shifted largely to the vendor.
These points are extremely important and illustrated in different ways in Figures 1 and 2. Figure 1 shows how the ASO fee to Options, and costs to the GIC vary with the actual level of claims costs per PIP in the contract's first year. Options faces some risk, but this is quite small in comparison with the possible cost variations faced by the GIC. Given the different sizes of Options and the Commonwealth of Massachusetts, the risk sharing arrangement appears to be sensible. Although GIC does bear most of the MHSA service costs, the remaining cost responsibility assumed by Options still seems significant for providing incentives for Options to meet the cost target. Figure 2 depicts the same risk sharing arrangement in a "proportional" way. Here, it is clear that the carve-out contract does not shift all cost responsibilities to the vendor.
As we noted above, the contract between GIC and Options was subject to renewal after the first year. The initial contract did specify an automatic adjustment on the ASO fee by 5% but other details of the contracts were open to revisions. In fact, in the second year, the same type of contract was signed by the GIC and Options, but the cost target was lowered from $20.72 per month per enrollee to $15.39 (or about 25%).
INTERPRETATION: INCENTIVE CONTRACTS AND PERFORMANCE
The ASO fee arrangements for Options contained a number of very interesting features. First, the contract did not allow the ASO fee to increase when Options was able to lower costs below the target level, but was subject to the risk of up to 20% of the fee for cost overruns. For a company of the size of Options, the total risk does not appear to be totally insignificant. This perhaps contrasts with the Massachusetts Medicaid behavioral health carve out (see Frank and McGuire, 1996), where the "at-risk" contract imposed a maximum penalty of $300,000 in the first year of the contract. In contrast, if the ASO fee was $3.43 per month per enrollee, for a population of 70,000 PIPs, Option's potential penalty in a year could be more than $560,000. If the use of aggressive managed care to reduce claims costs meant higher administrative expenses, the incentives established by the ASO fee mechanism would imply that costs should not be expected to fall significantly below the target level. But in actual fact, the first-year claims costs did fall significantly below the target. This brings us to the second point.
Options might have correctly anticipated that significant cost savings in the first year could have two effects. First, its superior performance might prompt the GIC to raise its expectation about cost saving potentials. A likely consequence was that GIC would lower the target rate. This phenomenon of superior contract performance resulting in more demanding terms in the future is called the "ratchet effect" in the contracting literature (see Laffont and Tirole, 1986, for example). Second, Options might think that it could convince the GIC that its value to the behavioral mental health carve out was high by demonstrating excellent performance in the first fiscal year. This could enhance Options's bargaining power in the contract renewal for the third year. In addition, it might also be a good signal to the market, so that Options's prospect of winning new contracts would be improved. We will call this the "reputation effect."
Clearly, the ratchet and reputation effects act against each other: the former induces Options to lower its performance, but the latter provides the opposite inducement. We can argue that Options in fact chose a performance level that traded off these two opposing effects. It was interesting to observe that the target rate was lowered in the second year by about 25% (in normal terms), and further reduced in the third year, but the administrative fee was reduced by a little in the second year, and then raised significantly in the third year.
From the perspective of incentives, the existence of a penalty for cost levels that are above the target does not necessarily imply that the target level will be achieved. In fact, Options might optimally choose to violate the target, incurring some penalty while saving administrative expenses. Nevertheless, the contract did not provide any incentive for Options to lower costs below the target level, since Options was unable to keep any savings. Therefore, it seems to us that what needs to be explained was the fact that Options achieved much more: in each of the years after the carve out, the actual costs were lower than the target level by a significant amount. Here, our hypothesis is that the reputation effect initially dominated the ratchet effect: for small cost reductions beyond the target level, Options's reputation began to build up, but the ratchet effect did not become important until significant savings beyond the target level was attained.
To understand the impact of the carve out, it is important to distinguish different two sets of relationship changes. First, Options was brought in to implement the provision of MHSA services by managed care. Whereas before the carve out, only those enrollees with the HMOs had their care delivered via managed care, all enrollees were under the management of Options since the carve out. This is a form of demand-side management. Second, Options set up a network of providers for enrollees. Before the carve out, providers negotiated individually with the GIC. After the carve out, Options, on behalf of the GIC, centralized all negotiations with providers. This affects the supply side. The first change may have the effect of reducing inappropriate use of MHSA services, since preadmission authorization, utilization review, and other monitoring may deter or screen out some demands for services. The centralization of bargaining makes Options a "monopsonist" buyer with market power, and enables it to use the size of the GIC population to secure a lower price from providers.
The above arguments suggest the following decomposition analysis. Consider any single type of service, say an outpatient visit. By definition, the total cost of this service in a given period of time is equal to the total number of times this service is used multiplied by the average price of each service. A reduction in total cost of this service can come about through a reduction in the quantity, the price, or both. From the claims data, we calculate the total number of outpatient visits for the periods before and after the carve out. Using the data of outpatient costs, we can estimate the average price per visit. For inpatient services, we calculate LOS of each episode and obtain the average LOS by dividing by the number of inpatient episodes. Using the inpatient costs data, we then estimate the average price per inpatient day. As it turns out, after the carve out, the claims data separated out from all inpatient services an additional class: inpatient service at an alternative setting. These are inpatient services performed at a less intensive setting such as residential facility, partial facility, intensive outpatient, residential professional and partial professional settings.
Table 5 and 6 present the decomposition of MHSA outpatient services and costs. For the continuously enrolled population, we estimate the prices per MHSA outpatient visit by dividing the total outpatient plan costs (after discarding outliers that may simply reflect adjustments to previous claims) by the total number of visits. We express the estimates both in terms of current year dollars and constant 1995 dollar. Table 5 shows an upward trend for MH outpatient prices, but a downward trend for SA. Nevertheless, we should note that the outpatient coverage of MH was significantly improved after the carve out; before the carve out, MH outpatient coverage was at 50% while SA at 80%. Table 6 presents the our own analysis and that from Options on number of admissions and average LOS per admission. While the data we received from MEDSTAT gave us numbers of admissions that were comparable to those Options reported, the total number of inpatient days were higher from our own analysis. Furthermore, we were unsuccessful in decomposing from our data total inpatient days into "conventional" and "alternative setting" inpatient services. Nevertheless, there is a slight decrease in the total of admissions as well as the ALOS in both analyses. From Table 5 suggests that the dramatic decrease in outpatient costs could be due to reduction in quantities, since "prices" either increased or remained relatively stable. On the other hand, Table 6 suggests that the reduction in inpatient plan costs mainly could be a result of price reduction, since numbers of admissions as well as ALOS did not decreaseas much as the total plan costs.
CONCLUSIONS
- The anticipated cost shifting from enrollees to the plan is offset by decrease in prices. Because of the improved MHSA coverage and benefits for enrollees, expenses for the plan should tend to increase. But in the GIC experience, this increase was more than compensated by the decrease in prices that GIC had to pay providers as well as by the effect of managed care quantities.
- Both outpatient and inpatient costs decrease. Despite the general view that managed care will tend to shift the demand for MHSA services from inpatient to outpatient, the GIC experience shows a mixed result. For mental health services, the decrease in outpatient costs between fiscal 92 and 95 was significantly less than inpatient, while these costs decreases were almost in the same percentage for substance abuse.
- Both MH and SA services decrease in quantity uniformly.
- The target level in the contract must be understood in relation to the penalty. That is, the entire schedule of ASO fees must be analyzed. Although there are penalties for failing to maintain the target, there is no a priori reason to expect that the target will be maintained. The vendor may optimally fail to maintain costs below target, incurring the penalty while avoiding administrative costs.
- In the case of the GIC MHSA carve out, the target level is related to the ratchet and reputation effects. We find that even when Options faces no financial gains from reducing costs below the target, in fact that was what happened. Meeting a target is insignificant when a contract is viewed in isolation, but may have repercussions when contract renewals and bidding for new contracts are considered part of a firm's incentive. As in many other industries, a good reputation is a very valuable asset to a firm. Our finding is consistent with the "long term" perspective of contracting. Whenever a carve out program requires the contracting out of the administrative and management duties of the deliveries of medical services, the long term effects of contracting must be considered.
NOTES
- For other examples, see Alexander Consulting Group (1990) on McDonnell Douglas; Altman and Price (1993) on Alcan; and Umland (1995).
- According to the contract, a PIP is a covered person who is an employee, a retired employee (of various classes), a covered student age 24 or over, an individual not part of a family unit covered under some continuation provision (see Appendix D of the Agreement for Managed Mental Health Services by and between Commonwealth of Massachusetts Group Insurance Commission and Options Incs. 1993). Thus, the total number of PIPs does not correspond to the total of all enrollees; rather each PIP roughly corresponds to a unique employee identification number in the enrollment records. In particular, spouses and most dependents are not PIPs.
- We actually selected these enrollees by identifying contracts with months of enrollment of 46 or greater of a possible 48.
- Some cost shifting between MHSA and general medical care is possible. For instance, inpatient treatment for alcohol abuse could be reclassified by a clinician as treatment for gastrointestinal problems and paid for under the general health insurance benefit. We are not in a position to evaluate how much of such cost shifting has occurred. For study of this in another context, see Norton et al. (1996).
- Active employees, retiree and survivors, and all groups.
- In many instances, potential vendors were asked to justify their projections, or to provide information on the basis of which those calculations were obtained.
- It is unclear whether any outside arbitration would be allowed.
- The benefit and enrollees' out-of-pocket payment designs for fiscal years 93-94 and 94-95 are identical.
- An implementation fee was also paid by the GIC in the first few months. This was calculated at $.35 per PIP per month.
- See Merrick (1996) for more discussion of the performance targets.
REFERENCES
Altman, L. And W. Price. "Alcan Aluminum: Development of a Mental Health 'Carve Out'." New Directions for Mental Health Services, Fall 1993, pp.55-65.
Alexander Consulting Group. "The Impact of the ASSIST Program During 1989 at the McDonnell Douglas Helicopter Company." Health Straties Group, May 1990, Westport, CT.
Battagliola, Monica. "Breaking with Tradition." Business and Health, June 1994, pp.53-56.
Frank, Richard G., Haiden A. Huskamp, Thomas G. McGuire, and Joseph P. Newhouse. "Some Economics of Mental Health Carve Outs." Archives of General Psychiatry, forthcoming, 1996.
Frank, Richard G. And Thomas G. McGuire. "Massachusetts Medicaid..." Psychiatric Services, forthcoming, 1996.
Frank, Richard G., Thomas G. McGuire, and Joseph P. Newhouse. "Risk Contracts in Managed Mental Health Care." Health Affairs, 1995, 14:3, pp.50-64.
General Insurance Commission, Commonwealth of Massachusetts. "Request for Proposal for Integrated Employee Assistance and Mental Health and Substance Abuse Program." October 16, 1992.
Grazier, K.L., R.M. Scheffler, S. Bender-Kitz, and P. Chase. "The Effect of Managed Mental Health Care on Use of Outpatient Mental Health Services in and Employed Population." In R.M. Scheffler and L.F. Rossiter, Advances in Health Economics and Health Services Research, 1993, Volume 14, pp.71-78, Greenwich, CT: JAI Press.
McGuire, Thomas G. Financing Psychotherapy: Costs Effects and Public Policy, 1981, Ballinger Publishing, Cambridge.
Merrick, Elizabeth. "Dissertation draft." 1996, Brandeis University.
Oss, Monica. "Managed Behavioral Health Market Shares in the United States." Open Minds, 1994, Gettysburg, PA.
Umland, Beth. "Behavioral Healthcare Benefit Strategies of Self-Insured Employers." Behavioral Healthcare Tomorrow, November/December 1995, pp.65-70.
| TABLE 1. Mental Health and Substance Abuse Costs | ||||
|---|---|---|---|---|
| Entire Set of Enrollees | FY 92 | FY 93 | FY 94 | FY 95 |
| Average monthly PIPs (92 is est) Average monthly enrolled |
69,440 101,373 |
69,212 101,012 |
81,571 128,496 |
81,062 127,486 |
| Total cost Total plan cost |
$22,345,087 $16,928,806 |
$20,001,460 $14,817,617 |
$12,429,902 $9,316,278 |
$9,710,747 $7,290,191 |
| Total cost per PIP per month Plan cost per PIP per month |
$26.82 $20.32 |
$24.08 $17.84 |
$12.70 $9.52 |
$9.98 $7.49 |
| Total cost per enrollee per month Plan cost per enrollee per month |
$18.37 $13.92 |
$16.50 $12.22 |
$8.06 $6.04 |
$6.35 $4.77 |
| TABLE 2. Mental Health and Substance Abuse Costs (adjusted for inflation, in 1995 $) | ||||
|---|---|---|---|---|
| Continuously Covered Enrollees | FY 92 | FY 93 | FY 94 | FY 95 |
| Average monthly PIPs Average monthly enrolled |
26,887 39,541 |
26,887 39,541 |
26,887 39,541 |
26,887 39,541 |
| Total cost Total plan cost |
$14,103,476 $10,455,369 |
$11,915,996 $8,467,091 |
$6,331,853 $4,601,074 |
$4,697,196 $3,898,639 |
| Total cost per PIP per month Plan cost per PIP per month |
$43.71 $32.41 |
$36.93 $26.24 |
$19.62 $14.26 |
$14.56 $12.08 |
| Total cost per enrollee per month Plan cost per enrollee per month |
$29,72 $22.03 |
$25.11 $17.84 |
$13.34 $9.70 |
$9.90 $8.22 |
| TABLE 3. Inpatient and Outpatient Costs | |||||
|---|---|---|---|---|---|
| Continuously Covered Enrollees | FY 92 | FY 93 | FY 94 | FY 95 | % Change |
| Total outpatient cost Plan outpatient cost |
$8,120,662 $4,577,179 |
$7,714,771 $4,394,690 |
$4,187,579 $2,647,443 |
$2,983,368 $2,068,618 |
0.55 0.47 |
| Total inpatient cost Plan inpatient cost |
$5,982,814 $5,878,191 |
$4,201,225 $4,072,402 |
$2,144,274 $1,953,631 |
$1,713,828 $1,830,021 |
0.62 0.62 |
| TABLE 4. Breakdown of Mental Health and Substance Abuse Costs | |||||
|---|---|---|---|---|---|
| Continuously Covered Enrollees | FY 92 | FY 93 | FY 94 | FY 95 | % Change |
| Plan total outpatient MH cost Plan total outpatient SA cost |
$4,291,262 $285,917 |
$4,056,528 $338,162 |
$2,547,510 $99,932 |
$1,835,488 $71,890 |
0.47 0.72 |
| Plan total inpatient MH cost Conventional inpatient MH Alternative level MH |
$4,689,307 | $3,246,222 | $1,605,253 $1,425,635 $173,575 |
$1,294,947 $1,112,972 $176,184 |
0.63 |
| Plan total inpatient SA cost Conventional inpatient SA Alernative level SA |
$1,188,883 | $826,180 | $332,671 $292,813 $39,740 |
$323,205 $276,173 $46,993 |
0.67 |
| NOTE: Inpatient MH, inpatient SA cost figures are from service claim file. | |||||
| TABLE 5. Price Estimates of Outpatient Mental Health and Substance Abuse | ||||
|---|---|---|---|---|
| Current Year Dollar | FY 92 | FY 93 | FY 94 | FY 95 |
| Continuous set: MH outpatient Continuous set: SA outpatient |
$40.29 $56.27 |
$42.68 $59.02 |
$54.23 $53.08 |
$52.95 $53.11 |
| Contant 1995 Dollar | FY 92 | FY 93 | FY 94 | FY 95 |
| Continuous set: MH outpatient Continuous set: SA outpatient |
$46.52 $64.98 |
$46.59 $64.43 |
$56.49 $55.29 |
$52.95 $53.11 |
| TABLE 6. Inpatient Quantity of Mental Health and Substance Abuse | ||||
|---|---|---|---|---|
| Data from MEDSTAT | FY 92 | FY 93 | FY 94 | FY 95 |
| Number of admissions Total number of days ALOS |
944 13,098 13.88 |
876 10,443 11.92 |
1,007 13,827 13.73 |
985 10,934 11.10 |
| Data from OPTIONS Annual Report | FY 92 | FY 93 | FY 94 | FY 95 |
| Number of admissions Total number of inpatient days Total number of alternative setting days Total number of days ALOS (counting only inpatient days) ALOS (counting all days) |
1,079 9,121 3,211 12,332 8.4 11.43 |
969 7,031 3,190 10,221 7.2 10.55 |
||
 |
 |
 |
Enrollment Duration, Service Use, and Costs of Care for Severely Mentally Ill Members of a Health Maintenance Organization
Bentson H. McFarland, M.D., Ph.D.; Richard E. Johnson, Ph.D.; and Mark C. Hornbrook, Ph.D.
Archives of General Psychiatry 53:938-944 (October 1996)
| Background: The rapid growth of prepaid health care and the increasing enrollment of Medicaid clients in health maintenance organizations (HMOs) raise concerns about the adequacy of services for persons with severe mental illness in capitated health plans. Uncontrolled studies have suggested that enrollment of HMO members with mental illness may be prematurely terminated.
Methods: We identified 250 adult Kaiser Permanente Northwest Region (Portland, OR) members who were enrolled during 1986 or 1987 and had chart diagnoses of schizophrenia or bipolar disorder. Severely mentally ill subjects were matched by age and sex with control HMO members with and without diabetes mellitus. Records of the HMO and the state mental health agency were reviewed to determine HMO enrollment duration, private and public service utilization, and HMO costs of care during the 4-year follow-up period. Results: The severely mentally ill subjects had 42 months of HMO enrollment during the follow-up period compared with 37 months for the controls without diabetes mellitus and 47 months for the patients with diabetes mellitus (P<.001). When HMO enrollment prior to the study was taken into account, the severely mentally ill subjects and those with diabetes mellitus had similar membership duration. Among the severely mentally ill subjects, community mental health service use was related to longer duration of HMO enrollment (P<.05) but HMO costs of care per member per month were not related to retention. The severely mentally ill subjects were high users of mental health services but their use of general medical care was similar to that of the controls without diabetes mellitus. Conclusions: This controlled study found no evidence for early termination of HMO members with costly mental illness. Use of community mental health care was associated with longer duration of HMO enrollment. |
The dramatic growth in health maintenance organization (HMO) enrollment has heightened concern about the adequacy of treatment available for persons with severe mental illness in prepaid systems.1, 2 This topic is of particular interest to the dozens of states3, 4 that are now in the process of replacing fee-for-service with capitated health care systems for Medicaid clients, many of whom have severe mental disorders.5 Indeed, Mechanic6 has suggested that public mental health programs should be gradually integrated into the larger, prepaid health care system while bearing in mind the many challenges involved.7 Conversely, Scheffler et al.8 have recommended that programs for persons with severe mental illness remain "carved out" of general health care. Furthermore, editorial writers have claimed that traditional HMOs "disenroll individuals who develop serious mental disorders"9 and have stated that "HMOs have routinely excluded any coverage of chronic mental illness."10 On the other hand, HMOs have also been described in which persons with severe mental illness "receive relative priority."11 Inconveniently, there have been few empirical data with which to inform this debate.1, 2
One of the few pertinent studies is the 1987 Minnesota project, which included a comparison of health status for chronically mentally ill Medicaid clients who had been randomized to fee-for-service vs prepaid (HMO) health care.2, 12, 13, 14 Unfortunately, the project ended prematurely after only a year of operation. Few if any differences were found for chronically mentally ill persons, although the subset of this group with schizophrenia may have been adversely affected by assignment to the independent practice association model HMOs that participated in the project.2, 14
Somewhat related to this issue is the RAND observational Medical Outcomes Study,15, 16 which raised the possibility that during 1986 through 1988 psychiatric patients with major depressive disorder in prepaid health care may have switched insurance coverage (i.e., terminated HMO enrollment) sooner than their counterparts in the fee-for-service sector. It was suggested that the limited mental health services provided to these subjects (referred to as HMO "skimping") may have contributed to their departure from the HMO.16, 17 However, the Medical Outcomes Study lacked a control group within the HMO.
To address these issues, we conducted a multiyear longitudinal cohort study of HMO members with severe mental illnesses such as schizophrenia or bipolar disorder. Based on the existing literature,9, 15 we hypothesized that the severely mentally ill HMO members would disenroll earlier than their lower-cost counterparts.9, 10 We also wished to learn if there was a relation between HMO members' use of public mental health services and their duration of enrollment.
METHODS
Study Site
The study was conducted in the Northwest Region of Kaiser Permanente, a nonprofit, prepaid, group-practice HMO that currently serves some 385000 members in greater Portland, OR. The HMO has been in operation for over 50 years, provides comprehensive medical benefits, and includes a specialty mental health department presently consisting of about 20 psychiatrists and 80 other mental health professionals.18 The HMO's mental health and substance abuse benefits conform to those mandated by Oregon law. Since 1987, Oregon insurers have been required to cover up to $2000 of outpatient and up to $8500 of inpatient, residential, or day treatment mental health and/or substance abuse services every 24 months for adult beneficiaries. The HMO allows substitution of inpatient for outpatient benefits. However, the total adult mental health and/or substance abuse benefit is a maximum of $10500 per 24 months. In addition, the vast majority of HMO members have a pharmacy benefit. A 1995 survey of the membership showed that 84% of enrollees obtain all of their prescriptions and 12% obtain some or most of their prescriptions (including those written by non-HMO clinicians) at the HMO's pharmacies. The HMO maintains a membership information processing system that records eligibility for services based on monthly premium payments. Administrative personnel attempt to contact individuals whose premiums are unpaid. For purposes of this study, disenrollment was defined to have occurred at the beginning of a 90-day or longer period of ineligibility. The project was reviewed and approved by the Kaiser Permanente Northwest Region Committee for the Protection of Human Subjects on February 16, 1995.
Selection of Subjects
The years 1986 and 1987 were chosen as a baseline period so that this project could be compared with earlier work.2, 12, 13, 14, 15, 16 Because the HMO's outpatient charts were not computerized at the time, severely mentally ill subjects were selected from the 2334 persons who received an antipsychotic drug (excluding prochlorperazine and thiethylperazine, which are used in the HMO only for treatment of nausea and vomiting) or lithium from an HMO pharmacy during 1986 or 1987; individuals in the original group who also received anticancer drugs or drugs used in the treatment of acquired immunodeficiency syndrome were excluded. To minimize the numbers of subjects who might have conditions such as Alzheimer disease, the study focused on the 733 potential subjects who were between ages 10 and 46 years in 1986. Of this group, 526 had mental health department charts (indicating they had had at least 1 contact with an HMO mental health specialist at some time). Individuals were then randomly selected from these 526 persons for mental health chart abstraction. Subjects who carried chart diagnoses of bipolar disorder (including mania, manic-depression, and hypomania) or schizophrenia (including schizophreniform disorder and schizoaffective disorder) in the mental health record were retained in the study. Mental health chart abstraction proceeded through 440 charts until 250 subjects meeting these inclusion criteria were located. Persons who were excluded at this stage typically had diagnoses of substance abuse (primarily amphetamines, cocaine, and/or alcohol) or psychotic depression. Since this study was designed to be descriptive in nature, the sample size of 250 was selected so that the SEs of the mean of annualized utilization estimates (measured in office visits per person per year) would be less than 10% of the estimated mean value. As in other record review projects, diagnoses were assigned based on the majority of those found in the subjects' mental health charts.19, 20 This group of subjects was labeled "cohort 1."
Control Members With and Without Diabetes Mellitus
The severely mentally ill subjects in cohort 1 were then matched with other HMO members. The "pharmacy" controls were taken from the population of HMO members who used the system's outpatient pharmacies during 1986 or 1987 (and had not received an antipsychotic drug or lithium). This group included some two-thirds of the HMO's membership. The "membership" controls were selected from the HMO's enrolled population during 1986 and 1987, which averaged about 290000 persons on any given day at that time. Subjects were matched for sex, year of birth, and "coverage status" (i.e., whether the subject was a subscriber or a dependent of the subscriber). For studies of the enrollment duration of cohort 1, the subjects were also matched for sex and year of birth (within 5 years) with 234 people selected from the 2140 individuals who were HMO members during 1986 or 1987 and who had been discharged by a general medical-surgical unit (in 1986 or 1987) with a diagnosis of diabetes mellitus.
Service Utilization
Cohort 1 subjects' HMO service utilization data were obtained from 1986 through 1990 record reviews and computerized databases. In addition, the names and dates of birth for all subjects without diabetes mellitus in cohort 1 were matched against state mental health agency computerized utilization data. The state agency provided information about subjects' use of community mental health programs and the state mental hospitals from 1986 through 1990. While there were extensive data on state hospital usage (including dates of admission and discharge, diagnoses, and so forth) the community mental health data were limited to enrolled vs not enrolled during particular time periods. The Chronic Disease Score21, 22 (based on nonpsychotropic drug dispensing) was used to gauge the severity of physical illnesses in subjects from cohort 1 without diabetes mellitus.
Costs
The HMO's accounting data and Medicare cost reports became available in 1987 and were used to calculate cost coefficients for each unit of service (e.g., outpatient visit to a provider, day in a medical-surgical unit, and so on). The cost coefficients were then multiplied by units of service for cohort 1 to determine the cost (in 1990 dollars) for each type of care.23, 24 Billing records were used to determine the costs (in 1990 dollars) of services purchased by the HMO (e.g., general hospital inpatient psychiatric care) for members of cohort 1. Public sector costs were not available.
Secular Trends in Enrollment Duration
To address possible secular trends in enrollment duration, a second group of severely mentally ill subjects (labeled "cohort 2") was chosen from the HMO members discharged from a general hospital during 1990 through 1992 with diagnoses of schizophrenia or bipolar disorder. These people were matched for age and sex with HMO controls with and without diabetes mellitus as described for cohort 1. The enrollment duration study focused on the 165 female and 116 male (average age, 31 years in 1990) severely mentally ill subjects in cohort 2 who were between the ages of 10 and 46 years at the time of the index hospital discharge, of whom there were 139 with a diagnosis of schizophrenia and 5 who also had a diagnosis of diabetes mellitus. Follow-up for cohort 2 started with the index hospital discharge and ended December 31, 1995.
Statistical Analysis
Service utilization and cost data for cohort 1 are reported on a per member per month of enrollment basis. In 2-way analyses of variance (ANOVA), data were transformed as needed so that the residuals were roughly normally distributed. For example, the total cost per person per month was transformed by adding 1 to the cost numerator, dividing by the months of enrollment denominator, and then taking the logarithm of that ratio. To account for multiple comparisons, the studentized range test was used to compare the cohort 1 severely mentally ill subjects' utilization and costs with those of the controls.25 Enrollment duration comparisons used the log-rank test and the Cox proportional hazards model stratified to account for the matching.26 Changes in coverage status (subscriber vs dependent) were examined using the Miettinen method.27
Cox proportional hazards models were used to examine factors associated with retention of cohort 1 severely mentally ill subjects in the HMO during the follow-up period from 1986 through 1990.26 Blocks of potential predictors were planned for stepwise inclusion in the proportional hazards models. These potential predictor variables were demographics (age, sex, schizophrenia vs bipolar disorder); enrollment status at the start of the study (subscriber vs dependent, Medicare vs no Medicare, Medicaid vs no Medicaid, years of HMO enrollment prior to the start of the study); and utilization (state hospital admission at any time while an HMO member during the study period, use of community mental health services while an HMO member at any time during the study period, total HMO costs of care per member per month, and HMO mental health costs of care per member per month).
RESULTS
Demographics
In cohort 1 there were equal numbers of males and females. Subjects in cohort 1 were (on average) 32 years old in 1986, with an age range from 13 to 45 years and an SD of 8 years. The ethnicity distribution was 80% white, 5% African American, 2% Asian American, 2% Hispanic, and 12% unknown. There were no differences in the distributions of know ethnicity between the severely mentally ill subjects and the controls. Some 30% of the 250 severely mentally ill persons in cohort 1 (for whom data were available) had never married. In contrast only 12% of the controls (for whom data were available) had never married. At the beginning of the study about half (53%) of the 750 subjects without diabetes in cohort 1 were subscribers, while 44% were dependents and the remaining few were nonmembers. Only 12% of the cohort 1 severely mentally ill subjects changed coverage status from dependent to subscriber during the 4-year follow-up period, compared with 22% of the controls without diabetes mellitus (relative risk, 0.53; 95% confidence interval, 0.30-0.92). The severely mentally ill subjects in cohort 1 were much more likely to have Medicare coverage than the controls without diabetes mellitus (10% vs 0.2%, P<.001 by Fisher exact test). There was no difference in the prevalence of Medicaid coverage (5% vs 4%).
The 250 severely mentally ill subjects in cohort 1 had lengthy histories of mental illness. At the time of their first HMO mental health department contact, the vast majority (73%) reported having had at least 1 previous psychiatric hospitalization, with 40% of severely mentally ill subjects reporting 3 or more admissions. Many (41%) were known to have been admitted to a state mental hospital in Oregon. The majority (57%) had had contact with the HMO's emergency psychiatric service at some time during their enrollment.
Diagnoses
The diagnostic algorithm showed that 79 (32%) of the 250 severely mentally ill subjects in cohort 1 had chart diagnoses of schizophrenia, 98 (39%) had bipolar disorder, and the remaining subjects had multiple diagnoses. As expected, 92% of the 98 persons with bipolar disorder had received prescriptions for lithium, while 93% of the 79 subjects with schizophrenia had been dispensed antipsychotic drugs. Some 30% of the bipolar subjects had received antipsychotic drugs as well as lithium.
Service Use
Health care utilization data for the 1986 through 1990 study period are presented in Table 1. Not surprisingly, the severely mentally ill HMO members utilized greater amounts of services than did the controls without diabetes mellitus. As expected, the severely mentally ill subjects had greater per member per month use of mental health [F(2498)=120.1, P<.001] and substance abuse outpatient services [F(2498)=6.5, P<.003] as well as greater use of general hospital psychiatric inpatient services [F(2498)=86.3, P<.001]. During the study period, 88 (35%) of the severely mentally ill subjects in cohort 1 had 274 general hospital psychiatric admissions while the pharmacy controls had none and the membership controls had 1.
Interestingly, there were no statistically significant differences among the 3 groups without diabetes mellitus in the per member per month use of general medical outpatient services. However, differences were observed with respect to use of general medical-surgical inpatient care [F(2498)=4.5, P=.01]. The studentized range test indicated that the severely mentally ill subjects' use of general medical-surgical inpatient care was equivalent to that of the pharmacy controls.
The Chronic Disease Score (based on pharmacy data other than psychotropic drugs for the 665 subjects without diabetes mellitus enrolled in 1986) showed that the severely mentally ill subjects had the highest score (mean=0.48, SD=1.18), followed by the pharmacy controls (mean=0.31, SD=0.92), who were in turn followed by the membership controls (mean=0.15, SD=0.65). These differences are highly statistically significant (2-way ANOVA F[2498]=7.9, P<.001). Because the Chronic Disease Score was not normally distributed, we also examined the percentage of each group with a nonzero score (47 [20%] of 231 severely mentally ill subjects, 34 [15%] of 225 pharmacy controls, and 16 [8%] of 209 membership controls). These frequency differences were also highly statistically significant (X2=14.3, df=2, P<.001).
During their HMO enrollment in the follow-up period, 30 (12%) of the severely mentally ill subjects in cohort 1 were admitted to a state mental hospital compared with 3 (1%) of the pharmacy controls and 1 (0.4%) of the membership controls (X2=48.5, df=2, P<.001). Similarly, 101 (41%) of the severely mentally ill subjects in cohort 1 used community mental health services during the follow-up period compared with 12 each (5%) among the pharmacy and membership controls (X2=152.7, df=2, P<.001).
Costs
Table 2 and Table 3 show the HMO costs of care per member per month for the subjects without diabetes mellitus in cohort 1. The vast majority (98% of the severely mentally ill subjects, 95% of the pharmacy controls, and 87% of the membership controls) incurred HMO costs. The severely mentally ill subjects had substantially higher HMO costs of care per member per month of enrollment than did the controls without diabetes mellitus. The average cost for the subjects with severe mental illness was $380 (median of $203) per member per month vs an average of $149 (median of $33) for the pharmacy controls and $90 (median of $23) for the membership control subjects [2-way ANOVA on the transformed total cost F(2419)=81.4, P<.001]. The studentized range test showed that the 3 groups were all statistically significantly different from one another at the P=.05 level.
Looking in more detail at costs per member per month for the severely mentally ill subjects showed that the median combined mental health cost (inpatient, outpatient, and pharmaceutical) was $99 with the median, excluding psychotropic pharmaceuticals, at $74. Median outpatient mental health cost was $48. The 90th percentile figures were $798 per member per month for total costs, $544 for all mental health costs, $492 for mental health costs excepting psychotropic medications, $284 for inpatient care, and $214 for outpatient mental health costs.
Enrollment Duration
The Kaplan-Meier product-limit estimates in the Figure show the retention of cohort 1 subjects in the HMO from the start of time under observation (in 1986 and 1987) until disenrollment or the end of follow-up on December 31, 1990. Mean enrollment duration for cohort 1 is shown in Table 4. The enrollment durations of the cohort 1 groups differ significantly (log-rank X2=40.7, df=3, P<.001). The stratified Cox model showed that the most powerful predictor of enrollment duration was not being in the membership control group (X2=25.1, df=1, P<.001), with the next most powerful predictor being years of HMO enrollment prior to entering the study (X2=17.8, df=1, P<.001). Once prior years of HMO enrollment had been taken into account, there were no statistically significant enrollment differences among those subjects with diabetes mellitus, severe mental illness, and pharmacy controls in cohort 1. Table 4 also shows that the enrollment duration of cohort 2 subjects was similar to that of cohort 1.
Retention
Among the severely mentally ill cohort 1 subjects, stepwise Cox proportional hazards modeling showed that the factors related to longer duration of enrollment in the HMO were years of HMO enrollment prior to the start of the study period (X2=7.6, df=1, P<.006); age (X2=5.6, df=1, P<.02); and community mental health service use (X2=3.9, df=1, P<.05).
Costs of care (total costs per member per month or mental health costs per member per month) for cohort 1 were not significantly related to retention based on the Cox proportional hazards modeling. Other factors not significantly related to cohort 1 enrollment duration in the proportional hazards models included sex, schizophrenia vs bipolar disorder, subscriber status, or use of the state hospital.
COMMENT
Results from this study need to be interpreted in light of its design. The project was not a randomized trial nor did it include a comparison group of subjects outside the HMO. Since the study was designed to take advantage of existing data, subjects were not interviewed and clinical outcomes were not measured. Consequently, there could well have been important but unrecorded differences among the groups. Furthermore, subjects' reasons for disenrollment and for use of public mental health services were not available.
The project examined "prevalent" cases of people with severe mental illness who were using HMO services. At the time of this study it was not possible to identify HMO members with newly emerging (i.e., "incident") psychosis. Certainly, the "careers" of severely mentally ill persons who do not receive treatment may well be different from those of the subjects described here. For example, persons who become psychotic and refuse HMO mental health services might be unable to maintain enrollment and quickly leave the organization. Indeed, earlier work has shown that the treated prevalence of schizophrenia within this HMO is less than what would be expected from Epidemiologic Catchment Area data, although the treated prevalence of bipolar disorder is comparable to the national estimate.18 Very recent improvements in the HMO's automated data systems may provide an opportunity to conduct an incidence study focusing on people with newly emerging psychosis.
Another issue is the degree of severity of the subjects' mental disorders. For example, some 67% of the cohort 1 severely mentally ill subjects were self-reported to be employed at the time of their first HMO mental health clinic visit. Interestingly, the Epidemiological Catchment Area project found that 43% of the persons identified in that study as having schizophrenia were employed.28 The severely mentally ill HMO members may be that subset of persons with conditions like schizophrenia, who have a relatively good prognosis.29, 30, 31, 32, 33, 34, 35, 36, 37
Nonetheless, the frequent use of emergency and inpatient psychiatric services for this population suggests that many of these individuals were, indeed, severely disabled. Furthermore, the Chronic Disease Score indicated that the severely mentally ill persons appeared to have had physical as well as mental health problems. These individuals were also much more likely to have Medicare coverage than the controls without diabetes mellitus. Presumably, the severely mentally ill subjects became eligible for Medicare coverage by virtue of qualifying for Social Security Disability Insurance due to their mental illness.38 The relatively low rate of Medicaid participation by the severely mentally ill subjects in cohort 1 may well have been due to state policies at the time of the study, which, in effect, deemed persons receiving Social Security Disability Insurance to be "too wealthy" for Medicaid.
Relatively few of the severely mentally ill subjects in cohort 1 (compared with the controls without diabetes mellitus) changed coverage status from dependent to subscriber during the 4-year follow-up period. One explanation for these findings is that the severely mentally ill subjects who entered the study as dependents were not as likely as their matched controls to obtain competitive employment (and thereby become subscribers in their own right). Indeed, naturalistic follow-up studies of patients with mania suggest that significant disability would be expected for at least some of those severely mentally ill HMO subjects who had bipolar disorder.39, 40
Its limitations notwithstanding, this study showed that HMO members with severe mental illness had enrollment duration longer than that of controls without diabetes mellitus but somewhat shorter than that of members with diabetes mellitus. Furthermore, costs to the HMO were unrelated to duration of enrollment. To the authors' knowledge, cohort 1 has been followed up longer than any group of mainstream managed care beneficiaries with severe mental illness. This study is also one of the few that measured both private and public mental health service use.13 In contrast to the Medical Outcomes Study,15, 16, 17 this project involved a variety of HMO control subjects.
It is worthwhile examining the factors that did and did not explain the severely mentally ill subjects' retention within the HMO. There was no support for the contention that HMO members were "disenrolled" due to severe mental illness.9 Of course, as expected in a "prevalence" study, subjects with very brief periods of enrollment were unlikely to be included in the sample. Consequently, length of HMO eligibility prior to the study was a good predictor of enrollment duration during follow-up. Indeed, when length of enrollment before the study period was included in the Cox proportional hazards analysis, the severely mentally ill subjects had retention times longer than the membership controls but equivalent to that of the diabetic subjects and the pharmacy controls.
We were also unable to find evidence that this HMO "routinely excluded any coverage of chronic mental illness."10 Indeed, the severely mentally ill subjects in cohort 1 were provided amounts of service that generated costs to the HMO several times that of the membership controls. This cost difference was accounted for chiefly by mental health care. Based on the HMO's cost data, it appears that 36% of the severely mentally ill subjects in cohort 1 exceeded the state-mandated outpatient mental health benefit of $2000 per 24 months. Psychiatric inpatient costs were generally less than the state-mandated $8500 per 24 months, but 9% of severely mentally ill cohort 1 subjects did exceed the benefit limit. Looking at combined inpatient and outpatient mental health costs showed that 12% of severely mentally ill cohort 1 subjects exceeded the $10500 per 24 months limit. Of course, one could challenge the accuracy of the cost data. However, it should be noted that some of the costs (e.g., general hospital inpatient psychiatric services) represent payments from the HMO to its vendors. In any event, it seems clear that coverage was provided to HMO members who were severely mentally ill. Furthermore, HMO costs were not related to enrollment duration.
An important issue is the HMO's policies toward serving persons with severe mental illness. As with many HMOs, this organization's mental health services were theoretically limited to treatment of conditions that, in the judgment of the attending physician, were subject to significant improvement through relatively short-term therapy.41 In practice, as demonstrated by these results, mental health services were provided to persons with chronic conditions. Since this approach to persons with severe mental illness may not be found in other HMOs, these results may have limited generalizability.42, 43, 44
Indeed, the distinctions among HMOs44 may explain the apparent discrepancy between the retention data from this project and the implication from the Medical Outcomes Study15 that severely mentally ill subjects would have a shorter enrollment than healthier members. It should be noted that the Medical Outcomes Study was conducted in several prepaid settings (including a traditional staff model HMO), with the poorest outcomes for depressed psychiatric patients observed in independent practice associations.17 Differences between the independent practice association approach to severe mental illness and that provided by traditional HMOs could be responsible for the disparate outcomes observed in the 2 studies. As Judith L. Feldman, MD, remarked: "When you've seen one HMO you've seen one HMO" (oral communication, 1988).
The integrated service delivery system provided by traditional HMOs may be of particular value for severely mentally ill members who have physical as well as mental health problems, as suggested by our data. It is interesting to note that the costs of general medical-surgical care for severely mentally ill subjects were similar to those of the pharmacy controls even though the Chronic Disease Score suggested that the former had more physical illness than the latter. An integrated system might be more efficient than a mental health "carve-out" for people with both physical and severe mental health problems. On the other hand, while the data from cohort 2 suggest that this HMO is continuing to serve severely mentally ill members, the now fiercely competitive health care environment45 makes one wonder if any HMO will be able to provide the level of mental health service described here.
It should be pointed out that the HMO was by no means the sole provider of mental health care to these individuals. Nearly half of the severely mentally ill subjects in cohort 1 also used community mental health services. Furthermore, the use of community mental health care was associated with longer duration of HMO enrollment. While this observational study cannot determine causality, it is conceivable that the subjects who maintained their HMO membership were also to optimize use of both private and public services. One might imagine that the HMO's expertise in areas such as psychopharmacology, emergency psychiatric services, and inpatient psychiatric care could complement the public mental health sector's capabilities in fields such as rehabilitation and vocational training. Unfortunately, shrinkage of public sector mental health funds combined with private sector competition may leave persons with severe mental illness struggling to find appropriate care.46 Nonetheless, there may be considerable value in studying ways HMOs and community mental health agencies can work together to offer an efficiently integrated package of services that will benefit people with severe mental illness.6
NOTES
From the Kaiser Permanente Center for Health Research (Drs McFarland, Johnson, and Hornbrook) and Oregon Health Sciences University (Dr. McFarland), Portland.
Accepted for publication June 21, 1996.
Supported in part by grants P50 MH43458, R01 MH45015, and K02 MH01238 from the National Institute of Mental Health, Bethesda, MD.
Presented in part at the 147th Annual Meeting of the American Psychiatric Association, Philadelphia, PA, May 25, 1994, and at the 123rd Annual Meeting of the American Public Health Association, San Diego, CA, November 1, 1995.
Reprints: Bentson H. McFarland, MD, PhD, Center for Health Research, Kaiser Permanente, Northwest Region, 3800 North Kaiser Center Drive, Portland, OR 97227.
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| TABLE 1. Service Utilization* Number (Percent) |
|||
|---|---|---|---|
| Service | Severely Mentally Ill Subjects (n=250) |
Pharmacy Controls (n=250) |
Membership Controls (n=250) |
| Inpatient Admissions - Medical-surgical - Psychiatry - State hospital |
11 (27) 31 (66) 6.1 (32) |
15 (48) 0 0.88 (11) |
5.9 (18) 0.096 (1.5) 0.068 (1.1) |
| Outpatient Visits - General medical - Mental health - Substance abuse |
770 (1010) 460 (560) 27 (110) |
770 (1130) 8.7 (46) 7.3 (64) |
610 (920) 18 (140) 4.9 (32) |
| Used Community Mental Health Program | 101 (40) | 12 (5) | 12 (5) |
| * Services per 1000 member-months of health maintenance organization enrollment. All data are presented as mean (SD) unless otherwise indicated. Data were collected from 1986 through 1990. | |||
| TABLE 2. Costs of Care, 1987 Through 1990 Number (Percent) |
|||
|---|---|---|---|
| Service | Mean (SD) Cost Per Member Per Month, 1990 $ | ||
| Severely Mentally Ill Subjects (n=225) |
Pharmacy Controls (n=223) |
Membership Controls (n=218) |
|
| Inpatient - Medical-surgical - Psychiatry - Substance abuse |
59 (182) 118 (317) 2 (12) |
77 (531) 0 0.1 (1) |
35 (147) 0.4 (6) 0 |
| Outpatient - General medical - Mental health - Substance abuse |
59 (69) 94 (138) 7 (32) |
55 (83) 4 (24) 2 (16) |
43 (67) 3 (19) 1 (8) |
| Pharmaceutical - General medical - Psychiatric - Substance abuse |
14 (25) 28 (39) 0.0004 (0.005) |
9 (19) 0.4 (2) 0.03 (0.4) |
6 (11) 1 (5) 0 |
| Total | 380 (473) | 149 (592) | 90 (194) |
| TABLE 3. Subjects With Nonzero Costs* Number (Percent) |
|||
|---|---|---|---|
| Service | Severely Mentally Ill Subjects (n=225) |
Pharmacy Controls (n=223) |
Membership Controls (n=218) |
| Inpatient - Medical-surgical - Psychiatry - Substance abuse |
76 (34) 88 (39) 4 (2) |
49 (22) 0 2 (1) |
34 (16) 1 (1) 0 |
| Outpatient - General medical - Mental health - Substance abuse |
212 (94) 192 (85) 36 (16) |
208 (93) 13 (6) 7 (3) |
183 (84) 17 (8) 8 (4) |
| Pharmaceutical - General medical - Psychiatric - Substance abuse |
205 (91) 205 (91) 1 (1) |
198 (89) 44 (20) 1 (1) |
159 (73) 35 (16) 0 |
| Total | 220 (98) | 212 (95) | 189 (87) |
| TABLE 4. Duration of Enrollment in Days* | ||
|---|---|---|
| Cohort 1 (1986-1990) |
Cohort 2 (1990-1995) |
|
| Subjects with diabetes mellitus Severely mentally ill subjects Pharmacy controls Membership controls |
1424 (39) 1263 (45) 1236 (45) 1023 (47) |
1437 (40) 1298 (48) --- --- |
| * Data from Kaplan-Meier survival distribution function. Data are given as mean (SE); ellipses indicate not applicable. | ||
 |
Managing the Care of Schizophrenia: Lessons From a 4-Year Massachusetts Medicaid Study
Barbara Dickey, Ph.D.; Sharon-Lise T. Normand, Ph.D.; Edward C. Norton, Ph.D.; Hocine Azeni, M.A.; William Fisher, Ph.D.; and Frederic Altaffer, Ph.D.
Archives of General Psychiatry 53:945-952 (October 1996)
| Background: In 1992, Massachusetts launched a statewide managed care plan for all Medicaid beneficiaries.
Methods: This retrospective, multiyear, cross-sectional study used administrative data from the Massachusetts Division of Medical Assistance and Department of Mental Health, consisting of claims for 16400 disabled adult patients insured by Medicaid in Massachusetts between July 1, 1990, and Jun 30, 1994. The main outcome measures include annual rates of hospitalization, emergency department utilization, and follow-up care 30 days after discharge; length of inpatient stay; and per-person inpatient and outpatient expenditures. Results: Between 1991 and 1994, the likelihood of an inpatient admission decreased from 29% to 24% and was accompanied by a slight reduction in length of stay (median number of bed-days per admission dropped by 3.3 days). There was a slight decrease in the number of patients who sought care in general hospital emergency department utilization. However, there was a small increase in the fraction of patients readmitted within 30 days of discharge. Medicaid and Department of Mental Health expenditures for mental health per treated beneficiary decreased slightly, from $11060 to $10640, during the 4-year study period. Conclusions: Although per-person expenditures dropped and most patient patterns of care remained the same, longer-term study is recommended to assess whether the trends can be maintained. |
The treatment of schizophrenia remains a major clinical challenge to health care providers.1 The behavioral problems and thought disorders that are characteristic of schizophrenia make management complex and expensive. For example, in the United States, even though slightly more than 1% of adults have the disorder, treatment expenditures account for more than 2.5% of all health care expenditures.2, 3 It is not unusual for those with schizophrenia to have disabilities that lead to loss of employment and private health insurance. When this occurs, government becomes the primary health care insurer. Almost two-thirds of all the expenditures for schizophrenia treatment come from federal, state, and local government sources.2
With so much government money at stake, it is not surprising that reforms are rapidly changing the provision of government services to the mentally ill. All but 6 states are pursuing managed care for Medicaid beneficiaries, including those with severe mental illness, such as schizophrenia. In some states, Medicaid managed care plans tap into existing health maintenance organization networks.4 In other states, Medicaid contracts with mental health managed behavioral care companies to provide administrative functions and direct beneficiaries to a local provider network.
There are 2 fundamental issues in the evaluation of managed care for the severely mentally ill. First, can managed care succeed in providing quality care to psychiatrically disabled patients, especially those diagnosed as having schizophrenia?5, 6, 7, 8 These individuals are at high risk for catastrophic psychiatric and medical care but seldom are able to navigate effectively within the health care system and often lack advocates on their behalf. Even though providers surveyed in Massachusetts have reported that quality has not been compromised,9 both critics and advocates would like to have more evidence before accepting this conclusion.
The second issue is whether managed care actually reduces costs of shifts costs onto families, other state agencies, or medical care providers. When there are strong financial incentives to reduce acute hospital admissions, managed care plans will be financially motivated to divert beneficiaries to the long-term care system run by the state mental health agency. Individuals with schizophrenia are likely to be eligible for both Medicaid benefits and a state-funded long-term care system of community and hospital-based services. Shifting costs to the state mental health agency may result in greater profits for managed care plans but may not improve continuity of care; moreover, the societal costs may be higher. To date, there are no studies of how the reduction in mental health expenditures for acute care might shift costs to long-term care.
Evaluations of managed care plans are in an early stage of development, and little descriptive information is available to provide benchmarks against which to compare different approaches to cost containment.10 Earlier reports 9, 11 of the Massachusetts plan studied only the first year after implementation. In addition, these studies were limited to claims for mental health treatment.
We developed a database on adult Medicaid beneficiaries with schizophrenia to examine access to care, use of services, and treatment costs associated with schizophrenia before and after the introduction of managed care. Because care for our disabled population is not limited to services reimbursed by Medicaid alone, the data are drawn from 2 state agencies: the Division of Medical Assistance (Medicaid) and the Department of Mental Health (DMH). Data cover 2 years of the plan after implementation and include nonpsychiatric medical care, pharmacy, transportation, and dental care. These additional data are important to include because they account for roughly 40% of the total expenditures. We also examined incident patients, those not treated for schizophrenia before managed care was introduced.
PATIENTS AND METHODS
The Massachusetts Managed Mental Health Program
In 1992, Massachusetts received a 1915b waiver from the Health Care Financing Administration. Under this plan, all beneficiaries were asked either to enroll in a local health maintenance organization or to select a Medicaid-approved primary care clinician. Virtually all psychiatrically disabled beneficiaries chose a primary care clinician. Medicaid contracted with a single proprietary vendor, Mental Health Management of America, a division of First Mental Health, Boston, MA, to management the provision of mental health benefits. The vendor had 4 specific cost-containment strategies: (1) negotiation of reimbursement rates with a network of providers who would be paid on a fee-for-service basis, (2) implementation of an aggressive utilization management plan, (3) development of community-based alternatives to hospitalization, and (4) collaboration with the DMH to fund emergency service teams to screen patients for appropriateness of inpatient admission, with a view toward diverting many of them to alternative treatment sites.
Under the terms of the contract with Medicaid, the vendor was required to make available to recipients all the mental health and substance abuse benefits: acute inpatient treatment, crisis stabilization, outpatient evaluation and treatment, psychiatric day treatment, residential detoxification, and methadone treatment. The vendor was directed to add diversionary services, including acute residential treatment programs, family stabilization teams, and partial hospitalization programs. The contract further specified that the vendor would be responsible for the centralized functions of utilization review, claims processing, systems support, and provider relations, and for decentralized regionally based case management and network management. The contract with the vendor excluded payment for long-term nursing home care, mental health services provided by the DMH, and any medical treatment or outpatient pharmacy. In addition, it did not include members of health maintenance organizations and those who had Medicaid as a second payer. Disabled beneficiaries were covered at a higher rate than other beneficiaries, and providers were reimbursed by the vendor on a fee-for-service basis.
Data Sources
We used administrative data obtained from Medicaid and the DMH. Together, these files provided information regarding patient sociodemographic status, reimbursed inpatient and outpatient care, discharge diagnoses, and timing of services.
Definition of Cross-Sectional Cohorts
We created 4 separate cohorts, 1 for each fiscal year of the study, that together described treatment spanning the period from July 1, 1990 (the start of fiscal year 1991) through June 30, 1994 (the end of fiscal year 1994). The members of each cohort consisted of all adult Massachusetts Medicaid beneficiaries, aged 18 to 64 years, who were disabled and treated, either as inpatients or outpatients, for schizophrenia (International Classification of Diseases, Ninth Revision, Clinical Modification, primary diagnostic code of 295) at least once during the fiscal year. The cross-sectional cohorts were created by assigning patients with a schizophrenia claim to the fiscal year in which the claim was submitted; for this reason, it was possible for patients to appear in more than 1 cohort.
With the use of the patient's unique Medicaid identification number, patient-level files for each fiscal year were constructed by identifying paid claims for all psychiatric and substance abuse care (claims with a primary diagnostic code of 290-315), medical care (claims with any primary diagnostic code excluding V codes and 290-315 or any claim with a mental health Current Procedure Terminology procedure code), and other services, such as pharmacy, transportation, and dental care. Finally, to ensure that we had a complete record of service use for each patient, we merged state hospital admissions from the DMH inpatient files with the administrative Medicaid information by means of unique patient identification numbers.
Sociodemographic and Comorbidity Data
We used Medicaid membership files to identify the date of birth, sex, race, and residence ZIP code for each patient in our study cohort. To measure the degree of substance abuse in our sample, we assumed that if a patient was ever diagnosed as a substance abuser (primary or secondary diagnostic International Classification of Diseases, Ninth Revision, Clinical Modification code of 291, 292, 303.00, 303.90, 304, or 305) in a given year, then the patient had a drug or other alcohol abuse problem in the given year.
Admission Type
During the study, the DMH had contracted with a few general hospitals for inpatient beds to replace some of the beds in state hospitals closed as part of a larger deinstitutionalization plan. Thus, DMH-funded admissions occurred in both state and general hospitals. To differentiate between beds funded by Medicaid and those funded by the DMH, we classified each mental health inpatient admission as either a DMH admission or a Medicaid admission. The admission policy for Medicaid recipients to a DMH bed required that beds be available to forensic patients and to patients with behavioral management requirements that could not be met in general hospital psychiatric units or in freestanding psychiatric facilities otherwise reimbursed by Medicaid.
Evaluation of Access to Care
We defined access to care in each year as the number of Medicaid beneficiaries with a primary diagnosis of schizophrenia who had at least 1 Medicaid-paid claim. We also examined the number of incident patients in each year. We classified a patient as incident if there was no mental health claim with a primary diagnosis of schizophrenia for the patient in the previous year(s). Because we did not have Medicaid data before 1991, we were unable to identify new patients in 1991 and consequently may also have overestimated the number of incident patients in the remaining years.
Mental Health Inpatient Utilization
We defined mental health inpatient utilization as hospital admissions with primary mental health discharge diagnoses corresponding to schizophrenia, or any other psychiatric and substance abuse disorder. Because we hypothesized that hospital admissions would drop as a result of the screening and diversion programs of the managed care plan, we examined the distribution of mental health inpatient admissions in each year. We also estimated the likelihood of having any mental health inpatient admission by the percentage of patients who had at least 1 such admission in a given year. Finally, for those patients who had at least 1 mental health inpatient admission in a given year, we examined the number of bed-days per admission.
Continuity of Care
To describe follow-up care after discharge, we first defined inpatient transfers as admissions to another hospital within 24 hours after a discharge and then linked information from the transfers to form a complete inpatient episode of care for each patient in our cohorts. We then categorized each discharge into 1 of 4 mutually exclusive categories: discharges for which there was no outpatient or inpatient contact within 30 days, discharges for which there was outpatient contact within 30 days, discharges resulting in rehospitalization within 30 days, and discharges for which both an outpatient contact and a rehospitalization within 30 days resulted. Outpatient contact included a visit to any hospital outpatient department or to a clinic; a visit to a physician office; or the provision of any 1 of a set of mental health services, such as psychological testing, case management, or day treatment.
Because we believed that, ideally, continuous patient care should be rendered from 1 provider, we also calculated the number of unique hospitals to which patients with more than 1 hospitalization were admitted. Finally, we estimated the distribution in each year of general hospital emergency department visits. We did not calculate the distribution for state hospitals because they do not have emergency departments.
Assessment of Expenditures
We derived costs for Medicaid services from the paid claims that indicated the amount reimbursed. Although we could not determine whether paid claims overestimated or underestimated the true cost of treatment, these costs represented public expenditures through this entitlement program. Because the DMH operates on a fixed budget and records only use of services, we estimated costs for inpatient care by means of the per diem for state hospitals calculated by the DMH. These estimated per diem costs are based on accounting costs, calculated by dividing total annual inpatient expenditures, including capital costs, by the number of actual patient bed-days in each facility annually. Hospital-specific per diem costs were used to estimate the episode costs for each person admitted to a DMH facility by multiplying the calculated per diem by the number of days in the episode.
Inpatient mental health expenditures (psychiatric or substance abuse care) were dichotomized into Medicaid and DMH admissions to examine the extent of cost shifting between these 2 government agencies. All inpatient expenses are clustered together so that room and board, ancillaries, and physician fees are included.
Outpatient mental health expenditures included hospital outpatient department or clinic services, physician services, and other mental health services provided in free-standing mental health agencies.
Non-mental health expenditures were composed of medical care, pharmacy, transportation, and dental care. Claims for the last 3 categories did not report diagnoses, and consequently we were unable to distinguish mental health--related from non-mental health--related expenditures.
We aggregated the inpatient and outpatient mental health expenditures and then added all categories for total expenditures. Within each category of expenditures we report the number and percentage of persons with any expenditures, the average expenditure per person with any expenditure, and the total expenditure. For inpatient care we also report expenditure per admission.
Statistical Analyses
We computed simple univariate summary statistics by year. For continuous-valued variables, we calculated sample means and SDs; we also constructed box plots12 to display the center and spread of the distributions of the observations. Inpatient utilization was stratified by admission type (DMH or Medicaid). All expenditure figures are reported in 1994 dollars by adjusting expenditures in 1991, 1992, and 1993 for inflation by means of the gross domestic product deflator.13
RESULTS
Description of the Cross-Sectional Cohorts
Between July 1, 1990, and June 30, 1994, we observed 16400 disabled adults who contributed a total of 32135 annual observations. Despite changes in the number of treated beneficiaries during the 4-year period, we found that the sociodemographic characteristics remained virtually unchanged (Table 1): approximately half the beneficiaries were female and the majority were white, with a mean age of 41 years. Eleven percent were ethnic or racial minorities. Comorbid substance abuse increased as a proportion of the total study population. This increase might be a coding artifact resulting from changes in diagnostic practice or an increased awareness of substance abuse. Reimbursement of the treatment of substance abuse received much attention from providers because of the emphasis placed by the managed care vendor on outpatient rather than inpatient detoxification. It is also possible, given increases in the level of alcohol and other drug dependence in the general population, that there is increasing substance abuse among many of these patients, and the increase is being documented by providers.
Access to Care
The number of Medicaid beneficiaries with schizophrenia being treated increased from 6614 in 1991 to 7541 in 1994 (Table 1). However, in 1993, the year managed care was introduced in Massachusetts, the number of treated beneficiaries increased by more than 3000 from the previous year. This 1993 increase occurred despite a decrease in the number of providers. The increase might be an epidemiological phenomenon, but the stable demographic characteristics suggest that is not the source of the increase. More likely, the increase can be attributed to the advocacy work of the mental health provider community and family members who wanted to ensure that those who met the eligibility criteria were actually enrolled in Medicaid. In fact, the incident patients in 1993 were more likely to be older, white, female, and substance abusers than new patients in the remaining years (Table 1). The most striking demographic change for new schizophrenia patients was the higher percentage, in all years, of substance abusers.
Mental Health Inpatient Utilization
The percentage of patients who had at least 1 inpatient admission dropped by 4 percentage points during the study period, from 29.8% in 1991 to 25.4% in 1994 (Table 2). The decrease in the likelihood of a mental health admission during the study period was larger for DMH admissions than for Medicaid admissions (Table 2). Even though the probability of an admission decreased, the total number of DMH admissions remained almost the same in all 4 years. Medicaid admissions dropped 65% in 1993 but returned to the pre-managed care level by 1994. For those admitted, the median number of bed-days per admission decreased by about 3.3 days; there was a drop of 2.5 days for Medicaid admissions and of 3 days for DMH admissions (Figure 1).
Continuity of Care
We found little evidence of change in continuity of care. Rapid readmissions were up slightly, from 22.1% in 1991 to 24.2% in 1994 (Table 3), but there was essentially no change in the absence of outpatient follow-up contact, with the proportion of discharges without any follow-up contact remaining at 29%. (We were unable to identify in these data follow-up that may have occurred through DMH-funded community support services.) For patients with multiple admissions, there was an increase in the percentage who were admitted to more than 1 hospital (Table 3) but no increase in the percentage of patients who used emergency departments.
Mental Health Expenditures
Inpatient
Medicaid inpatient expenditures dropped dramatically in 1993, in the first year of managed care, but rose the following year (Table 4). The savings in Medicaid inpatient expenditures were largely offset, however, by increased expenditures on DMH hospital admissions. The annual Medicaid per-inpatient costs dropped below pre-managed care levels, while DMH per-inpatient costs were higher after implementation of the managed care program.
Outpatient
Both total expenditures and pre-treated beneficiary expenditures rose from their pre-managed care levels. The large increase in the number of beneficiaries in 1993 led to a dip in per-treated outpatient expenditures, but by 1994 this effect had disappeared. Given the large reductions in inpatient treatment, it was expected that outpatient treatment would expand, although these increases suggest only a modest cost shifting from inpatient to out-patient treatment.
Non-Mental Health Expenditures
Total expenditures of inpatient and outpatient medical and surgical care rose with the influx of new beneficiaries in 1993 (and then dropped as the number declined in 1994), but the per-person treated costs were about the same across all 4 study years. These data do not provide evidence that mental health treatment was shifted to the non-mental health sector. Other non-mental health expenditures include transportation and dental costs, which remained essentially the same during the study period. Pharmacy costs doubled both in total expenditures and per person treated.
Total Expenditures
The total Medicaid and DMH expenditures for mental health per treated beneficiary fell slightly from $11090 to $10600 during the 4-year study period. When all other Medicaid reimbursed care is added to mental health care, there is a slight increase in the total per-person expenditures (Table 4). The total dollar expenditures fluctuated with the number of treated beneficiaries across the study years, but it was decreasing, not increasing, at the end of the study period. The total Medicaid and DMH dollar expenditure for mental health care after managed care reversed the upward trend and stabilized at about $80 million in 1993 and 1994 (Figure 2).
COMMENT
Using a unique database of patient-level mental health treatments constructed from 2 sources, Medicaid and the DMH, we found that managed care was associated with some gains in continuity of care but a slight increase in rapid readmissions. Furthermore, there were reductions in mental health expenditures at the per-person level, primarily because fewer inpatient bed-days were reimbursed by Medicaid. The use of DMH inpatient beds for these beneficiaries remained about the same. Total mental health expenditures during the 4-year study period were contained, despite a growth in the number of treated beneficiaries.
There are several general conclusions from this study. First, because our measures of access and continuity of care are based on administrative data, they are limited in their scope and sensitivity. Furthermore, we have no way of knowing whether the pre-managed care levels were appropriate. Finally, for those with chronic illnesses, examination of short-term results is not an adequate indicator of the value of managed care. Information regarding the appropriateness of processes of care, such as the adequacy of discharge planning, or knowledge regarding patient well-being is crucial in judging the adequacy of quality. Because there is no clear evidence about the effectiveness of managed care plans to provide services needed by the most seriously mentally ill, we believe that continued research is essential to document the benefits or risks to clients.
Second, although we established that there were cost savings under managed care, we cannot be certain of the actual magnitude of the savings. Our assessment before and after managed care allows only 2 types of comparisons. The first type simply focuses on levels and directions of trends observed before and after implementation. The second approach compares observed postintervention levels with the levels that would have been expected in the absence of the intervention.14 From the perspective of the first approach, the vendor appears to have achieved a net reduction in expenditures and service use. The reduction in Medicaid inpatient expenditures was a function of 3 factors: the negotiated rates with the network hospitals, the reduced number of admissions, and the reduction in the total number of bed-days.
Third, the introduction of this managed care plan resulted in an unanticipated increase in the number of beneficiaries treated for schizophrenia. In this study we observed an increase in additional patients in 1993 who had a profound effect on the system, at least in the first year. The increase in treated patients in 1993, which shrank in 1994, tells us less about access to care and more about diagnostic variability in mental health. Rather than roughly 3000 members losing their coverage, as it appears, we found that they remained enrolled and were being treated for other mental illnesses. The marked increase in the number of beneficiaries in 1993 is real, regardless of diagnostic category. However, it creates a denominator problem: comparing percentages across years may be misleading, and per-person mean costs may be lower because individuals who need less intensive treatment are added to the membership. For example, the proportion of treated beneficiaries who had 1 or more admissions to a DMH inpatient bed during a year appears to drop from 15% to 10%, but the actual number of admissions did not change. This suggests that many of the new patients were among those less seriously ill. Trends such as these have been exhibited in a range of evaluations in a number of divergent fields.15, 16 Their ubiquitous character suggests the need for caution on the part of administrators and providers who would attempt to learn in the first few months after implementation what the ultimate effects of managed care will be on savings or service use.
Our final conclusion relates to cost shifting. We did find some evidence of cost shifting in this study. For example, one striking finding is the doubling of pharmacy costs. The increases in pharmacy costs observed might raise concern that psychosocial treatments are too often replaced by pharmacological interventions, but what seems more likely is that pharmaceutical costs have risen, especially for patients who are taking newer antipsychotic medications. Additionally, the growth in medical expenditures might signal cost shifting to that sector, and the fact that per-person medical care costs increase slightly might signal such a shift. The growth in medical expenditures are important because they compose about a third of all the health care dollars spent by Medicaid and the DMH on treatment for those with schizophrenia.
This report must be considered carefully in the light of its limitations. The mental health environment in Massachusetts at the time of this study was in transition. Reforms that are a response to fiscal and social problems are rarely unidimensional. In Massachusetts, prepaid managed care was only 1 aspect of a more global effort to privatize the Massachusetts mental health service system in the early 1990s. This effort entailed the closing of 3 state hospitals and the expansion of community-based services provided by vendors under contract to the DMH. The current study design does not rule out secular trends.
Although this study raises many questions, it also provides preliminary findings about the relationship of managed care with service use and with expenditures for seriously mental ill adults with schizophrenia. Future studies of managed care will need to continue to explore the trade-off between quality of care and costs, cost shifting between government agencies, and the difference between short-term and long-term effects.
From the Departments of Psychiatry (Dr. Dickey) and Health Care Policy (Dr. Normand), Harvard Medical School, Boston, MA; Mental Health Services Research, McLean Hospital, Belmont, MA (Dr. Dickey and Mr. Azeni); Department of Biostatistics, Harvard School of Public Health, Boston (Dr. Normand); Center for Economics Research, Research Triangle Institute, Research Triangle Park, NC (Dr. Norton); Center for Psychosocial and Forensic Services Research, University of Massachusetts Medical School, Worcester (Dr. Fisher); and Mentor, Inc., Boston (Dr. Altaffer).
NOTES
Accepted for publication June 21, 1996.
This research was supported by grant RO1-MH54076 from the National Institute of Mental Health, Rockville, MD.
We thank the Massachusetts Department of Mental Health and the Division of Medical Assistance for providing data and technical support. Thanks also to Richard Lindrooth, Research Triangle Institute, Research Triangle Park, NC, for providing technical assistance.
Reprints: Barbara Dickey, Ph.D., McLean Hospital, Administrative Building, 115 Mill Street, Belmont, MA 02178-9106.
REFERENCES
- Lehman, A.F., W.T. Carpenter, H.H. Goldman, and D.M. Steinwalchs. "Treatment Outcomes in Schizophrenia: Implications for Practice, Policy, and Research." Schizophr Bull, 1995; 21:669-675.
- Rupp A., and S.J. Keith. "The Costs of Schizophrenia." Psychiatr Clin North Am, 1993; 16:413-423.
- Regier, D.A., W.E. Narrow, D.S. Rae, R.W. Manderscheid, B.Z. Locke, and F.K. Goodwin. "The De Facto US Mental and Addictive Disorders Service System." Arch Gen Psychiatry, 1993; 50:85-94.
- Hurley, R.E., D.A. Freund, and J.E. Paul. Managed Care in Medicaid: Lessons for Policy and Program Design. Ann Arbor, MI: Health Administration Press; 1993.
- Sharfstein, S.S. "Utilization Management: Managed or Mangled Psychiatric Care?" Am J Psychiatry, 1990; 147:965-966.
- Tischler, G.L. "Utilization Management of Mental Health Services by Private Third Parties." Am J Psychiatry, 1990; 147:967-973.
- Schlesinger, M. "On the Limits of Expanding Health Care Reform: Chronic Care in Prepaid Settings." Milbank Q, 1986; 64:189-215.
- Schlesinger, M. "Striking a Balance: Capitation, the Mentally Ill,and Public Policy." In: D. Mechanic and L.H. Aiken, eds. Paying for Services: Promises and Pitfalls of Capitation, New Directions for Mental Health Services. San Francisco, CA: Jossey-Bass, Inc.; 1989; 43:91-115.
- Callahan, J.J., D.S. Shepard, R.H. Beinecke, M.J. Larson, and C. Cavanaugh. Evaluation of the Massachusetts Medicaid Mental Health/Substance Abuse Program. Waltham, MA: Brandeis University; January 1994.
- Wells, K.B., B.M. Astrchan, G.L. Tischler, and J. Unutzer. "Issues and Approaches in Evaluating Managed Mental Health Care." Milbank Q, 1995; 73:57-75.
- Dickey, B., E.C. Norton, S.L. Normand, H. Azeni, W. Fisher, and F. Altaffer. "Massachusetts Medicaid Managed Health Care Reform: Treatment for the Psychiatrically Disabled." Adv Health Econ, 1995; 15:99-116.
- Statistical Sciences Inc. S-PLUS: User's Manual. Seattle: WA:Statistical Sciences, Inc., 1991; 1:5-51.
- U.S. Department of Commerce. Survey of Current Business. Washington, DC: U.S. Department of Commerce, 1995.
- Cook, T.D., and C.T. Campbell. Quasi-Experimentation: Design and Analysis for Field Settings. Chicago, IL: Rand McNally, 1979.
- Rossi, P.H., and H.E. Freeman. Evaluation: A Systematic Approach. 5th ed. Newbury Park, CA: Sage Publications, 1993.
- McCleary, R., and R.A. Hay. Applied Time Series Analysis for the Social Sciences. Beverly Hills, CA: Sage Publications: 1980.
| TABLE 1. Demographic Characteristics of Cross-Sectional Cohorts* | |||||||
|---|---|---|---|---|---|---|---|
| All Patients, No. (%) | Incident Patients, No. (%) | ||||||
| FY 1991 (N=6614)‡ |
FY 1992 (N=7295)‡ |
FY 1993† (N=10685)‡ |
FY 1994† (N=7541)‡ |
FY 1992 (N=2528)§ |
FY 1993 (N=5484)§ |
FY 1994 (N=1774)§ |
|
| Age, y - 18-21 - 22-39 - 40-64 - Mean±SD |
172 (2.6) 3234 (48.9) 3208 (48.5) 41±12 |
184 (2.5) 3503 (48.0) 3608 (49.5) 41±12 |
331 (3.1) 4843 (45.3) 5511 (51.6) 41±12 |
179 (2.4) 3538 (46.9) 3824 (50.7) 41±11 |
118 (4.7) 1302 (51.5) 1108 (43.8) 39±12 |
246 (4.5) 2480 (45.2) 2758 (50.3) 40±12 |
104 (5.9) 934 (52.6) 736 (41.5) 38±11 |
| Female | 3182 (48.1) | 3486 (47.8) | 5808 (54.4) | 3470 (46.0) | 1201 (47.5) | 3291 (60.0) | 764 (43.1) |
| Race - African American - American Indian - Asian American - Hispanic - White - Unknown |
618 (9.3) 3 (0.0) 19 (0.3) 86 (1.3) 5865 (88.7) 23 (0.3) |
699 (9.6) 3 (0.0) 25 (0.3) 125 (1.7) 6413 (87.9) 30 (0.4) |
891 (8.3) 9 (0.1) 28 (0.3) 188 (1.8) 9537 (89.3) 32 (0.3) |
772 (10.2) 4 (0.1) 22 (0.3) 102 (1.4) 6464 (85.7) 177 (2.3) |
260 (10.3) 1 (0.0) 14 (0.6) 76 (3.0) 2164 (85.6) 13 (0.5) |
430 (7.8) 5 (0.1) 15 (0.3) 126 (2.3) 4891 (89.2) 17 (0.3) |
187 (10.5) 0 (0.0) 12 (0.7) 38 (2.1) 1377 (77.6) 160 (9.0) |
| Substance Abuse | 636 (9.6) | 775 (10.6) | 3108 (29.1) | 1023 (13.6) | 355 (14.0) | 1875 (34.2) | 324 (18.3) |
| * Patients are disabled Massachusetts Medicaid beneficiaries treated for schizophrenia. FY indicates Fiscal Year. † Managed care plan years. ‡ Number of treated beneficiaries § Number of new treated beneficiaries. |
|||||||
| TABLE 2. Mental Health Inpatient Utilization* for Disabled Patients With Schizophrenia | ||||
|---|---|---|---|---|
| FY 1991 | FY 1992 | FY 1993† | FY 1994† | |
| No. of treated beneficiaries | 6614 | 7295 | 10685 | 7541 |
| Total No. of admissions | 3937 | 4624 | 2486 | 3870 |
| Distribution of hospital admissions, No. (%)‡ - 0 - 1 - 2 - 3 - 4 - >5 |
4690 (70.9) 991 (15.0) 459 (6.9) 198 (3.0) 125 (1.9) 151 (2.3) |
5120 (70.2) 1120 (15.4) 471 (6.5) 252 (3.5) 148 (2.0) 184 (2.5 |
9146 (85.6) 1001 (9.4) 318 (3.0) 114 (1.1) 58 (0.5) 48 (0.4) |
5623 (74.6) 1085 (14.4) 388 (5.1) 202 (2.7) 108 (1.4) 135 (1.8) |
| >1 inpatient admission, No. (%)‡ - All admissions - DMH admissions - Medicaid admissions |
1924 (29.1) 1082 (16.4) 1170 (17.1) |
2175 (29.8) 1098 (15.1) 1466 (20.1) |
1539 (14.4) 1038 (9.7) 608 (5.7) |
1918 (25.4) 915 (12.1) 1232 (16.3) |
| * Hospital admissions for treatment of mental illnesses or substance abuse. † Managed care plan years. ‡ Percentage was calculated with number of treated beneficiaries used as the denominator. FY indicates fiscal year; DMH, Department of Mental Health. |
||||
| TABLE 3. Continuity of Care for Disabled Patients With Schizophrenia* | ||||
|---|---|---|---|---|
| No. (%) | ||||
| FY 1991 | FY 1992 | FY 1993† | FY 1994† | |
| Follow-up care within 30 d of a discharge - None - Outpatient contact - Rehospitalization - Rehospitalization and outpatient contact - Total No. of Discharges |
1077 (29.2) 1797 (48.7) 142 (3.8) 677 (18.3) 3693 (100.0) |
1199 (27.3) 2178 (49.7) 127 (2.9) 880 (20.1) 4384 (100.0) |
932 (38.0) 1159 (47.2) 124 (5.1) 238 (9.7) 2453 (100.0) |
1117 (29.7) 1729 (46.0) 215 (5.7) 696 (18.5) 3757 (100.0) |
| Distribution of unique hospitals‡ - 1 hospital - 2 hospitals - 3 hospitals - 4 hospitals - >5 hospitals - Total No. of Patients With 2 Hospitalizations |
361 (38.7) 364 (39.0) 145 (15.5) 42 (4.5) 21 (2.3) 933 (100.0) |
342 (32.4) 431 (40.9) 171 (16.2) 71 (6.7) 40 (3.8) 1055 (100.0) |
227 (42.2) 213 (39.6) 64 (11.9) 24 (4.5) 10 (1.9) 538 (100.0) |
298 (35.8) 381 (45.7) 113 (13.6) 29 (3.5) 12 (1.4) 833 (100.0) |
| Emergency department visits - 0 - 1 - 2 - 3 - 4 - >5 - Total |
5626 (85.1) 545 (8.2) 192 (2.9) 92 (1.4) 44 (0.7) 115 (1.7) 6614 (100.0) |
6219 (85.3) 577 (7.9) 221 (3.0) 97 (1.3) 69 (0.9) 112 (1.5) 7295 (100.0) |
9894 (92.6) 562 (5.3) 140 (1.3) 44 (0.4) 22 (0.2) 23 (0.2) 10585 (100.0) |
6653 (88.2) 435 (5.8) 210 (2.8) 82 (1.1) 43 (0.6) 118 (1.6) 7541 (100.0) |
| * FY indicates fiscal year. † Managed care plan years. ‡ Distribution of patients with 2 or more hospitalizations categorized by the number of unique hospitals to which they were admitted during the fiscal year. In FY 1991, 38.7% of the 933 patients who had at least 2 hospitalizations went to a single hospital, 39.0% were admitted to 2 distinct hospitals, 15.5% were admitted to 3 distinct hospitals, 4.5% were admitted to 4 distinct hospitals, and the remainder (2.3%) were admitted to 5 or more distinct hospitals. |
||||
| TABLE 4. Annual Expenditures for Disabled Patients With Schizophrenia* | ||||
|---|---|---|---|---|
| FY 1991 | FY 1992 | FY 1993† | FY 1994† | |
| Mental Health Expenditures‡ | ||||
| Medicaid mental health inpatient admissions - No. of inpatients - Average annual expenditure per inpatient, $ - Total annual expenditure, x$1000 |
1170 16916 19791 |
1466 17722 25980 |
608 10205 6205 |
1232 13673 16845 |
| DMH mental health inpatient admissions - No. of DMH inpatients - Average annual expenditure per DMH inpatient, $ - Total annual expenditure, x$1000 |
1082 40323 43629 |
1098 44773 49161 |
1038 57898 60098 |
915 54997 50322 |
| Outpatient mental health care - No. who are outpatients - Average annual expenditure per recipient, $ - Total annual expenditure, x$1000 |
6517 1525 9938 |
7191 1574 11319 |
10695 1246 13108 |
7541 1752 12774 |
| Non-Mental Health Expenditures | ||||
| Inpatient or outpatient non-mental health care - No. who received non-mental health care - Average annual expenditure per recipient, $ - Total annual expenditure, x$1000 |
5736 6478 37157 |
6386 7389 47054 |
9541 6928 66102 |
6325 7672 48527 |
| Pharmacy - No. who use pharmacy - Average annual expenditure per recipient, $ - Total annual expenditure, x$1000 |
6239 897 5598 |
6964 1087 7573 |
10142 1331 13503 |
6980 1634 11407 |
| Transportation or dental care - No. who use transportation or dental care - Average annual expenditure per recipient, $ - Total annual expenditure, x$1000 |
3896 425 1654 |
4115 450 1852 |
6521 441 2875 |
4225 441 1865 |
| Total Expenditures | ||||
| No. of patients Average annual expenditure per patient, $ Total annual expenditure, x$1000 |
6614 17806 117767 |
7295 19594 142940 |
10685 15151 161891 |
7541 18796 141740 |
| * FY indicates fiscal year; DMH, Department of Mental Health. † Managed care plan years. ‡ All expenditures have been converted to 1994 dollars by means of the gross domestic product deflator. The cumulative inflation rates from 1991 until 1994 were 7.1%, 4..1%, and 2.1% respectively. |
||||
 |
 |
Session 3: Impact of Managed Care on Adults with AIDS or Physical Disabilities
Reactor Biographies
Gerbon DeJong, Ph.D.
Gerben DeJong is the Director of the National Rehabilitation Hospital Research Center (NRH-RC) and the Director of the Research and Training Center in Medical Rehabilitation and Health Policy (RTC-MR&HP) in Washington, DC. He also serves as a Professor in the Department of Family Medicine at Georgetown University's School of Medicine. Prior to coming to NRH in 1985, Dr. DeJong was a Senior Research Associate and Associate Professor in the Department of Rehabilitation Medicine at Tufts University School of Medicine in Boston, MA. Dr. DeJong's academic training is in economics and public policy studies. His main research interests are in disability and health outcomes, health care utilization, disability policy, long-term care policy, national health care policy, and biomedical ethics. He is the author or co-author of more than 140 papers on health, income maintenance, and disability issues. He is perhaps best known for his seminal work on disability and health policy and the independent living movement. His works have appeared in a variety of health, science, business, and public policy journals. His works have appeared in more than seven different languages. In 1985, he received the Licht Award for Excellence in Scientific Writing from the American Congress of Rehabilitation Medicine. He is a frequently invited speaker both in the United States and abroad. In 1984, he was a Fulbright Scholar in the Netherlands serving with the research staff of the Social Security Council.
Dr. DeJong is an ardent student of health care reform and the managed care revolution. He is especially interested in managed care's probable impact on medical rehabilitation, on people with disabilities, and on other vulnerable populations. During the Clinton transition, Dr. DeJong served on the Transition Team's working group on long-term care policy. During the health care reform debate in the 103rd Congress, he spoke throughout the country on health care reform. He continues to testify before Congress on health care and disability income issues. In 1993, Dr. DeJong presented the honorary Coulter Lecture to the American Congress of Rehabilitation Medicine on the topic of "Health Care Reform and Disability." In 1994, he gave the keynote address to the National Brain Injury Association's annual meetings on the future of health care reform and brain injury. In 1995, Dr. DeJong presented the honorary John W. Goldschmidt Lecture at NRH on "Empowering the Consumer and Enabling the Provider in an Era of Managed Care."
Tony Dreyfus
Tony Dreyfus joined the Medicaid Working Group in 1993 to work on rate setting, casemix adjustment and Medicare waiver issues. The Group was organized with funds from Pew and Robert Wood Johnson to assist in the creation of managed care programs for Medicaid recipients with significant disability or chronic illness in Wisconsin, Ohio, Missouri and New York.
Mr. Dreyfus has been working in the past year with Richard Kronick, also of the Medicaid Working Group, on the development of a diagnosis-based risk adjustment system for people with disabilities. Mr. Dreyfus works part-time with the Community Medical Alliance, a managed care program for Medicaid recipients with late-stage AIDS or severe physical disability.
Co-authored articles include "Making Risk Adjustment Work for Everyone" (Inquiry), "The Community Medical Alliance: an Integrated System of Care in Greater Boston for People with Severe Disability or AIDS" (Managed Care Quarterly), and "Diagnostic Risk Adjustment for Medicaid: the Disability Payment System" (Health Care Financing Review).
Mr. Dreyfus earned his master's degree in planning at MIT and has worked in economic analysis, teacher training and curriculum development, elder homecare, and in a group home for men with mental retardation.
Lex Frieden
Lex Frieden is Senior Vice President at The Institute for Rehabilitation and Research (TIRR) in Houston, TX. TIRR is a comprehensive medical rehabilitation center which provides clinical, educational, and research programs pertaining to spinal cord and brain injuries and other disabling conditions. He is also Professor of Physical Medicine and Rehabilitation at Baylor College of Medicine.
From 1984-1988, Mr. Frieden served as Executive Director of the National Council on the Handicapped (now the National Council on Disability), an independent Federal agency located in Washington, DC. In this capacity, he was instrumental in conceiving and drafting the recently enacted Americans with Disabilities Act (ADA).
A graduate of Tulsa University, Mr. Frieden has been honored as a Distinguished Alumnus. He also holds a master's degree in social psychology from the University of Houston. He has done additional graduate work in rehabilitation psychology at the University of Houston with support from an SRS doctoral fellowship, and he has been awarded a World Rehabilitation Fund Fellowship to study programs for disabled people in Europe. Currently, he is Deputy Vice President for North America of Rehabilitation International.
Mr. Frieden, a quadriplegic due to a spinal cord injury, has been involved in the organization of several groups of disabled individuals including the American Coalition of Citizens with Disabilities, the Coalition of Texans with Disabilities, and the Houston Coalition for Barrier Free Living.
Working in the independent living movement by severely disabled people since the early 1970s, Mr. Frieden has published several books and papers on independent living. He served as a consultant panel member for the United States House of Representatives' Committee on Science and Technology from 1976-1978, and he prepared the background paper on "Community and Residential Based Housing" for the White House Conference on Handicapped Individuals in 1977. From 1989-1990, he represented the United States on a disability and employment panel at the Organization for Economic Cooperation and Development in Paris, France.
He has received two Presidential Citations for his work in the field of disability, and he was honored by the U.S. Jaycees in 1983 as one of America's Ten Outstanding Young Men.
Access, Use, and Satisfaction of the Under 65 Medicare-Disabled in HMOs and Fee-for-Service
Leonard Gruenberg, Ph.D.
Leonard Gruenberg is the President and founder of DataChron Health Systems, Inc. Dr. Gruenberg received his doctoral degree in theoretical physics from Columbia University, and has worked for more than 20 years as a Researcher and Consultant in the field of applied health services research. His primary research focus has been associated with financing of health services for elderly and disabled populations. He has developed payment models for managed care programs for elderly and disabled populations that are being used by the Health Care Financing Administration in demonstration programs including the SHMO, PACE, and CNO projects.
Prior to establishing DataChron, Dr. Gruenberg headed up research on Medicare's TEFRA payment formula (i.e., the AAPCC) at the Brandeis University Institute for Health Policy, served as Director of Research for Elderplan (the SHMO in Brooklyn, NY), conducted evaluation and operations research at the Hebrew Rehabilitation Center for the Aged in Boston, and directed long-term care research at the Massachusetts Department of Public Health.
COMMON VARIABLES FOR HMO 1 AND MCBS
- Demographics
- Age, gender, race/ethnicity, educational level, marital status
- Health Status
- Self-reported health
- Diagnoses: high blood pressure, heart problems, cancer, diabetes, rheumatoid arthritis, other arthritis
- Impact of health on social activities
- Functional Activity
- Bending, kneeling, or stooping, lifting or carrying groceries, walking several blocks
- Bathing and dressing
- Satisfaction
- Overall satisfaction
- Satisfaction with information given
- Usual Source of Care
- Have regular doctor
- Doctor is interested in overall health
- Preventive Care
- Mammogram, pap smear, hysterectomy, flu shot, pneumonia vaccine shot, smoking behavior
RESEARCH QUESTION
Did those in poor health and those with functional limitations report lower levels of satisfaction?...more problems with access?
MEASURES OF POOR HEALTH, FUNCTIONAL LIMITATIONS
- Poor Health
- Self-reported health status
- Report having serious or chronic condition
- Impact of health on social activities
- Functional Limitations
- ADL: limited a lot in bathing and dressing
- Limited a lot in walking one block
| TABLE 1. Enrollment by Medicare Category: U.S. and HMO: 1991-1995 | ||||||
|---|---|---|---|---|---|---|
| Year | U.S. Medicare Disabled Population* | HMO 1 | HMO 2 | |||
| Disabled | Aged | Disabled | Aged | Disabled | Aged | |
| 1991 | 3,385 9.7% |
31,485 90.3% |
1,090 2.4% |
45,112 97.6% |
0 - |
0 - |
| 1992 | 3,579 10.1% |
32,019 89.9% |
1,410 3.0% |
45,161 97.0% |
71 0.4% |
18,362 99.6% |
| 1993 | 3,863 10.6% |
32,477 89.4% |
1,567 3.4% |
45,069 96.6% |
186 0.9% |
20,423 99.1% |
| 1994 | 4,151 11.2% |
32,799 88.8% |
1,763 3.8% |
44,773 96.2% |
339 1.4% |
23,963 98.6% |
| 1995 | 4,500 12.0% |
33,100 88.0% |
1,918 4.1% |
45,054 95.9% |
667 2.5% |
26,256 97.5% |
| *U.S. data are given in 1,000s. | ||||||
| TABLE 2. Enrollment by Age and Gender | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Age | U.S. Medicare Disabled | HMO 1 | HMO 2 | ||||||
| Female | Male | Total | Female | Male | Total | Female | Male | Total | |
| <20 years | 0.18 | 0.07 | 0.12 | 0.00 | 0.52 | 0.28 | 1.28 | 1.97 | 1.69 |
| 20-34 years | 12.95 | 14.27 | 13.76 | 5.67 | 6.70 | 6.23 | 7.26 | 7.02 | 7.12 |
| 35-44 years | 18.75 | 22.90 | 21.29 | 9.51 | 12.24 | 10.99 | 22.65 | 19.38 | 20.68 |
| 45-54 years | 29.25 | 23.82 | 25.92 | 27.30 | 20.36 | 23.53 | 20.51 | 18.82 | 19.49 |
| 55-59 years | 15.02 | 17.04 | 16.26 | 22.85 | 18.17 | 20.31 | 40.17 | 45.51 | 43.39 |
| 60-64 years | 23.85 | 21.90 | 22.66 | 34.66 | 42.01 | 38.66 | 8.12 | 7.30 | 7.63 |
| Total | 100.0 (1,451) |
100.0 (2,294) |
100.0 (3,745) |
100.0 (652) |
100.0 (776) |
100.0 (1,428) |
100.0 (234) |
100.0 (356) |
100.0 (590) |
| *U.S. Medicare population data is given in 1,000s. | |||||||||
| TABLE 3. Total Enrollment of the Disabled Population: 1991-1995 | ||||||||
|---|---|---|---|---|---|---|---|---|
| Year | HMO 1 | HMO 2 | ||||||
| Enrolled at Start of Year | New Enrollees During Year | Disenrollees During Year | Enrolled at Start of Year | New Enrollees During Year | Disenrollees During Year | |||
| Voluntary | Death | Voluntary | Death | |||||
| 1991 | 1,090 | 453 | 98 | 35 | 0 | 272 | 1 | 0 |
| 1992 | 1,410 | 330 | 116 | 57 | 271 | 382 | 10 | 3 |
| 1993 | 1,567 | 383 | 108 | 79 | 640 | 354 | 18 | 8 |
| 1994 | 1,763 | 385 | 158 | 72 | 968 | 629 | 20 | 24 |
| 1995 | 1,918 | 591 | 199 | 89 | 1,553 | 258 | 85 | 31 |
| TABLE 4. Disenrollment Rate by Medicare Category: 1991-1995 | ||||
|---|---|---|---|---|
| Year | HMO 1 | HMO 2 | ||
| Disabled | Aged | Disabled | Aged | |
| 1991 | 7.84% | 5.29% | 0.74% | - |
| 1992 | 7.79% | 4.59% | 2.20% | - |
| 1993 | 6.49% | 4.86% | 2.24% | - |
| 1994 | 8.58% | 4.62% | 1.59% | - |
| 1995 | 9.61% | 4.69% | 5.23% | - |
| * Not includes disenrollments due to death | ||||
| TABLE 5. Utilization Rates: A Comparison of the U.S. and HMO 1 | |||||
|---|---|---|---|---|---|
| U.S. Medicare | HMO 1 | State FFS | |||
| Disabled | Aged | Disabled | Aged | Total | |
| 1992 | |||||
| Inp.adm* | 364 | 311 | 486 | 284 | 241 |
| Inp.days* | 3,134 | 2,587 | 2,932 | 1,520 | 1,360 |
| SNF adm* | 11 | 28 | 16 | 23 | 23 |
| SNF days* | 311 | 767 | 501 | 503 | 542 |
| 1994 | |||||
| Inp.adm* | 370 | 337 | 451 | 259 | 305 |
| Inp.days* | 2,774 | 2,291 | 2,638 | 1,396 | 1,573 |
| SNF adm* | 13 | 43 | 25 | 29 | 40 |
| SNF days* | 353 | 1,169 | 523 | 596 | 867 |
| per 1,000 | |||||
| TABLE 6. Utilization Rates by Medicare Category for HMO 1 (1994) | ||
|---|---|---|
| Health Service | HMO 1 | |
| Disabled | Aged | |
| Hospital admissions* | 451 | 259 |
| Hospital days* | 2,638 | 1,396 |
| Day surgeries* | 267 | 164 |
| SNF admissions* | 25 | 29 |
| SNF days* | 523 | 596 |
| ER visits* | 862 | 531 |
| Physician visits | 23.8 | 11.3 |
| Prescriptions | 31.3 | 18.3 |
| * per 1,000 | ||
| TABLE 7. Repeated Hospitalizations: 1991-1994 | ||||
|---|---|---|---|---|
| # of Hospital Episodes | HMO 1 | MCBS | ||
| Disabled | Aged | Disabled | Aged | |
| Percent of Persons by Number of Hospital Episodes | ||||
| 0 episodes | 53.8% | 62.6% | 63.0% | 58.2% |
| 1 episode | 18.2% | 17.3% | 15.9% | 20.5% |
| 2 episodes | 10.0% | 10.5% | 7.7% | 9.6% |
| 3 episodes | 5.7% | 4.8% | 3.5% | 5.0% |
| 4+ episodes | 12.3% | 4.9% | 10.0% | 6.8% |
| #Obs | 942 | 2,293 | 3.054,920 | 24,201,805 |
| Number of Hospital Days/1,000 per year | ||||
| 0 episodes | 0 | 0 | 0 | 0 |
| 1 episode | 1,169 | 1,103 | 1,600 | 1,525 |
| 2 episodes | 2,595 | 2,345 | 3,475 | 3,875 |
| 3 episodes | 3,650 | 3,682 | 5,850 | 5,600 |
| 4+ episodes | 9,333 | 7,527 | 12,650 | 10,775 |
| #Obs | 942 | 2,293 | 3.054,920 | 24,201,805 |
| TABLE 8. Distribution of Hospital Days by Number of Episodes | ||||
|---|---|---|---|---|
| # of Hospital Episodes | MCBS | HMO 1 | ||
| Disabled | Aged | Disabled | Aged | |
| 1 episode | 12.7% | 18.5% | 11.6% | 19.5% |
| 2 episodes | 13.4% | 22.0% | 14.2% | 25.1% |
| 3 episodes | 10.4% | 16.5% | 11.4% | 17.9% |
| 4+ episodes | 63.5% | 43.0% | 62.8% | 37.6% |
| TABLE 9. Services Utilization in HMO 1 by Number of Episodes: 1991-1994 | |||||
|---|---|---|---|---|---|
| # Episodes | 0 | 1 | 2 | 3 | 4 |
| Aged | |||||
| SNF days* | 0 | 485 | 877 | 924 | 2,022 |
| Day surgeries* | 103 | 130 | 177 | 216 | 275 |
| ER visits* | 208 | 408 | 831 | 1,167 | 1,719 |
| Physician visits | 7.5 | 9.7 | 13.0 | 16.7 | 22.5 |
| Prescriptions | 12.5 | 16.8 | 23.7 | 28.1 | 34.7 |
| Disabled | |||||
| SNF days* | 0 | 149 | 202 | 236 | 1,489 |
| Day surgeries* | 92 | 164 | 277 | 434 | 474 |
| ER visits* | 323 | 797 | 738 | 1,648 | 2,032 |
| Physician visits | 10.9 | 16.5 | 25.7 | 30.7 | 51.4 |
| Prescriptions | 18.2 | 28.5 | 39.2 | 44.5 | 50.8 |
| * per 1,000 persons | |||||
| TABLE 10. Distribution of Services in HMO 1 by Number of Episodes: 1991-1994 | |||||
|---|---|---|---|---|---|
| # Episodes | 0 | 1 | 2 | 3 | 4 |
| Aged | |||||
| Inpatient days | 0.0% | 19.52% | 25.1% | 17.9% | 37.6% |
| SNF days | 0.0% | 26.3% | 28.8% | 13.8% | 31.0% |
| Day surgeries | 50.0% | 17.4% | 14.3% | 7.9% | 10.4% |
| ER visits | 30.5% | 16.5% | 20.4% | 13.0% | 19.7% |
| Physician visits | 48.8% | 17.5% | 14.1% | 8.2% | 11.4% |
| Prescriptions | 48.1% | 17.9% | 15.3% | 8.2% | 10.5% |
| Disabled | |||||
| Inpatient days | 0.0% | 11.6% | 14.1% | 11.4% | 62.8% |
| SNF days | 0.0% | 11.1% | 8.3% | 5.5% | 75.1% |
| Day surgeries | 26.1% | 15.6% | 14.5% | 13.1% | 30.7% |
| ER visits | 23.6% | 19.6% | 10.0% | 12.8% | 34.0% |
| Physician visits | 30.0% | 15.4% | 13.1% | 9.0% | 32.5% |
| Prescriptions | 35.4% | 18.7% | 14.1% | 9.2% | 22.6% |
| TABLE 11. A Comparison of Those Age 65-69 Who Were Disabled and Those Age 65-69 Who Were Not Disabled: Health Service Utilization | ||
|---|---|---|
| 1995 Utilization Rates | Disabled 65-69 | Aged 65-69 |
| Hospital admission* | 432 | 150 |
| Hospital days* | 2,096 | 645 |
| Day surgeries* | 227 | 114 |
| SNF admissions* | 46 | 6 |
| SNF days* | 999 | 74 |
| ER visits* | 703 | 365 |
| Physician visits | 16.6 | 9.1 |
| Prescriptions | 29.8 | 16.2 |
| * per 1,000 persons | ||
| TABLE 12. A Comparison of Payments Made by Age in HMO 1 Health Plan | ||
|---|---|---|
| HMO 1 AAPCC Rates | ||
| HMO 1 | 60-64 | 65-69 |
| Part A | ||
| Male | $182.29 | $156.90 |
| Female | $227.86 | $132.76 |
| Part B | ||
| Male | $116.28 | $101.17 |
| Female | $146.88 | $88.52 |
| TABLE 13. Comparing HMO 1 Questionnaires to MCBS | |
|---|---|
| Health and Functional Status | |
| In general, compared to other people (your/sp's) age would you say your health is excellent, very good, good, fair, or poor? | In general, would you say your health is excellent, very good, good, fair, poor? |
| How much of the time during the past month has (your/sp's) health limited (your/sp's) social activities, like visiting friends or close relatives?... none of the time, some, most, all | During the past four weeks, to what extent has your physical health or emotional problems interfered with your normal social activities with family, friends, neighbors or groups? not at all, slightly, moderately, quite a bit, extremely |
| How much difficulty, if any, (do you/sp) have stooping, crouching or kneeling? Would you say; no difficulty at all, a little difficulty, a lot of difficulty, not able to do it | Does your health now limit you in any of these activities? If so, how much?--bending, kneeling or stooping--yes limited a little, yes limited a lot, no not limited at all |
| How much difficulty, if any, (do you/sp) have lifting or carrying objects as heavy as ten pounds, like a sack of potatoes? Would you say: no difficulty at all, a little difficulty, some difficulty, a lot of difficulty, not able to do it | Does your health now limit you in any of these activities? If so, how much?--lifting or carrying groceries--yes limited a little, yes limited a lot, no not limited at all |
| What about walking a quarter of mile, that is, about 2 or 3 blocks? no difficulty at all, a little difficulty, some difficulty, a lost of difficulty, not able to do it | Does your health now limit you in any of these activities? If so, how much?--walking several blocks--yes limited a little, yes limited a lot, no not limited at all |
| Because of a health or physical problem do you/sp have any difficulty...(yes, no, doesn't do) Is this because of a health or physical problem? Do you/does sp receive help from another person? Does someone usually stay nearby just in case you need/sp needs help... Do you/does sp use special equipment or aids to help you/him/her with...? Who helps?--bathing or showering, dressing | Does your health limit you in bathing or dressing yourself? yes limited a little, yes limited a lot, no not limited at all |
| Preventive Care | |
| Have you/has sp a mammogram or breast x-ray since a year ago? (yes, no, refused, DK) | When was last time you had a mammogram? (never, within last 12 months, within last two years, within last three years, within last five years, more than five years ago) |
| Have you/sp had a pap smear since a year ago? (yes, no, refused, DK) | When was last time you had a pap smear? (never, within last 12 months, within last two years, within last three years, within last five years, more than five years ago) |
| Have you/sp ever had a hysterectomy? (yes, no, refused, DK) | Have you had a hysterectomy (surgical removal of uterus)?...yes, no |
| Did you/sp have a flu shot for last winter (between September and December)? (yes, no, refused, DK) | Did you get a flu shot during the last 12 months? yes, no |
| Have you/has sp ever had a shot for pneumonia? (yes, no, refused, DK) | Have you ever had a pneumonia vaccine shot (pneumococcal vaccine, pneumovax)? yes, no |
| Have you/has sp ever smoked cigarettes, cigars, or pipe tobacco? (yes, no, refused, DK) Do you/does sp smoke now? (yes, no, refused, DK) | Do you currently smoke cigarettes? yes, no never smoked |
| Diagnosis | |
| "Has a doctor ever told you..." | "Has a doctor ever told you..." |
| Hypertension or high blood pressure | Hypertension or high blood pressure |
| Myocardial infraction or a heart attack | Heart problems |
| Angina pectoris or coronary heart disease | Heart problems |
| Other heart conditions such as congestive heart failure, problems with the values in the heart, or problems with the rhythm of your heart | Heart problems |
| Skin cancer | Cancer |
| Any other kind of cancer, malignancy or tumor | Cancer |
| Diabetes, high blood sugar, or sugar in your urine | Diabetes diagnosed before age 40. Diabetes diagnosed at age 40 or later. |
| Rheumatoid arthritis | Rheumatoid arthritis |
| Arthritis other than rheumatoid | Arthritis |
| Satisfaction and Access to Care | |
| Is there a particular doctor you/sp usually see(s)? | Do you have a HMO 1 doctor you consider to be your regular doctor? |
| Now I am going to read some statements people have made about their medical care... For each statement please tell me whether you strongly agree, agree, disagree, or strongly disagree--The doctor(s) often seem to be in a hurry. Doctor does not explain your medical problems to you | In general how satisfied with each of the following items related to quality of care at HMO 1? Very satisfied, satisfied, neutral, dissatisfied, very dissatisfied--Amount of time doctors spend with you. Amount of explanation or information provided. |
| The overall quality of the medical care (you have/sp has) received in the last year? Very satisfied, satisfied, neutral, dissatisfied, very dissatisfied. | Overall, how satisfied are you with HMO 1? Very satisfied, satisfied, neutral, dissatisfied, very dissatisfied. |
| The information given to (you/you or sp) about what was wrong with (you/sp)? Very satisfied, satisfied, neutral, dissatisfied, very dissatisfied. | Amount of explanation or information the doctors give you? Very satisfied, satisfied, neutral, dissatisfied, very dissatisfied. |
| The concern of doctors for your overall health rather than just an isolated symptom or disease? Very satisfied, satisfied, neutral, dissatisfied, very dissatisfied. | Personal interest and attention the doctors give you? Very satisfied, satisfied, neutral, dissatisfied, very dissatisfied. |
| TABLE 14. Age and Gender Composition of Survey Respondents, % | ||||||
|---|---|---|---|---|---|---|
| Age | HMO 1 | MCBS | ||||
| Male | Female | Total | Male | Female | Total | |
| Less than 20 years | 0.3 | 0.3 | 0.3 | 0.1 | 0.0 | 0.1 |
| 20-34 years | 7.4 | 5.3 | 6.5 | 8.4 | 7.6 | 8.1 |
| 35-44 years | 12.7 | 12.9 | 12.8 | 19.8 | 18.8 | 19.5 |
| 45-54 years | 18.2 | 24.7 | 21.1 | 24.2 | 23.7 | 24.0 |
| 55-59 years | 19.6 | 20.2 | 19.9 | 17.0 | 18.6 | 17.6 |
| 60-64 years | 41.9 | 36.5 | 39.5 | 30.4 | 31.3 | 30.7 |
| TABLE 15. Race and Ethnic Composition, % | ||||
|---|---|---|---|---|
| HMO 1 | MCBS | |||
| Aged 65 and over | Under age 65 | Aged 65 and over | Under age 65 | |
| White | 97.3 | 95.1 | 92.3 | 79.9 |
| Black/African American | 0.8 | 2.3 | 6.1 | 14.6 |
| Other | 1.9 | 2.6 | 1.6 | 5.5 |
| TABLE 16. Educational Level, % | ||||
|---|---|---|---|---|
| HMO 1 | MCBS | |||
| Aged 65 and over | Under age 65 | Age 65 and over | Under age 65 | |
| Grades 0-8 | 7.8 | 7.9 | 24.9 | 25.7 |
| Grades 9-11 | 12.0 | 12.5 | 16.3 | 21.0 |
| High school graduate | 35.2 | 31.8 | 32.6 | 35.4 |
| Some college | 24.4 | 30.4 | 13.3 | 11.8 |
| College graduate | 8.3 | 8.5 | 7.2 | 3.8 |
| Post-college work | 12.4 | 9.0 | 5.8 | 2.4 |
| TABLE 17. Marital Status, % | ||||
|---|---|---|---|---|
| HMO 1 | MCBS | |||
| Aged 65 and over | Under age 65 | Aged 65 and over | Under age 65 | |
| Currently married | 69.1 | 58.0 | 57.4 | 53.2 |
| Widowed | 22.3 | 6.9 | 33.9 | 8.2 |
| Divorced/separated | 6.6 | 19.8 | 5.0 | 18.3 |
| Never married | 2.0 | 15.3 | 3.6 | 20.3 |
| TABLE 18. Overall Health Status of Survey Respondents, % | ||||
|---|---|---|---|---|
| Rating of Health | HMO 1 | MCBS* | ||
| Aged 65 and over (n=1,429) |
Under age 65 (n=838) |
Aged 65 and over (n=22,757*) |
Under age 65 (n=1,558*) |
|
| Excellent | 5.5 | 3.2 | 17.8 | 4.2 |
| Very good | 26.2 | 9.6 | 25.4 | 8.4 |
| Good | 43.4 | 31.4 | 30.6 | 18.1 |
| Fair | 20.3 | 36.5 | 18.6 | 30.9 |
| Poor | 4.6 | 19.3 | 7.6 | 38.5 |
| * in 1,000s | ||||
| TABLE 19. Diagnoses, % | ||||
|---|---|---|---|---|
| Diagnosis | HMO 1 | MCBS | ||
| Aged 65 and over | Under age 65 | Aged 65 and over | Under age 65 | |
| High blood pressure | 45.8 | 47.5 | 47.9 | 41.8 |
| Heart problems | 32.5 | 33.7 | 33.9 | 36.0 |
| Cancer | 21.2 | 16.4 | 17.2 | 13.0 |
| Diabetes | 14.7 | 27.9 | 13.8 | 15.8 |
| Rheumatoid arthritis | 17.3 | 22.1 | 9.4 | 17.2 |
| Arthritis other than rheumatoid | 51.5 | 44.1 | 45.3 | 40.6 |
| TABLE 20. Functional Difficulty: Percent Reporting Some Degree of Difficulty | ||||
|---|---|---|---|---|
| Functional Activity | HMO 1 | MCBS | ||
| Aged 65 and over | Under age 65 | Aged 65 and over | Under age 65 | |
| Bending, kneeling, stooping | 62.0 | 78.7 | 67.9 | 80.5 |
| Lifting or carrying groceries | 38.5 | 72.5 | 37.8 | 63.9 |
| Walking several blocks | 41.4 | 70.7 | 43.3 | 70.3 |
| Bathing and dressing | 14.4 | 35.5 | 8.8 | 24.5 |
| TABLE 21. Impact of Health on Social Activities: Percent Reporting Some Degree of Impact | ||||
|---|---|---|---|---|
| HMO 1 | MCBS | |||
| Aged 65 and over | Under age 65 | Aged 65 and over | Under age 65 | |
| Health has limited social activities | 39.8 | 66.8 | 32.8 | 71.7 |
| TABLE 22. Overall Satisfaction, % | ||||
|---|---|---|---|---|
| Level of Satisfaction | HMO 1 | MCBS* | ||
| Aged 65 and over (n=1,465) |
Under age 65 (n=843) |
Aged 65 and over (n=22,786*) |
Under age 65 (n=1,558*) |
|
| Very satisfied | 32.0 | 38.4 | 38.2 | 27.3 |
| Satisfied | 55.6 | 47.3 | 49.2 | 53.1 |
| Neutral | 10.5 | 9.1 | 3.8 | 8.4 |
| Dissatisfied | 1.5 | 3.7 | 1.1 | 3.2 |
| Very dissatisfied | 0.4 | 1.4 | 7.7 | 8.0 |
| * in 1,000s | ||||
| TABLE 23. Levels of Satisfaction for Aspects of Care, % | ||||||
|---|---|---|---|---|---|---|
| Aspect of Care | Aged 65 and Over | Under Age 65 | ||||
| Very satisfied/ satisfied | Neutral | Dissatisfied/ very dissatisfied | Very satisfied/ satisfied | Neutral | Dissatisfied/ very dissatisfied | |
| HMO 1 | ||||||
| Amount of explanation or information provided | 79.3 | 14.0 | 6.6 | 80.8 | 11.8 | 7.5 |
| Time spent with doctor | 80.8 | 14.1 | 5.1 | 78.6 | 13.0 | 8.4 |
| Doctor's interest in overall health | 88.4 | 10.1 | 1.5 | 83.9 | 11.4 | 4.8 |
| MCBS | ||||||
| Amount of explanation or information provided | 85.1 | N/A | 13.7 | 82.4 | N/A | 16.1 |
| Time spent with doctor | 83.0 | N/A | 16.5 | 77.0 | N/A | 21.7 |
| Doctor's interest in overall health | 85.5 | N/A | 6.6 | 80.4 | N/A | 9.4 |
| TABLE 24. Preventive Care, %* | ||||
|---|---|---|---|---|
| Preventive Practice | HMO 1 | MCBS | ||
| Aged 65 and over | Under age 65 | Aged 65 and over | Under age 65 | |
| Mammogram* | 57.9 | 59.8 | 37.5 | 33.5 |
| Pap smear* | 39.7 | 49.8 | 32.5 | 41.3 |
| Hysterectomy | 51.1 | 44.9 | 40.5 | 44.5 |
| Flu shot* | 80.6 | 71.2 | 43.4 | 25.1 |
| Pneumonia vaccine shot* | 64.7 | 46.2 | 22.1 | 18.2 |
| * Percent who answered "yes" to experiencing preventive care item within the past year. | ||||
| TABLE 25. Smoking Behavior, % | ||||
|---|---|---|---|---|
| HMO 1 | MCBS* | |||
| Aged 65 and over | Under age 65 | Aged 65 and over | Under age 65 | |
| Currently smoke | 8.6 | 23.1 | 26.1 | 57.5 |
| Ever smoked | 52.4 | 57.6 | 57.3 | 70.0 |
| TABLE 26. Regular Physician, % | ||||
|---|---|---|---|---|
| HMO 1 | MCBS* | |||
| Aged 65 and over | Under age 65 | Aged 65 and over | Under age 65 | |
| Have Primary Care Physician | 91.2 | 91.1 | 81.5 | 69.9 |
| TABLE 27. Significant Correlations | ||
|---|---|---|
| Measures of Satisfaction/Access | Significant Variables | Sign |
| Overall satisfaction | ||
| Overall quality of service | Asthma Depression |
+ + |
| Quality of care provided by doctors | Asthma Arthritis |
+ + |
| Quality of care provided by physician assistants | ||
| Quality of care provided by nurses | Arthritis | + |
| Time spent with doctors | Asthma Diabetes at age 40 or later |
+ - |
| Overall access to care | Bathing and dressing Arthritis | + + |
| Getting night and weekend care | Asthma | + |
| Getting emergency care | Bathing and dressing Bronchitis |
+ + |
| Have regular doctor | Age Gender Arthritis |
- + - |
How the Oregon Health Plan Serves People With Disabilities: System Design Issues and First-Year Impacts
Margo L. Rosenbach, Ph.D.
Margo Rosenbach is Executive Vice President of Health Economics Research, Inc., Waltham, MA. She is the Principal Investigator of the HCFA-funded Evaluation of the Oregon Medicaid Reform Demonstration, which assesses the impact of Oregon's Section 1115 Medicaid waiver on quality, access, utilization, satisfaction, and program costs. The Oregon Health Plan (OHP) involves expansion of Medicaid eligibility, increased enrollment in managed care, and implementation of a priority list to determine Medicaid benefits. The Disability Component of the evaluation focuses on the impact of OHP on people with disabilities. Dr. Rosenbach is also the Principal Investigator on several other Medicaid demonstration evaluations, and has a special interest in access to care among vulnerable populations. Dr. Rosenbach received her Ph.D. in Health Policy from the Heller Graduate School, Brandeis University.
This research was funded under Contract #500-94-0056 from the Health Care Financing Administration. The statements do not necessarily reflect the views or policies of HCFA. The contractor assumes responsibility for the accuracy and completeness of the information contained herein.
OBJECTIVES OF THE OREGON HEALTH PLAN
- Expand Medicaid eligibility to those below the Federal Poverty Level, without regard to categorical criteria.
- Set reimbursement levels sufficient to cover costs, to eliminate cost shifting.
- Make an overt commitment to managed care, where feasible.
- Develop a prioritized list of health services that would be used to establish the scope of benefits, based on the availability of State funds.
PHASED IMPLEMENTATION
- Phase I implemented February 1, 1994 (AFDC, General Assistance, poverty-level pregnant women and children, and Medicaid expansion).
- Phase II implemented January 1, 1995 (disabled, children in foster care, and elderly).
SYSTEM DESIGN ISSUES
- Choice Counseling
- Continuity of Care Referral Form
- The Ombudsman
- The Exceptional Needs Care Coordinator
- The OHP Benefit Package
- Coordination of Acute Care and Long-Term Care
FIRST-YEAR IMPACTS
- Provider Issues
- Consumer Issues
- Access to Care
- Mental Health Services
 |
 |
Comparison of Physician and Hospital Use Among People with Chronic Illness in HMO and FFS Plans
Teresa Fama
Teresa Fama is the Deputy Director of the Robert Wood Johnson Foundation National Program Office, "Chronic Care Initiatives in HMOS." Through this program, Ms. Fama is engaged in fostering and evaluating innovations in the management of people with chronic conditions who are enrolled in HMOS. Prior to her involvement with the Robert Wood Johnson Foundation, Ms. Fama was an analyst at the Prospective Payment Assessment Commission (ProPAC), where she worked on Medicare post-acute care financing issues. Prior to ProPAC, Ms. Fama was a Senior Associate at Lewin-VHI, Inc., a health care consulting firm. Ms. Fama has a Master of Science degree from the University of Rochester in Rochester, NY.
RESEARCH QUESTION
Do chronically ill HMO and FFS enrollees use the same level of physician and hospital services?
DATA SOURCE
1992 National Health Interview Survey
METHODS
Descriptive and multivariate analyses
PRIOR WORK (HEALTH AFFAIRS, SPRING 1995)
- Refuted the notion that chronic illness is more prevalent among people covered by indemnity plans than by HMOS
- Could not examine Medicare and Medicaid
CURRENT WORK
Examined two subgroups:
- People with at least one of 15 chronic conditions
- People who reported their health as fair or poor
DESCRIPTIVE FINDINGS: MD VISITS
- HMO enrollees with chronic conditions more likely than FFS enrollees to visit a physician
- For users, no difference in number of visits
DESCRIPTIVE FINDINGS: HOSPITAL STAYS
- HMO enrollees with 8+ bed days less likely than FFS enrollees to be hospitalized
- For users, no difference in average length of stay
REGRESSION RESULTS
- HMO enrollees with chronic conditions more likely than FFS enrollees to visit a physician
- For users, no difference in number of visits
- No difference in likelihood of a hospital stay or, for users, in the average LOS
- No difference found for subgroup who perceived their health as fair/poor
LIMITATIONS
- Self-reported data
- Non-elderly only, with private insurance
- Can examine utilization only, with some inference about access to care
- Can't conclude anything about patterns of care or outcomes
POLICY IMPLICATIONS
- Data indicate that chronically ill have better access to physician care in HMOS than in FFS
- HMOS appear not to be skimping on care for chronically ill population
- Question remains: To What Extent are HMOS "Shadow Practicing" the FFS System?
| TABLE 1. PHYSICIAN VISITS IN THE PRIOR 12 MONTHS | ||||||
|---|---|---|---|---|---|---|
| Variables | Percent with 1+ Visits | Mean Number of Visits | ||||
| Indemnity | HMO | Total | Indemnity | HMO | Total | |
| Has Chronic Condition | 85.8% | 89.3%* | 86.8% | 7.6 | 8.4 | 7.8 |
| Perceives Health as Fair/Poor | 89.0 | 88.7 | 88.9 | 12.2 | 13.8 | 12.6 |
| Has Limit in Major Activity | 91.5 | 93.4 | 92.0 | 12.2 | 13.9 | 12.8 |
| 8 or more Bed Days | 96.9 | 98.0 | 97.2 | 12.4 | 13.8 | 12.9 |
| All Persons | 77.3 | 81.4* | 78.6 | 4.6 | 4.9 | 4.7 |
| N (in thousands) = | 83,993 | 38,263 | 122,256 | 64,927 | 31,146 | 96,073 |
| * Percentage is significantly different at p<.05, compared with indemnity plan. SOURCE: National Center for Health Statistics, 1992 National Health Interview Survey. |
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| TABLE 2. HOSPITAL STAYS IN THE PRIOR 12 MONTHS | ||||||
|---|---|---|---|---|---|---|
| Variables | Percent with 1+ Visits | Mean Number of Visits | ||||
| Indemnity | HMO | Total | Indemnity | HMO | Total | |
| Has Chronic Condition | 9.7% | 8.2% | 9.3% | 7.6 | 6.9 | 7.4 |
| Perceives Health as Fair/Poor | 20.0 | 16.1 | 18.9 | 8.6 | 8.6 | 8.6 |
| Has Limit in Major Activity | 19.1 | 14.5 | 17.7 | 8.8 | 10.2 | 9.1 |
| 8 or more Bed Days | 32.7 | 26.5* | 30.7 | 8.7 | 8.6 | 8.7 |
| All Persons | 4.8 | 4.1* | 4.6 | 5.8 | 5.7 | 5.8 |
| N (in thousands) = | 83,993 | 38,263 | 122,256 | 4,031 | 1,561 | 5,592 |
| * Percentage is significantly different at p<.05, compared with indemnity plan. SOURCE: National Center for Health Statistics, 1992 National Health Interview Survey. |
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A Managed Care Program for Working-Age Persons with Physical Disabilities
Andrew I. Batavia, J.D., M.S.; Gerben DeJong, Ph.D.; Thomas J. Burns, M.A.; Quentin W. Smith, M.S.; Sigrid Melus, M.P.A.; and Dennis Butler, B.A.
January 31, 1989
EXECUTIVE SUMMARY
This report presents the findings of a study funded by The Robert Wood Johnson Foundation (RWJF) and conducted by the Research Program of the National Rehabilitation Hospital (NRH) to determine the feasibility of developing a managed health care program for working-aged persons with physical disabilities in the Washington, DC, metropolitan area. Members of the physically disabled population tend to be highly vulnerable to such conditions as decubitus ulcers, scoliosis, acute urinary tract infections, and lower respiratory tract infections. They have substantially higher rates of hospitalization than persons who are not disabled. The proposed program is intended to provide access to affordable comprehensive health care services for physically disabled persons aged 18-65. Its objective is to prevent the escalation of minor health concerns to major problems that require hospitalization or other forms of institutionalization.
The feasibility study was conducted by a Research Team consisting of specialists in rehabilitation and health services research, and was reviewed by an Oversight Committee consisting of representatives from local government, the insurance industry, disability organizations, and the provider community. The study had four parts, which are as follows:
- Analysis of the appropriate conceptual model on which to base the proposed program, and determination of the program's general parameters;
- Identification and survey of members of the target population to determine whether they would benefit from, and be interested in, the program;
- Assessment of the prospects for offering the program to members of the target population through public and private sector payors of health care; and
- Analysis of the financial feasibility of the program through projections of likely cost savings to payors as a result of the program.
Based on these analyses, the researchers conclude that the proposed program is feasible, and recommend that it be developed and implemented. A summary of the results of each analysis and the overall conclusions of the study are provided below.
Analysis of Managed Care Models
As initially conceived, the proposed program was to be based on the health maintenance organization (HMO) model of managed care. Under the HMO model, the provider is placed "at risk" financially for providing all covered services needed by its enrolled population during the period of enrollment. The program was to be offered through the disabled individual's underlying health insurance, such as Medicaid, Medicare, Blue Cross/Blue Shield, or other private health insurance plan. The insurer would pay the program a capitation payment to provide a comprehensive set of health care services, as needed, to one of its beneficiaries during the enrollment period.
However, this initial conceptualization changed as a result of the findings of the feasibility study. The HMO model was abandoned due to:
- insufficient cost and utilization data, based on the actual claims experience of the target population, for the accurate calculation of capitation rates;
- concerns about financial viability of a program based on the HMO model (due to the high risks of the target population and lack of adequate claims data on which to base capitation rates);
- the relatively small number of persons likely to be enrolled in the program as compared to the number of enrollees typically required for a viable HMO;
- the unlikelihood that the program would be able to secure affordable reinsurance; and
- concerns by the disabled community over the strong cost-containment incentives of capitation financing and problems in replicating a program for disabled persons based on the HMO model.
Under the revised conceptualization of the program, it would be based on the preferred provider arrangement (PPA) model of managed care. Under the PPA model, the disabled person's insurer would negotiate preferred provider rates with the program for each type of service offered to its disabled beneficiaries, and the program would provide such services as needed. As compared to the HMO model, the PPA model is (a) less financially risky for providers because they do not bear the responsibility of providing the comprehensive care of their enrollees for a single capitation payment; (b) somewhat less dependent on accurate cost data, large enrollment, and reimbursement; (c) less likely to result in conflicts of interest between providers and patients, due to its somewhat weaker incentives for cost containment; and (d) more readily replicable in other areas of the country, including small urban areas.
The Proposed Program
The program would provide a comprehensive set of inpatient and outpatient services to its enrolled population. These would include outpatient primary care services, inpatient hospital services, medical specialty services, home visits by nurse practitioners, and emergency attendant care. It would address the health care needs of persons aged 18-65 who reside in the Washington, DC, Standard Metropolitan Area (SMA) and who have any of the following diagnosed disabilities:
- amputation
- cerebral palsy
- cystic fibrosis
- head injury
- multiple sclerosis
- muscular dystrophy
- post-polio
- spina bifida
- spinal cord injury
- stroke.
The program would be offered through a variety of public and private sector insurance programs to their beneficiaries who qualify under the program as members of the target population. Enrollment in the program would be entirely voluntary on the part of the beneficiary, though disabled persons who choose to enroll in the program would "lock themselves in" for the annual enrollment period. The program, as currently envisioned, would have a small administrative and clinical staff, and would be based in an outpatient facility. It would also contract on a preferred provider basis with hospitals and practitioners in the Washington, DC, area to provide services to the enrolled population.
The Market Analysis and Survey
A market survey was needed to identify physically disabled persons of working age in the Washington, DC, metropolitan area, and to assess their unmet health care needs and their desire for the proposed program. The market area for the survey was defined as the Washington, DC, SMA. To identify members of the target population, an initial screening survey was developed by the researchers and distributed to members of 18 disability organizations in the market area. To be included in the study group, a respondent to the screening survey had to be:
- 18 to 65 years of age;
- a resident of the market area; and
- a person who has at least one of the ten
- diagnosed disabilities included in the target population for the program.
The main survey questionnaire was sent to 993 persons who indicated through the screening survey that they are members of the target population. There were 607 usable responses to the main survey questionnaire (a response rate of 61 percent).
The information objectives of the survey were to develop a demographic profile of the members of the target population; to describe their health and functional status; to evaluate their use of inpatient and outpatient health care services; to determine their level of satisfaction with their current health care services; to examine the extent to which they are covered by health insurance from the public and/or private sectors; and to ascertain their preferences for a managed health care approach to meeting their health care needs. The survey results most pertinent to determining the feasibility of the proposed program are summarized below.
Demographic Profile
Overall, the study group is predominantly white (85 percent), male (56 percent), well-educated, and not currently employed (59 percent). Only 12 percent of the respondents did not complete high school. Some 37 percent have either a college or graduate degree. Only 41 percent of the study group are working full- or part-time. Some 16 percent are unemployed and seeking work. About a third of the members of the study group have an annual household income of less than $10,000. Almost a quarter of the study group have an annual household income of more than $50,000. Slightly over half of the members of the study group receive Social Security Disability Insurance (SSDI), Supplemental Security Income (SSI) or both.
Health and Functional Status
About three-quarters of the study group rate their own health as either "good" or "excellent." Some 55 percent of the study group use either a manual or a power wheelchair. About two-thirds of the study group take care of their own personal needs; the remaining third obtain help on a regular basis from another person. Some 12 percent of the entire study group use a paid attendant to meet their personal care needs. Overall, the group consists of a relatively large number of persons with substantial functional limitations.
Health Care Utilization
About a quarter (26 percent) of the study group were hospitalized at least once during the 12 months prior to receiving the survey. Some 37 percent of all respondents hospitalized in the previous 12 months were hospitalized two or more times during that period. Because some had multiple admissions, the entire study group averaged 45 hospitalizations per 100 respondents during the previous 12 months. Of those hospitalized, half were hospitalized for a week or less; half were hospitalized for a week or more. Some 16 percent were hospitalized for more than two weeks. The average length of stay for the most recent hospitalization was 13 days.
Those who were hospitalized in the previous 12 months were asked how many of their hospitalizations could have been averted if they had received early treatment by a doctor or other health care provider knowledgeable about their disability. Of those who responded to this question, 23 percent indicated that at least one hospitalization could have been averted. Some 28 percent of the study group had difficulty in the past year finding a physician who was knowledgeable about the particular health care needs related to their disabilities.
Health Insurance Coverage
About 96 percent of survey respondents have some form of health insurance coverage: 27 percent have only public sector coverage; 43 percent have only private sector coverage; and 26 percent have a combination of both public and private sector coverage. Some 17 percent of respondents receive health benefits under Medicaid; 20 percent of respondents receive benefits under Medicare; and an additional eight percent receive both Medicare and Medicaid. Of those who have some form of private coverage, most have traditional private health insurance (77 percent). A minority of those with private coverage use a private HMO (13 percent).
Preference for a Managed Care Program
Members of the study group were asked to rank their preferences for three specified types of health care plans. About half (52 percent) of the survey respondents indicated that their first choice would be a managed care plan in which choice of provider is limited to a group of practitioners who are knowledgeable of their disability-related problems, but in which patients would have considerable control over the coordination of their own care. This plan is rated third by only four percent of the respondents. Preference for this type of plan is strong across all disabilities except among respondents with cerebral palsy.
Some 29 percent of the study group indicated that their first choice would be a plan in which choice of provider is limited to practitioners specifically knowledgeable of disability-related problems, but in which the plan is responsible for coordinating the patient's care. Almost half (49 percent) indicated that this type of plan would be their third choice. Some 31 percent of the group indicated that they prefer a traditional health plan in which choice of provider is not limited and the patients are responsible for coordinating their care.
The Payor Analysis
Under the proposed program, health care payors such as Medicaid, Medicare, Blue Cross/Blue Shield, other commercial insurers, and self-insured corporations would pay the program negotiated rates per service for providing health care services to their disabled beneficiaries. For this reason, third-party payor involvement is essential to the success of the program. A central component of the feasibility study was to determine whether the various public and private sector payors in the Washington, DC, area would be interested in offering the program to their beneficiaries with disabilities. Throughout the study, members of the Research Team met with public and private sector payors.
The researchers determined that Medicaid participation in the proposed program would be essential to its feasibility, because it is believed that physically disabled Medicaid recipients comprise the single largest pool of potential enrollees for the program. The District of Columbia Office of Health Care Financing (DCOHCF), which administers the District's Medicaid program, indicated that it would be willing to participate in the program if it can obtain "waivers" necessary for federal Medicaid funding of the program from the U.S. Health Care Financing Administration (HCFA). It is expected that HCFA will approve the Medicaid waiver request prepared by the Research Team on behalf of DCOHCF, and the program will be able to receive funding under DC Medicaid. Once approved, similar waiver requests will be prepared for the program on behalf of Maryland and Virginia.
Medicare participation in the proposed program would also contribute importantly to the program's feasibility. Funding of the program by Medicare is somewhat less likely than is funding by Medicaid, though it is still very feasible. Medicare waivers for a research or demonstration project would be needed for Medicare participation in the program, but approval of such waiver requests by HCFA is more discretionary than approval of Medicaid waiver requests. Once the program has been applied to Medicaid recipients, the Research Team will be able to estimate program costs adequately to apply for a Medicare waiver. There is a reasonable probability that Medicare funding could be secured by the third year of the program.
The prospects for funding of the program by private sector payors such as Blue Cross/Blue Shield and other commercial insurers are least optimistic. Impediments to private sector participation include (a) difficulties for insurers in identifying disabled persons among their beneficiaries and in determining their costs; (b) high costs of negotiating for and operating a separate program for a relatively small number of disabled beneficiaries; and (c) difficulties in addressing the administrative complexities of paying for services under the program. Despite these impediments, private sector insurers have expressed interest in meeting the needs of their disabled beneficiaries, and it is likely that some private payors will cover services provided by the program.
The likelihood of obtaining reinsurance for the program at a premium that would permit the program to operate in a financially viable manner is small. It is expected that this will not preclude the program's feasibility, because the risk of extraordinary losses is substantially reduced due to the adoption of the preferred provider model for the program.
The Financial Analysis
The Research Team had initially proposed to RWJF to develop a series of income statements and cost projections for the proposed program, based on varying assumptions on program utilization and per capita rates. However, due to the lack of available cost data based on actual claims experience, and the modification of the proposed program from a capitation-financed program to a preferred provider program, such projections are too speculative at this time. Instead, the Research Team developed a set of projections as to likely cost savings by Medicaid as a result of the managed care program.
It is anticipated that annual cost savings to the Medicaid program would range between $25,000 (if only 250 Medicaid recipients enroll in the program) to $125,000 (if 500 recipients enroll). Projecting that 300 Medicaid recipients would enroll in the program by its third year, the Research Team believes that Medicaid is most likely to save $55,000 a year as a result of the managed care program. Cost savings are likely to be similar for Medicare and private sector insurers that offer the program, and to increase over time as hospital costs increase more rapidly than program costs.
In addition to reducing health care costs, the program would enhance access to high-quality care for persons with disabilities. It is through such enhanced access to managed care that the program is expected to reduce the number of avoidable hospitalizations and emergency room visits by disabled persons, and to increase the cost-effectiveness with which they receive health care services. The high rate of hospitalizations of disabled persons and their poor access to informed comprehensive care have resulted in substantial disruptions to their lives, including financial hardship and interference with their social and work responsibilities. The researchers believe that the program's expected ability to reduce such disruptions for disabled persons is as important as the modest cost savings expected for payors.
Conclusions/Recommendations
Based on the results of this study, the researchers recommend that the proposed program should be developed and implemented. There appears to be a strong interest in, and desire for, a managed care program among the target population of persons with physical disabilities in the Washington, DC, metropolitan area. A majority (70 to 80 percent) of the members of the study group prefer some type of managed health care program over a traditional health care program. These respondents, and other members of the target population they represent, are likely to consider enrolling in the proposed program if it is offered to them.
Almost all persons (96 percent) surveyed have some form of health insurance that could potentially offer the program to their beneficiaries with disabilities. There appears to be considerable interest among the payor community in the program, and a substantial likelihood that the program would be financially viable. The DC Medicaid Program is very likely to be willing and able to offer the program to its recipients. Similarly, there is reason to believe that the Virginia and Maryland Medicaid programs will be willing to participate. Medicare and the private sector insurers may also participate once the program has been implemented.
This study further confirms the findings of other studies that have found a high rate of hospitalizations among the disabled population. It is noteworthy that 23 percent of the respondents who had been hospitalized at least once in the previous 12 months indicated that they believe at least one hospitalization could have been averted if they had access to early preventive care. These results suggest that the proposed program, which would provide prevention and early detection of disability-related health problems, would help to reduce unnecessary hospitalizations and thereby reduce the health care costs of the disabled population. However, even if such cost savings do not result, the program is still very likely to enhance access to care and quality of services for disabled persons without increasing costs.
The specific form that the program should take must be decided during a technical design and development stage of this project. Results from the market analysis suggest that the target population includes many sophisticated health care consumers who would prefer to retain substantial control over their own health care within a managed care system, as well as a significant number of persons who would prefer that health care professionals maintain primary control. One implication of this finding is that the program should consider offering enrollees two options, one in which the staff would coordinate their care and another in which enrollees would coordinate their own care. In either case, care would be provided by a limited number of practitioners specifically knowledgeable of the health care needs of working-age persons with physical disabilities.
This study was sponsored by the Robert Wood Johnson Foundation.
A Vision for the Future: Interview with Gerben DeJong, Ph.D.
Jane Mattson Prince, Ph.D., and Janet Haas, M.D.
Journal of Head Trauma Rehabilitation (forthcoming)
DO NOT QUOTE OR CIRCULATE
Q: You obviously have a very strong interest in disability and health policy issues. Could you summarize your many research projects in disability and health policy by telling us about the major themes they encompass?
A: Our health services research portfolio falls into two main categories of research issues. The first category of issues pertains to medical rehabilitation as a distinct provider group in the American health care system with its own financing, service delivery, and outcome issues. The second category of issues pertains to people with disabilities as a distinct consumer group within the larger health care system with its own health care needs, access issues, and outcome concerns. In the second category, we are concerned with the full spectrum of health care services, not only medical rehabilitation services, that people with disabilities may need.
Our research addresses the full spectrum of health service issues--health care need, capacity, access, service delivery, utilization, costs, outcomes, consumer satisfaction, and health care financing. In addition to our investigator-initiated and contract research projects, we are also home to the Research and Training Center (RTC) on Medical Rehabilitation Services and Health Policy funded by NIDRR [National Institute on Disability Research and Rehabilitation]. We also conduct, with Georgetown University, a health policy research fellowship program for people with disabilities.
Q: In your description of your research, you touched on an area that is of enormous interest to brain injury professionals. Brain injury programs have proliferated in the past 16 years but recently, many have recently closed and while others have consolidated or merged. This change in the industry may have reflected the tremendous changes in reimbursement precipitated by managed care. Managed care has had a significant impact on who has care and for how long they have it. Do you think that, by the Year 2000, managed care will be the dominate way in which we deliver and pay for health care?
A: Yes, very definitely. Approximately, 70% of all people who participate in employer-sponsored health plans are now enrolled managed-care plans. Even Medicare and Medicaid, the first and third largest payers of brain injury rehabilitation services, respectively, are converting rapidly to managed care. I predict that, by 2000, over 50% of the Medicare and 85% of Medicaid will be managed care. Other payers of brain injury rehabilitation such as commercial insurers, workers' compensation, and CHAMPUS have also introduced managed care options that will become more prevalent in the years to come.
Those who look to Medicare as the remaining bastion of fee-for-service medicine should think again. Medicare and Medicaid remain the fastest growing portions of the federal budget. Politicians are perfectly content to let the "market forces" of managed care bring down the costs of these two programs and make the hard decisions for them. The politics of the federal deficit and the economics of health care converge on managed care. In other words, managed care is the harmonic convergence of deficit politics and health economics. It is unstoppable. We have to figure out how we can make managed care work for the people we serve.
Q: How is managed care being implemented in the public sector especially in Medicare and Medicaid? Do individual state Medicaid programs contract with private managed health care plans such as health maintenance organizations (HMOs)? Will each state offer more than one managed care plan to its Medicaid participants?
A: In many markets, Medicare beneficiaries can choose whether they want to enroll in a managed care plan. In a highly managed care market such as the Los Angeles, about 40% of all seniors already participate in a managed care plan. In the parlance of the Medicare program, these plans are commonly referred to as "at-risk Medicare contracts." The Medicare program sets the premium at 95% of what Medicare theoretically would have spent for the same population adjusting for age and county of residence.
Until recently, Medicare was introducing managed care more quickly than state Medicaid programs. Currently, state Medicaid programs are converting to managed care more rapidly than the Medicare program. Medicare beneficiaries can usually choose between a managed care and a fee-for-service plan. In most states that have converted, Medicaid recipients can only choose between two or more managed-care plans.
State Medicaid programs typically invite proposals from managed health care plans in response to RFPs [requests for proposals]. States typically like to see two, three or more HMO's in each market in order to spur competition. The managed-care industry is already bidding vigorously on Medicaid contracts. One has only to read the reports of Wall Street analysts to appreciate how managed care plans are poised to move aggressively into the Medicaid market.
Q: Some of the larger HMO's have significant experience working with catastrophic injuries. Companies such as Kaiser Permanente, US Healthcare, and others may have had good results in managing these cases. Do you think that this track record will help them compete successfully for Medicaid contracts?
A: I cannot attest to the track records of Kaiser and US Healthcare with respect to catastrophic injuries. Yes, having a good track record is important in helping secure contracts. I doubt, however, that a health plan's track record with catastrophic injuries is being examined all that closely at this time. Managed-care plans scrambling to get into the emerging Medicaid markets are ill-equipped to address large populations of people who have disabling health conditions. Up until recently, managed care's largest market consisted of people who participated in employer-sponsored plans. Moreover, the first Medicaid participants to be enrolled managed care have been AFDC [Aid to Families with Dependent Children] recipients, not SSI [Supplemental Security Income] recipients [who are also Medicaid eligible]. Employer-sponsored enrollees and AFDC recipients are, on average, much healthier and less impaired than the disabled populations served under the SSI program or the SSDI [Social Security Disability Insurance] program [who are Medicare eligible]. Many managed care plans are at the bottom of a learning curve as they move into those portions of the Medicare and Medicaid markets comprised of people with disabilities. I believe that, at least in the short term, many people with disabilities such as those with significant brain injuries will not be well served.
In many states, the transition of managed care has been chaotic. In the District of Columbia, for example, there have been problems with people who have not been enrolled properly with family members being assigned to primary-care gatekeepers located at the opposite ends of town. Again, remember, that Medicaid only pays about 11% or 12% for inpatient brain injury rehabilitation. This percentage is bound to increase as problems in the private health insurance market continue to get passed on to the public sector.
Q: You describe a fair amount of chaos for health care services and payment for individuals who sustain brain injuries over the next decade.
A: I don't know that it will last for ten years, but there certainly will be chaos in the short term. I believe that, over the long term, things will be better organized than in the past for reasons I hope I will have a chance to elaborate later in this interview.
Q: How will health plans and health services be organized in the future? How will that affect access to services for people with brain injuries?
A: We don't need a crystal ball. The future is already here. Our center conducted a study of how medical rehabilitation is faring in the three most highly managed-care markets in the country, namely San Diego, Minneapolis-St. Paul, and Worcester, Massachusetts. Our study uncovered a number of trends worth noting. One important trend is how managed care is forcing consolidation of providers into three or four major provider networks within each market. In the Minneapolis-St. Paul market, most providers have been organized into three main "integrated service networks" or ISNs for short. For people with brain injury, their access to services will depend on how their health plan is tied to one of these networks and whether the network includes the full range of health services that people with brain injuries need--from initial acute care and rehabilitation to ongoing health care services following rehabilitation. For providers of brain injury services, their referrals will depend on whether they are a member of an ISN. If not, they are at risk of being frozen out of the market since one purpose of the ISN is to keep patients within the network.
There are even larger forces at work here and some historical perspective can be useful in ascertaining their probable impact on people with brain injuries. Until recently, our health care system was a provider-driven system that competed not on price and quality as in other markets, but largely on prestige. Prestige competition meant that providers competed on the basis of their latest technology, their academic affiliations, the size of their research grants, the credentials and size of their medical staffs, their level of specialization, and the bed-size of their institutions. Prestige competition encouraged capacity building such as the development of brain injury rehabilitation services during the 1980s. Prestige competition helped to make American health care the most sophisticated and technologically advanced in the world, but it has also led to tremendous excess capacity that made American health care frightfully expensive. With the advent of managed care and capitation payment, our health care system has become a payer-driven system where price (i.e., costs) has replaced prestige as the defining element in the competition. People with brain injuries are disadvantaged in a system that competes mainly on price because people with brain injuries may require considerable services of indefinite duration.
In the shift from a provider- to a payer-driven health care system, one element has remained, namely, risk competition where health plans and risk-bearing entities seek to avert having to enroll or serve high-risk groups with potentially high health care costs such as those with brain injury. Unbridled risk-based competition means that certain groups will be underserved, excluded, or simply priced out of the market.
Although the incentives of a payer-driven system do not bode well for people with brain injury, I believe that we are on the verge of yet another major shift in American health care, namely the shift from the current payer-driven system that competes on price and risk to a consumer-driven system that competes on price and quality as in most other markets.
Effective quality competition as both the health-plan and health-provider levels requires a number of preconditions. Most important is the availability of quality-related information that consumers, employers, and governments can use to evaluate health-plan and provider performance in determining whether to contract with, or enroll in, a health plan and its corresponding provider network. By quality-related information, I mean data about outcomes, consumer satisfaction, and health-plan disenrollment rates, adjusted, or course, for the case mix or severity mix of the people participating in a particular health plan.
Quality competition is where I see the interests of both providers and consumers converge. In the absence of sound quality information, providers of brain injury services must compete mainly on price and will find themselves ratcheted down by payers over time. Quality competition, in addition to price competition, will help to create a more level playing field for providers. Moreover, quality information is sorely needed by consumers and their representatives who need to make informed choices about where best to obtain services. Effective quality competition is essential to the survival of the nation's brain injury rehabilitation capacity.
Q: Since consumers and providers have a mutual interest, what can they do in the short term to foster effective quality competition?
A: First, the rehabilitation industry has to organize itself to develop an agreed-upon set of quality indicators. Fortunately, the industry has already made some significant advances in outcome measurement and has the basic building blocks to develop industry-wide quality indicators that can be used to evaluate the performance of both providers and health plans. I would strongly recommend the involvement of the industry's consumer constituencies to obtain both their insight and their political support for implementation.
An important technical challenge, I believe, is to develop risk adjusters or severity adjusters by which quality indicators can be adjusted for the case mix of people served in various programs and health plans. Only then can we make effective comparisons across providers and health plans.
Second, consumers and providers need to pressure their respective state governments to make sure that, as their Medicaid programs convert to managed care, there be a choice of plans in each state and that there be quality indicators across a whole spectrum of health services, including brain injury services, by which consumers can make informed choices about health plans. Not every consumer needs to be a sophisticated shopper of health plans but a well-informed minority can alter a health plan's market share and can be the opinion leaders that cause others to follow suit.
Third, consumers and providers need to pressure the federal government to insist that there be comparable quality indicators in both the Medicare and Medicaid programs across state lines. Some degree of standardization will be needed in order to ease the burden on health plans and providers who operate across state lines. Standardization will also facilitate comparisons of comparable health plans and providers in different states.
Fourth, brain injury providers and consumers need to pressure quality standard-setting organizations such as NCQA [National Committee on Quality Assurance] which accredits managed-care plans on behalf of large-group purchasers in both the private and public sectors. National accrediting bodies such as NCQA need to include rehabilitation indicators in their standard repertoire of quality measures.
There is much more that can and should be done. The point is that the brain injury community, both consumers and providers, should insist on a level-playing field on which providers can compete and consumers can choose.
Q: Even if we create a more level-playing field, will there not be serious discontinuities in health care coverage for people with newly-acquired brain injuries? In the past, many individuals has unlimited coverage under their automobile no-fault insurance; today fewer individuals have substantial auto no-fault coverage. There are individuals who come into the system with worker's compensation, but many cases come with only limited commercial health insurance. As they deplete their benefit, how can they access Medicaid or Medicare? Will managed care provide a vehicle by which there be greater continutiy of coverage from one health plan to another?
A: The majority of individuals will have some health care coverage. Of those who have no coverage at the time of their injuries, many will eventually become Medicaid eligible because of low income or because they have exhausted their financial resources that would otherwise render them ineligible for Medicaid. Regardless, of the source or type of health care coverage, managed care will be the dominant arrangement.
Having a health plan is only half the battle. The other half is whether the health plan will pay for rehabilitation services. Many health plans nominally include rehabilitation benefits in one form or another. The problem in managed care arrangements is obtaining access to the benefit vis-a-vis a physician gatekeeper or case manager. Moreover, there is a real issue as to whether a person will be able to obtain services in a setting most appropriate to his or her needs. Here is where individual and family advocacy becomes so important. The issue then, is a three-fold: First, does the person have a health plan? Second, does the health plan really cover the range of rehabilitation services needed? And, third, will the case manager authorize the services? In other words, having health insurance means little unless the health plan is prepared to pay for the services needed.
I believe that significant discontinuities between private-sector and public-sector coverage will remain for the foreseeable future. This is especially the case now, as mentioned earlier, for individuals who become eligible for Medicaid following a means test that requires an individual to deplete their resources, In other words, they must first impoverish themselves. There is also a continuity problem for working-age people who apply for Medicare. Applicants face a 24-month waiting period after first becoming eligible for disability income benefits under the Social Security Disability Insurance program for which there is already a 5-month waiting period--29 months in all, not to mention the several months it initially takes to apply for DI benefits.
Within, the Medicaid program, however, there are many changes underway at the state level that will help diminish, but not necessarily eliminate, some of the current discontinuities. State Medicaid programs are becoming less categorically oriented. In the past, you had to be an AFDC [Aid to Families with Dependent Children] recipient or an SSI [Social Security Income] recipient, or be "categorically related" to such recipients except for income, in order to qualify for Medicaid benefits. Today, many states have applied for, and received, federal "waivers" that enable them to provide Medicaid coverage for a broader segment of the population. Some of the discontinuities or disruptions will not be as severe or as long lasting as they once were. During the health care reform debate in the 103rd Congress there was some discussion of making the Medicaid program also function as a "wrap-around" program for private sector health plans. The problem in implementing the concept was that it would encourage private plans to shift their costs to the public sector and such a plan would require a policing or gate-keeping function between private and public health plans.
Managed care by itself will not solve the discontinuities from one health plan to another, from the private sector to the public sector. The health care reform debate and the managed care revolution has spurred us as a nation to think more creatively about how these discontinuities can be addressed. These changes have forced us to "think outside the box" and cast away self-limiting assumptions. To illustrate, the six New England states are now banding together to apply for a federal waiver that would enable each state to pool both Medicare and Medicaid funds and coordinate benefits, perhaps under a managed care umbrella, for those who receive both Medicare and Medicaid benefits by virtue of their dual eligibility for both DI and SSI benefits. Such an arrangement may help to dissolve some of the discontinuities between acute and long-term care.
Q: In some of your writings you underscore another important discontinuity, namely, the discontinuity in meeting the ongoing health care needs of people with disabilities once the rehabilitation phase of their care is completed. Many people with disabilities in managed care plans believe that most primary care physician gatekeepers do not fully understand their constellation of ongoing health care needs and find that they are blocked from obtaining the services they need from specialists. What can providers and consumers do to alter this state of affairs? Should they demand that a specific kind of gatekeeper be used for people with significant impairments?
A: Medical rehabilitation providers have been slow in addressing this important issue. Many rehabilitation providers thought it was enough simply to refer the patient back to his or her primary care provider if he or she had one. For years, people with disabilities have been telling the rehabilitation community that their needs were not being met by primary care providers who did not understand their needs were not being met by primary care providers who did not understand their needs and who often had offices and examine tables that were not fully accessible. In many instances, former rehabilitation consumers rely on their rehabilitation physician when they doubt the medical advice and care they receive from traditional primary care providers. This problem dates back before the days of managed care but the problem has come to a head in managed care because most managed care physician gatekeepers are primary care physicians who have little training or knowledge about the health care needs of people with significant disabilities.
I do not want to mis lead you. Organized rehabilitation medicine has not been totally asleep on the issue of primary care. Several meetings and conferences have addressed this issue. One noteworthy meeting was the April 1995 conference cosponsored by the Rehabilitation Institute of Michigan and the NRH Research Center on the role of organized rehabilitation medicine in primary care.
Quite candidly, most primary care physicians would prefer not having too many people with disabilities in their practice. We learned this several years ago, when we attempted to develop a network of primary care physicians as part of Robert Wood Johnson Foundation project on disability and managed care. People with catastrophic injuries are viewed as a loosing financial proposition for most primary care providers. People with disabilities require much longer-than-average office visits and they consume more downstream health services which count against the primary care gatekeeper's utilization score card that is carefully monitored by the managed care plan.
Thus, in a capitated managed-care environment, payers have few incentives to attract, and providers such as primary care providers have few incentives to serve, people with disabilities. Once people with disabilities are in a health plan, it is to the advantage of the plan to more effectively manage their ongoing health care. This state of affairs provides an opening for rehabilitation providers to negotiate capitated carve-outs with managed care plans in keeping with the kinds of services people with disabilities need and actually want.
Rehabilitation providers often understand the ongoing health care needs of people they serve far better than most primary care providers. Rehabilitation providers need to think about how they can become an upstream primary care provider in a managed care environment for people with disabilities. Dr. Bruce Gans of the Rehabilitation Institute of Michigan framed it well he suggested that rehabilitation providers need to ask themselves the following question: "Are we in the business of rehabilitation or are we in the business of health care for people with disabilities?" The answer to the latter opens up many new possibilities.
The concept of carve-outs for selected groups of people with disabilities is not a new. Community Medical Associates (CMA) in Boston, for example, has a successful capitated health plan with Massachusetts Medicaid for a group of working-age people who require personal assistance services. This is akin to the "disease-management" programs that are emerging across the land. These are programs in which providers carve out populations within health plans in order to better meet the health care needs of the plan's subscribers and thus also avert the downstream expenditures that would otherwise compromise the bottom of line of managed-care organizations.
Q: Capitation involves shared risks in which rehabilitation providers assume more risk. Providers will realize adequate profits if they assess accurately the resources that will be used over time to reach a specified outcome. Are you saying that if providers are willing to become risk-taking or risk-bearing entities that they will be prone to render more efficient care that will become the standard of future care?
A: The answer is yes--if certain conditions are met--but the reasons differ somewhat depending on the phase of care one is speaking about, whether it be the rehabilitation phase or the post-rehabilitation phase of care.
For a provider to be a risk-bearing entity during the rehabilitation phase, it must have reasonably accurate information about the probable costs associated in attaining a particular outcome for a patient with a particular clinical and psycho-social profile. This requires the provider to invest heavily in information systems that can provide the cost and outcome information needed to price its services with reasonable confidence. It also means that each provider has to accumulate enough experience over time to develop the confidence intervals needed to measure its risk exposure. As competition intensifies, each provider will have to determine how it can achieve the predetermined objectives in the most efficient manner. Over time and through experience, new standards of care will emerge as providers are incentivized to achieve quality outcomes at a price.
At the risk of some digression, I believe that efficient markets driven by price and quality concerns, also have significant implications for the role of research and the development of practice guidelines in establishing standards of care. In short, if markets work efficiently, what then should be the role of research and the development of practice guidelines? I believe their roles will change. Practice guidelines are anchored in "scientific evidence" and supplemented with consensus expert clinical opinion. The gold standard for scientific evidence is the randomized clinical trial (RCT). RCTs have a number of inherent limitations. RCTs usually investigate a limited number of interventions or combination of interventions. The ability to generalize study findings is sometimes severely limited by the criteria used to the select the study sample. RCTs are an enormously expensive and inefficient way to arrive at a scientific basis for clinical practice.
I believe that, if markets are structured appropriately with the right incentives, providers are smart. Very smart. One only has to observe how providers are able to game any payment system to their advantage. Establish fair rules based on costs and outcomes, and providers will figure it out. In other words, an efficient market system based on sound rules and sound information, is tantamount to thousands of scientific experiments as each provider seeks to maximize outcomes and minimize costs. Yes, RCTs will still be needed to answer certain questions, but I believe that sound price-and-quality competition will bring us more quickly to a better standard of rehabilitative care than will a thousand RCTs. RCTs and much of clinical research is needed because we do not have efficient markets to ferret out inefficient and nonbeneficial care. This is where health services research comes in. Health services research can help clarify whether markets are sufficiently efficient and can evaluate how provider and patient inputs relate to predetermined outcomes.
In the area of brain injury rehabilitation, Paradigm Health Corporation, though not a provider, is an example of an entity that uses clinical and outcome data to negotiate prices and to determine its risk exposure. Paradigm is an organization that serves as a broker between payers and rehabilitation providers. Because it has accumulated a substantial data base, it has the historical data with which to determine the probable costs and outcomes that should be expected in providing rehabilitation services to a patient with a particular clinical profile.
Another variant on the Paradigm model is a market concept developed by Robert Magnuson, MD who suggests that health plans purchase rehabilitation services through a bidding process that would work like this: when a subscriber incurs a major disabling impairment, the health plan would issue an RFP [request for proposal] by fax or e-mail to qualified rehabilitation providers. The RFP would describe the clinical and psycho-social profile of the patient and outline the desired therapeutic objectives and outcomes. Each eligible provider would be asked to fax back, within 24-48 hours a proposal and a fixed price. The rehabilitation provider may also want to send a nurse or, in the case of brain injury, a neuropsychologist to examine the patient and medical record more closely before sending in its bid. To make informed bids, the rehabilitation provider would have to draw heavily on previous outcome and cost data. This approach would be particularly attractive in health markets where integrated service systems do not include rehabilitation providers and where payers, such as auto insurers and workers' compensation do not have corresponding service networks in the area in which the patient lives.
For a provider to be a risk-bearing entity for ongoing health care services during the post-rehabilitation phase, it also must have information about the probable costs associated in providing health services during a given enrollment period. If the enrollee's health plan is incentivized to retain subscribers from one enrollment period to another--by grading health plan quality in part on disenrollment rates, then the health plan and health provider will also be incentivized to avert longer-term downstream costs by providing the necessary up-front preventive services. The Community Medical Alliance of Boston, I mentioned earlier, determined that clinical depression and pressure sores were two sentinel conditions, that if managed proactively, would save them considerable costs both in the short-term (current enrollment period) and in the long-term (beyond the current enrollment period). These kinds of experiences will eventually help to establish new standards of care for ongoing health care needs of people with disabilities during the post-rehabilitation phase of care.
In establishing capitation rates, providers can examine the claims history files of their target population. Some of these data are proprietary but there are a number of public-use files, stripped of personal identifiers, at the federal and state levels for Medicare and Medicaid respectively. Providers willing to go at risk can use these data as benchmarks by which to capitate their services and offer payers a price that beat these benchmarks.
Q: Let's go back to the rehabilitation phase of care. You have spoken about the need for a system that competes on price and quality where quality is defined in large part by health and functional outcomes. What is the role of outcome studies today and what do you see as the role of outcome studies in the future?
A: Good question. The best way to answer this question is to go back to my thesis that the American health care system of the past was a provider-driven one that competed on prestige and risk; that the system of the present is a payer-driven one that competes on price and risk; and that the system of the future will be a consumer-driven one that will compete on price and quality. The role of outcome studies is different is each of these three systems.
In the provider-driven system of the past that competed on prestige, the role of outcomes research was to help establish the academic and scientific legitimacy of a field, a specialty, a profession, or a particular intervention. The ultimate and intended audiences were not payers or consumers but mainly one's professional peers, particularly those in related disciplines. Outcomes research was, and to some extent, remains, an important weapon in prestige competition. Medical rehabilitation's desire to obtain a foothold in the National Institutes of Health is one example of how a profession or discipline has sought legitimacy among its professional peers. I do not mean to be cynical at all but simply wish to illustrate how prestige competition was fundamental to the business of research.
In the payer-driven system of the present that competes on price, the role of outcomes research is cost minimization, i.e., to help establish the minimum that payers should be required to pay or cover in their benefit packages. In other words, health plans seek to cover and pay only those services for which there is a proven benefit or outcome. Payers are confronted with many claims about efficacy but are seeking more explicit evidence for these claims.
Outcome research is a payer-driven system is also promoted by providers who see outcome studies as a defense against the unrelenting drive to cost minimization.
In the consumer-driven system of the future will compete on quality as well as price, the role of outcomes research is to help consumers and large-group purchasers to make informed choices about health plans and health providers based on risk-adjusted comparisons of outcomes and other quality indicators. In the consumer-driven system of the future, outcomes research will become much more institutionalized; it will become part of the infrastructure of our entire health care system. It will become an integral part of how we do business. We will still be doing ad-hoc studies in response to specific information needs, but outcomes research will become much more ubiquitous. Because health-plan and provider outcomes will be so important competitively, there will also be powerful incentives to game the outcomes research process. I envision an auditing subindustry to emerge that will audit the integrity of outcomes research data analogous to the way in which public accounting firms audit financial statements.
Q: You mention that, in today's payer-driven system, health plans want to cover and pay only those services for which there is adequate evidence of benefit or outcome. Could you explain or illustrate what you mean by this?
A: Health plans are constantly bombarded with coverage and payment demands for services that sometimes appear to be of marginal benefit. In a payer-driven system where cost-minimization or price is central to the competitive process, health plans do not know how to triage many of the demands for coverage or claims for payments.
To illustrate, the NRH Research Center faced this issue recently when it completed a year-long study on the effectiveness of medical rehabilitation services for CHAMPUS [Civilian Health and Medical Program of the Uniform Services]. One purpose of the review was to determine which medical rehabilitation services might be added or deleted from the CHAMPUS benefit package. CHAMPUS requested that the NRH Research Center, under a subcontract to another firm, review the medical rehabilitation literature for each of 13 major impairment groups represented in medical rehabilitation including traumatic brain injury. To facilitate this process we commissioned a panel of rehabilitation physicians, each of whom prepared a paper that reviewed the best available literature in their respective impairment area of expertise. Project methodologists rated the scientific rigor of this literature and an allied health panel evaluated whether each paper was sufficiently responsive to allied health issues.
We learned that there was more literature than we had anticipated but very little of this literature attained the level of scientific rigor eventually sought by CHAMPUS. Nathan Cope, MD prepared an outstanding review of the brain injury literature and your readers will want to know that this literature is among the stronger literatures in medical rehabilitation.
We also learned that the literature is not organized to answer the questions that CHAMPUS, and other payers ask on a daily basis. CHAMPUS, it turned out, wanted to know how each individual rehabilitation service contributed to outcomes. For example, CHAMPUS wanted to know how many hours or visits of PT or OT should be covered and what would be an appropriate length of stay in a rehabilitation center for a person with a particular impairment. The medical rehabilitation literature is not organized at the therapy level and the allied health literature is quite weak. Moreover, in daily practice, the configuration of individual therapies are customized to the needs of each individual patient in keeping with the nature of the impairment, medical history, functional status, psycho-social profile, lifestyle needs, and other individual and family circumstances. Such individualization makes generalization about units of therapy very difficult.
A significant portion of the medical rehabilitation outcomes literature is organized around systems of care as exemplified by the model systems such as the brain injury model systems program. Dr. Cope said it best when he, in his paper, argued that TBI rehabilitation cannot always be reduced to a single 'silver bullet' and that TBI rehabilitation is "multifactorial with many poorly defined elements delivered with variable intensity and expertise over differing time spans." He argued that in addressing questions about the overall efficacy of TBI rehabilitation, it often become necessary "to consider the TBI rehabilitation process to essentially comprise a 'black box' consisting of various permutations of all these treatments." Health plans such as CHAMPUS want to know what is in the black box and how much of the black box they should pay for.
Q: Are payers asking the wrong question?
A: In some ways they are. Payers are mainly concerned about outcomes in helping them determine whether a service should be included in their benefit package. In everyday practice, however, their quest for cost minimization causes payers to focus mainly on inputs and the cost of those inputs. They are input, not outcome conscious. They are looking at the wrong side of the input/output equation. I believe that too many health plans are still encumbered by the baggage of the fee-for-service, provider-driven system that focuses on a separate payment for each input. In today's managed-care, payer-driven system, this focus has led to tremendous micromanagement by health plans of health care providers including rehabilitation providers.
I believe we should let providers worry about inputs and let payers worry about outcomes. I believe that in the consumer-driven system of the future, when there is effective quality competition, payers will pay for outcomes and will let providers worry how to configure the Dr. Cope's black box to maximize outcomes. This gets back to my earlier comment that, if markets are structured appropriately with the right incentives, providers will figure out how best to provide their services both effectively and efficiently.
Q: The team concept has been important in both brain injury rehabilitation and medical rehabilitation generally. How has managed care affected the team concept and what do you see as the future for the rehabilitation team?
A: The concept of the rehabilitation team has been sacrosanct in medical rehabilitation. It embodies several important patient-care and professional values and gives expression to the notion of "interdisciplinary rehabilitation." Theoretically, it is the team's task to define the contents of Dr. Cope's black box.
With managed care, the team concept has been under attack because it is seen as a very expensive way to organize services in the face of declining reimbursement in a managed care environment. Moreover, managed care's review of each therapy or service to be rendered, has sometimes induced competition within teams as to whose skills are most needed and which personnel will be given the dollars to provide services. In short, the very collaborative nature of the team is in many ways threatened. Many providers have significantly altered their approach to teams or have abandoned the team concept altogether.
I believe that predictions about the team's demise is premature. In the current payer-driven, managed-care environment, it may be disappearing but I believe it will make a comeback, albeit not necessarily in its previous form. In a more consumer-driven system where price and quality are paramount, I believe that providers will need to assemble teams to help determine the best configuration of services the individual patient may need in order to attain a predetermined set of outcomes. Each patient, not each professional service area, will be a cost center and it will be up to the team to figure out how to maximize the outcomes in keeping with the funds available. In the future, teams may even be incentivized accordingly. If they are, you will also see some blurring of the boundaries between professional disciplines in medical rehabilitation as team members put aside professional prerogatives in pursuit of patient goals.
Q: You have indicated that we are moving toward a more consumer-driven health care system that will compete on price and quality including health and functional outcomes. What evidence do we have currently that would suggest that such a system will emerge?
A: The linchpin of a well-functioning market is a consumer who can make informed choices about price and quality. Up until recently, consumers had little information upon which to make informed choices about health plans (presuming they has a choice) or health providers. Basic data about the performance of health plans and providers have generally not been available to the public. By contrast, anyone contemplating the purchase of an automobile, for example, can always turn to Consumer Reports to obtain data about a model's past performance. I realize that some people do not like to see health care reduced to a commodity but, if we want a market-based health care system, then we do need to think about health care as a commodity--as well as any other attribute we may want to give it.
Many of us have seen consumer satisfaction surveys of health plans but they really do not tell us much. Many of these surveys are self-anointed seals of approval. The differences between health plans are marginal and most satisfaction surveys typically do not report the experiences of those who had significant health care needs and significant encounters with the health care system during the previous year.
More encouraging, I believe is the health care report card movement that is gaining momentum across the country. Health care report cards rate health plans and health providers based on health outcomes as well as consumer satisfaction surveys.
At the forefront of the health care report card movement has been the fast-growing National Committee on Quality Assurance (NCQA) in Washington, DC and more recently, the Foundation for Accountability in Portland, Oregon. NCQA is the accrediting body for managed care plans much the same way that JCAHO is the accrediting body for health providers such as hospitals. In early 1997, NCQA will be releasing its third version of HEDIS (Health Plan Employer Data and Information Set) which provides for a standard set of quality indicators for health plans. If you want to find information on any of the 200 health plans that NCQA has rated, you can locate it on the Internet at http://www.ncqa.org. Many large employers demand that health plans be accredited by NCQA before they make the health plan available to its employees.
Another important development is the publication of Health Pages, a consumer health magazine similar to Consumer Reports, which rates health plans and health providers in several large markets around the nation--Atlanta, Boston, Columbus-Cincinnati, Pittsburgh, St. Louis, Phoenix, Denver, South Florida, Los Angeles, and more to come.
One can identify many other examples of a stronger consumer-based, outcomes-oriented focus in health care: Consider the Cleveland Health Quality Choice Program which provides severity-adjusted outcomes and patient satisfaction data for 29 Cleveland-area hospitals. Consider the North Central Texas HEDIS Coalition which has developed a report card on seven HMOs on HEDIS performance measures and member satisfaction data from independent surveys. Consider how NCQA and Health Pages have combined forces in Denver to develop an HMO report card that compares the HEDIS performance results of several Denver-area health plans such as Cigna, FHP International, Kaiser, MetraHealth, Pru and Sloan Lake. Consider the Pittsburgh Business Group on Health which has spearheaded a similar cross-HMO comparison involving HealthAmerica HMO, Keystone Health Plan West, and US Healthcare.
This is only a sampling. The leading edge in the development of a more consumer-driven health care system is the large employer who is demanding that health plans, particularly managed care plans, provide standardized outcome and consumer satisfaction data. Large employers believe that they have the health care cost spiral under some degree of control and are now turning their attention to quality issues and want to know what value they are getting for their money. Small employers are still concerned mainly about price. Large employers have clout with managed care companies and have market power akin to a purchasing cooperative or a health alliance. Consider for example, the National HMO Purchasing Coalition which includes 10 employers such as Sears. All HMOs must meet the Coalition's quality specifications if the plan is to be offered to Sears' employees.
In many ways the information needs of large purchasers are similar to those of individual consumers and the information being sought by large employers are being made digestible to ordinary consumers as in the Denver market where NCQA, by working with Health Pages, is making its findings available to the average consumer.
I believe that we are entering a new era of health care accountability and that rehabilitation providers better figure out quickly how their performance data can be made digestible to the consuming public as well as to their traditional referral sources. I have many thoughts on this and only wish that we had more time to explore what should be the industry's response to this growing movement.
Q: You seem quite convinced that will eventually evolve into a more consumer-driven system. What do you see as the main threat to the emergence of such as system?
A: If there is a threat, I believe it may come from potentially excessive consolidation in many health care markets. A consumer-driven system presumes that there will be a choice of health plans and provider networks. I do not want to dwell on this but a day does not go by when one does not hear of another merger or acquisition in health care. The urge to merge is also very great in rehabilitation. Some degree of consolidation is both necessary and inevitable as excess capacity is wrung out of the system. Earlier in this interview, I indicated that an advanced managed-care market like Minneapolis-St. Paul has already consolidated into three main provider networks and some observers are now asking whether consolidation in the Twin Cities has gone too far. Excessive consolidation is a potential threat to both competition and choice.
Q: What is the role of government in developing a more consumer-driven system? Will markets self-correct?
A: The consumer-driven system of the future will not get there by itself but I do believe that there is sufficient momentum in the system to get us there.
Government has a very vital role. Government, particularly at the federal and state levels, has an important role in making sure that the conditions for a sustainable consumer-driven, risk-neutral, market-based health-care system are in place. There is no such thing as a free lunch and there is no such thing as a free market. Markets are like sports. There have to be rules, boundary lines, referees, and the power to sanction those who violate the rules in order assure fair play and a level-playing field. The problem with health care, compared to most other kinds of market, is that it more susceptible to manipulation because players will try to win by competing on risk rather than price and quality.
One important role of government is to reduce risk competition and to promote price-and-quality competition. This means that government may have to sponsor research in developing risk adjusters that can adjust prices and outcomes on the basis of case-mix; sponsor carve-outs for certain "high-risk" populations; and establish guidelines as to how health plans market their services in order to minimize risk selection. One of the most important steps for government, in the short run, is to make sure that Medicare and Medicaid, as they convert to managed care, take on the characteristics of a more consumer-driven, risk-neutral system and that they do not fall prey to the risk competition that has plagued American health care.
Finally, government also has an important role in monitoring consolidation in the health care system and to prevent excessive consolidation that undermines effective consumer-based competition. At present, I very much doubt that government has adequate resources in the Department of Justice's Anti-trust Division or in the Federal Trade Commission to monitor the current flurry of mergers and acquisitions, not only in health care, but also in other industries such as the telecommunications and the banking and financial services industries.
Q: Let's shift the discussion abound another issue important to people with brain injuries. What about long-term supports for people with brain injury? It seems that we still a long away from having a continuum of services available to an individual with a brain injury over many year's of individual's remaining life?
A: This is a frustrating question especially for observers such as myself who believe that there has to be a good answer lurking somewhere. The integration of acute and long-term services has probably been the most vexing issue in American health and social policy. There have been many interesting proposals, demonstration projects, and population-specific programs. The list is long. None, however, seem to form the basis for a more unified social policy response that can take into account the diversity of individual needs and financial circumstances and can create the societal consensus that will sustain such a social policy politically. Our society's willingness to develop a sound long-term services policy is limited by the perception of many people that their individual or family risk for needing long-term services, apart from nursing home care in old age, is fairly minimal and distant. Most people, especially younger people, see such needs as remote and prefer not having to deal with it. As a result they do not plan for it privately nor do they support it politically.
My first inclination is to think about how sound market-based solutions can be forged but I frequently run into one or more limitations that undermine market solutions. I believe that we can bring more market-based solutions to some government-sponsored programs that will serve the interests of both consumers and public accountability. As many of your readers know, I have been a proponent of publicly consumer-directed long-term services but I believe that current approaches have not dealt adequately with limitations on both the demand and supply sides of the market that require some level of government sponsorship to rectify. I believe that long-term services will always require some combination of public and private sponsorship in order to create effective markets and to make the costs palatable to the general public and affordable to the individual or family.
Q: Overall though, you paint a fairly bright view for the future, do you not?
A: I am optimist. There is much doom and gloom among both consumers and providers about managed care. Much of it is understandable but we do need to look to the future. While we are mired in the travails of the current system, I see a new system emerging one that will be in the interests of both consumers and providers. But, as I said before, the new system, while inevitable, will not come by itself. If the new system is to be responsive to the needs of TBI consumers and providers, the TBI community needs to organize itself and become a player in the emerging consumer-driven health care system of the future. The TBI community needs to make sure that the quality indicators that drive the new system address those issues that speak to the needs of TBI consumers. It will take the goodwill of many people and will require the participation of government to help create the level-playing field about which I spoke.
The shift from a payer-driven system that competes on a price and risk to the consumer-driven one that competes on price and quality is an exciting one. Quality competition is where the interests of both consumers and providers converge.
Perspective and Analysis--Market Forces: Medical Rehabilitation Undergoing Major Shakeup in Advanced Managed Care Markets
Gerben DeJong, Ph.D.; Ben Wheatley, B.A.; and Janet Sutton, Ph.D.
Managed Care Reporter 2:138-141 (February 7, 1996)
The fast-growing $27 billion medical rehabilitation industry is undergoing its greatest transformation since the traditional inpatient model of medical rehabilitation came of age in the 1980s. Nowhere is this transformation more evident than in the most advanced managed care markets such as San Diego, Minneapolis-St. Paul, and Worcester, Mass. These markets presage the changes that are beginning to hit medical rehabilitation in other markets as managed care makes its march through the American health care economy.
For many years, medical rehabilitation occupied a largely unnoticed niche in American health care, providing restorative services to people who acquire a disabling impairment because of a congenital condition, a traumatic injury, an acute illness, or a chronic health condition that limited their ability to function independently. Through an array of therapeutic services, such as physical, occupational, and speech therapies, and through the use of prosthetics, orthotics, and other assistive technologies, medical rehabilitation services enabled people with impairments to manage their own daily needs and, whenever possible, return to an active and productive lifestyle.
Since the mid-1980s, organized medical rehabilitation has become a major player in the post-acute continuum of health care services. The number of inpatient programs more than doubled in the ten-year period since then. From 1985 to 1994, the number of free-standing rehabilitation hospitals increased 175 percent from 68 to 187 hospitals, and the number of rehabilitation units based in acute-care hospitals increased by 118 percent from 386 units to 804 units. With this growth, medical rehabilitation physicians, know as physiatrists, enjoyed increasing compensation and new-found recognition among their physician peers.
With the dramatic growth of managed care, however, the Golden Age of hospital-based medical rehabilitation has come to an abrupt end. This change of fortune is particularly evident in the more advanced managed care markets often considered harbingers of things to come. To find out what has been happening to medical rehabilitation providers in these markets, the National Rehabilitation Hospital (NRH) Research Center, as part of a grant from the National Institute on Disability and Rehabilitation Research, conducted dozens of interviews with leading payers, providers, and health care experts in the San Diego, Minneapolis-St. Paul, and Worcester areas. Researchers supplemented these interviews with data from local newspapers, the trade literature, published market data, and other third-party information sources.
MARKETS CONSOLIDATE, PROVIDERS SCRAMBLE
In all three markets, according to the Group Health Association of America, well over 50 percent of the total population is now enrolled in health maintenance organizations (see table). Managed care has also penetrated the senior population through the use of at-risk Medicare contracts. Seniors are an important market segment for inpatient rehabilitation providers. Nationally, these providers depend on Medicare for 70 percent of their revenues.
In two of the markets, San Diego and Minneapolis-St. Paul, high levels of managed care penetration have precipitated the consolidation of health care providers into three or four competing integrated provider networks and have forced rehabilitation providers to realign themselves accordingly.
In the San Diego market, the dominant provider networks now include Sharp Health Care, Scripps Health, and the University of California San Diego or UCSD Healthcare Network. Both Sharpe and Scripps include medical rehabilitation providers who, as network members, are in a strong position to capture medical rehabilitation patients.
Large unaffiliated for-profit rehabilitation providers such as the San Diego Rehabilitation Institute (SDRI) and Continental Hospital, part of the national Continental Medical Systems chain, are scrambling to retain market share by diversifying their rehabilitation capacity to include lower-cost settings, such as subacute beds and outpatient care, to make themselves price competitive with the major networks. Both SDRI and Continental are for-profit providers that entered the San Diego market in the late 1980s and early 1990s mainly as inpatient rehabilitation providers.
In Minnesota--dubbed the land of 10,000 mergers--the consolidation movement includes mergers between provider networks and health plans, effectively blurring the line between providers and payers. The Minneapolis-St. Paul market has consolidated into three payer-provider networks: Blue Cross and Blue Shield of Minneapolis, Allina Health System Inc., and HealthPartners which, combined, control 78 percent of the market.
The Allina system includes Sister Kenny Institute, a long-standing and well-recognized name in the nation's rehabilitation industry. Sister Kenny appears well positioned mainly on the strength of Allina's market position. By contrast, North Memorial Hospital has sought to maintain its independence but finds itself effectively frozen out of many rehabilitation admissions. Once patients participate in one of the larger systems, they usually stay in those systems.
In a much smaller market, Worcester's leading health plan has been the Fallon Community Health Plan, a group-model HMO that has also been caring for Medicare beneficiaries since 1980. Although able to contain costs, Fallon experienced very little price competition until Boston area-based Pilgrim Health Plan (now, Harvard Pilgrim Health Care) entered the central Massachusetts market in 1994 and New Hampshire-based Healthsource Inc. entered in 1995 by acquiring Central Massachusetts Health Care of Worcester.
Fairlawn Hospital remains Worcester's only major inpatient rehabilitation provider, but it has seen a decline in census as HMOs have looked to subacute rehabilitation providers. Fairlawn has responded by making strategic alliances through shared ownership. Fairlawn is now one-third owned by Fallon and one-third owned by Advantage Health, a large publicly traded rehabilitation chain.
PROVIDERS INTEGRATE VERTICALLY
Thus, one common denominator across the three markets has been the desire of rehabilitation providers to integrate vertically with larger health systems for fear of losing patient referrals from acute-care hospitals if they remain outside large systems. Several rehabilitation providers have remained independent either from conscious choice or from lack of foresight. One informant in the later category said: "We thought we were God's gift because we were the premier hospital for many diagnoses." Most providers have come to realize that fierce independence often comes at a price--survival.
Vertical integration is also occurring within rehabilitation as providers assemble a broader array of rehabilitation settings that will enable them to move patients more quickly to lower-cost settings at the earliest possible moment. In addition to the traditional inpatient program, the "rehabilitation continuum of care" increasingly includes a subacute program, an outpatient program, and a home-based rehabilitation program. Informants often spoke about a "seamless" continuum of care in which physicians and therapists follow the patient as he or she moves into less-structured settings.
HOSPITAL-BASED REHABILITATION DECLINES
The economic driver in establishing a wider array of rehabilitation settings is simply costs, particularly the cost of traditional inpatient rehabilitation, which can quickly reach $1,000 per day and more. In many instances, managed care payers bypass inpatient rehabilitation altogether and insist that patients traditionally seen in inpatient programs obtain their rehabilitation in subacute units instead. Inpatient rehabilitation's "bread-and-butter" patients, such as older patients with a stroke or hip fracture--which previously made up more than 50 percent of traditional inpatient programs--are now going to subacute settings instead. In the three highly managed care markets, inpatient programs are being reserved for a handful of impairment groups such as persons with severe traumatic brain injury, spinal cord injury, and younger persons with stroke.
Inpatient utilization has declined dramatically in the three advanced managed care markets. Occupancy rates are off by 40 percent or more in some facilities. An average length of stay of 30 days or 35 days only five years ago is now down to 19 day or 20 days, but appears to be leveling off because, as one respondent indicates, "results were falling off as well." In the face of declining lengths of stay, some observers have begun to question whether inpatient rehabilitation, as traditionally organized and practiced, may be a vanishing breed.
SUBACUTE REHABILITATION BOOMING
As the utilization of inpatient rehabilitation has declined, subacute rehabilitation has become the new growth industry in highly managed care markets. Respondents in the three markets report that "there is a huge, huge explosion of subacute providers." "Subacute is booming everywhere." One informant in the Worcester area reports that "there are five brand-new subacute facilities within a 15-minute drive."
The growth of subacute rehabilitation appears to spring from three sources of sponsorship. First are the traditional inpatient providers who have diversified by offering a subacute alternative. Second are existing skilled nursing facilities (SNFs) that have added a rehabilitation component in response to what is seen as a new market opportunity. And third are the fast-growing national for-profit chains, such as Manor Care, NovaCare, and TheraTx, that have anticipated the demand for subacute rehabilitation in more highly managed care markets.
Subacute providers typically price their services at about $300 to $500 per day, half the inpatient rate. People usually remain in subacute care longer than they do in traditional inpatient rehabilitation, however.
INPATIENT PROVIDERS RESPOND BY SLASHING COSTS
Traditional inpatient providers insist that predictions of their demise are premature and have responded by slashing their costs in order to become more price competitive. The Sharp system in San Diego, for example, reduced its administrative overhead by eliminating 100 positions through layoffs and attrition and by removing entire levels of management. "On a system basis," said one respondent, "there's been a radical reorganization, and we are doing everything we can to reduce our costs...It's moving very, very quickly."
At Sharp, managers are now responsible for multiple entities throughout the system. There is no longer a therapy director at every site within the system, but one director for the entire system. One respondent characterized the approach as being "system-oriented rather than entity-based." At Fairlawn Hospital in Worcester, the staffing mix has changed. Fairlawn has eliminated LPNs entirely from its mix of RNs, LPNs, and nurse aides. Many providers have resorted to using more therapy extenders and fewer higher-salaried professional therapists.
THERAPY TEAMS REORGANIZED
The need to slash costs has prompted inpatient providers to reevaluate one of rehabilitation's most cherished institutions, the "interdisciplinary team approach" to rehabilitation in which each discipline or department develops a treatment plan that is reevaluated and renegotiated in weekly team meetings. One facility in the Minneapolis-St. Paul market has adopted what it calls a "transdisciplinary team approach," in which the team comes together initially to identify "the barriers to discharge" and to designate the steps that each therapy will take to remove the barriers identified.
Other providers have turned to one of health care's latest rages, critical pathways, as a way of making treatment plans more predictable and as a way of representing the expectations for each patient to managed care payers. Providers are attempting to break down the boundaries and turf issues between the professional therapies that often add to the cost of doing business.
NICHE MARKETING
Rehabilitation providers have learned that reengineering, cost-cutting, and downsizing are not enough. These internal adjustments cannot substitute for the market savvy that is needed in a rapidly changing market. As managed care markets mature and become crowded with new entrants, rehabilitation providers are learning to create niches and to emphasize their uniqueness in contract negotiations.
According to one marketing director, rehabilitation providers will, in the future, offer a menu of niche services. "They have a short window of opportunity to become specialists in wound care, HIV, etc. If they can franchise it, they can ride that market segment for a while. They have to make themselves have value." "They need to stop thinking of the rehabilitation hospital as the $35 million centerpiece of their business."
Another rehabilitation market strategy has been to form alliances and joint ventures with somewhat similar competitors in order to shore up market share and to develop a unique continuum of services that will be attractive to payers. Such market strategies also allow competitors to eliminate duplication and achieve economies of scale. As one respondent indicated: "Why do you have to have cardiac rehabilitation services at four or five locations in the community when you could funnel all of that into one and be more efficient and have better outcomes too?" The respondent did not address the potential restrain-of-trade and anti-trust issues implicit in horizontal integration strategies.
FULL CAPITATION YET TO COME TO REHABILITATION
With managed care, the fee-for-service and cost-based methods of rehabilitation payment are vanishing rapidly, but full case-rate capitation has yet to come to rehabilitation in any significant way. Most acute and subacute rehabilitation providers in the three markets studied are being paid on a fixed per-diem basis, where length of stay is negotiated depending on patient status and progress.
One rehabilitation hospital reports being paid a declining per-diem amount the longer the patient remains in the hospital. For a given type of patient, for example, the hospital receives twice as much payment for Days 1 through 7 than for Days 31 through 35. "In effect," said one respondent, "it's risk sharing because once you go beyond the 21st day, you're getting a reimbursement rate that's well below your cost. It's not a DRG, but it's certainly a front-loaded system to get your patients out quickly..."
Capitation arrangements, where they do exist, typically do not extend yet to the individual rehabilitation facility. An entire provider network may be capitated for a health plan member's hospitalization, but that hospitalization may include all types of inpatient care--acute care, rehabilitation care, psychiatric care. Interest in full case-rate capitation for rehabilitation specifically remains limited to niche programs with considerable experience serving well-defined populations; for instance, people with spinal cord injury.
PAYERS LACK SOPHISTICATION ABOUT OUTCOMES
Informants in the three markets report that functional outcomes are not, for the most part, being considered by payers. Quality is more or less assumed. In contract negotiations, informants say, managed care payers give price much greater consideration. One informant said, "Frankly, in this market place, nobody asks, nobody cares [about outcomes]. While this is a huge market in terms of HMO penetration, the level of sophistication still is not where it should be."
Informants complain that payers are only looking at price; they do not consider functional outcomes gained per dollar. Hospital-based providers in particular would like to see payers give more consideration to outcomes and functional gains per dollar spent in order to create a more level playing field between them and their subacute competitors.
Some providers report that payers are beginning to ask the right questions, especially for people with catastrophic injuries. They are asking, "Do you have outcomes for your brain-injured patients? Do you have critical pathways for your brain- and spinal-injured patients?
IMPLICATIONS FOR PROVIDERS IN OTHER MARKETS
Most rehabilitation providers are already experiencing, to some degree, many of the trends in leading managed care markets. Providers in other markets would do well to consider the experiences of their counterparts represented in the three-market study.
A central finding is that traditional hospital-based rehabilitation should no longer be considered the focal point of a rehabilitation service delivery system. Diversification attempts that merely remake the rehabilitation hospital as the hub of a larger multifacility program will fall short of the changes required by the new marketplace. The need for rehabilitation hospitals will continue, but is therapeutic mission will be more focused and targeted.
Traditional rehabilitation providers will thrive to the extent to which they form strategic alliances that will guarantee them a supply of patients. To be nonaligned, a rehabilitation hospital will have to be a fairly specialized center of excellence with a national or broad regional market base. Very few rehabilitation programs qualify. Whether national or local in focus, rehabilitation programs of all kinds require a therapeutic focus or identity that separates them from their competitors.
Despite the doom and gloom that grips parts of the rehabilitation hospital industry, demographic demands will require that health systems include a substantial rehabilitation component in order to accommodate a rapidly growing disabled population, especially in the older age groups. Rehabilitation will remain a growth industry. The point of market saturation has yet to be determined.
The greatest change demanded by the managed care revolution is the change in mind set. In the former fee-for-service, cost-based reimbursement systems, more was better: the more service rendered, the more revenue produced. In the emerging fixed-fee or fixed-cost environment, less is better: the less service provided, the more net income produced. Managed care has reversed the financial incentives governing provider behavior in the past.
IMPLICATIONS FOR MANAGED CARE PAYERS
The question remains whether quality and outcomes are being sacrificed when financial incentives are reversed. In the drive for lower costs and prices, purchasers may be overlooking the product they are purchasing. Managed care payers would do well to demand quality and outcome data upon which they can make comparisons across provider networks. Rehabilitation providers are far more sophisticated in outcome measurement than purchasers assume. Standardized and reliable, cross-provider, functional outcome data are already available, and managed care payers would do well in making these data one of the bases upon which they make their purchase and payment decisions.
Gerben DeJong, Ph.D., Director, Ben Wheatley, B.A., Research Assistant, and Janet Sutton, Ph.D., Senior Research Associate, Research and Training Center on Medical Rehabilitation Services and Health Policy, NRH Research Center, Medlantic Research Institute, Washington, DC.
NOTES
The production of this article was supported in part by the NRH Research Center's Research and Training Center on Medical Rehabilitation Services and Health Policy (RTC-MRS&HP) which is funded with a grant from the National Institute on Disability and Rehabilitation Research (NIDRR). Grant #H133B40025.
The views expressed in this article are those of the authors and do not necessarily reflect the views of the NRH Research Center, National Rehabilitation Hospital, Medlantic Research Institute, or any other organization with which the authors are affiliated.
| TABLE 1. HMO Penetration | |||
|---|---|---|---|
| Market | 1991 | 1994 | Increase |
| San Diego | 36.0% | 53.8% | +49.4% |
| Minneapolis/St. Paul | 46.0% | 55.1% | +19.8% |
| Worcester | 51.0% | 58.8% | +15.3% |
Surviving Managed Care and Preparing for the Next Revolution in American Health Care
Gerben DeJong, Ph.D.
February 24, 1996
INTRODUCTION (Rehab 2000=heads up)
- Purpose of presentation
- Outline what is happening in the larger health care system;
- Tease out some of the implications for people with disabilities, the allied health professions, and the medical rehabilitation industry; and
- Identify some of the steps that both consumers and providers can/must take to reposition themselves in a manner that will
- Make health care and rehabilitation more responsive to the consumer,
- Address the economic concerns of providers, and
- Respond to the financial constraints of the payer community and the public at large..
- Thesis
- As we move toward managed health care, there is much doom and gloom, but there are also enormous opportunities for both the consumer and the provider alike.
- As we move toward managed care, health care providers across the board are scrambling to reposition themselves in a drastically altered marketplace. In the short term, providers need to do what they have to do to survive.
- In the long-run, provider interests are best served by working with the consumer community. In a health care system that, historically, has been provider-driven, providers have not looked to the consumer as vital to their economic interests.
- Moreover, consumers, especially those with disabilities and chronic health conditions, have interests that are not particularly well-served by the financial incentives inherent in managed care.
- I believe we are entering a special period in which the interests of consumers and the interests of providers are beginning to converge on several key points. If we fail to seize this moment, I believe we will loose an historic opportunity to unlock the promises of a truly market-based health care economy.
- Note:
- Where I am coming from. Originally trained as an economist. A strong believer in a market-based health care system. Also believe that managed care is a necessary corrective to the excesses of the past. The problem with managed care today is that it is being hoisted on a health care system that violates all the precepts of a competitive market system. As such, managed care is likely to intensify the risk-based competition that is so detrimental to the well-being of people with disabilities and chronic health conditions.
- Objectives
- Outline the extent to which managed care is rapidly becoming the dominant method of health care financing
- Geographically
- By payer
- Private sector
- Public sector
- Medicare
- Medicaid
- Outline how managed care is reshaping health care system and the rehabilitation industry
- Health care in general
- Medical rehabilitation
- The buzz words of the 1990s
- Mergers, acquisitions, alliances
- Discuss the emergence of the consumer/ demand side of the market and identify some of the steps needed to strengthen it
- Identify some additional steps that need to be taken in order to secure a consumer-driven, risk-neutral, market-based system
- Provide a brief summary of action steps
- Close by noting how collaboration between consumers and providers is essential to achieving a health care system that we can live with
- Outline the extent to which managed care is rapidly becoming the dominant method of health care financing
I. THE GROWTH OF MANAGED CARE
- Geographically
- Highest penetration in West and Northern states (Minnesota and eastward); penetration varies greatly within states. See outdated map in Appendix.
- By payer
- Private sector (Slide 5)
- 1993--26% of private health insurance market=managed care
- 1994--38%
- 1995--50%?
- 65% of employees in mid to large firms were enrolled in managed care in 1995 up from 29% in 1988.
- 2000--85-95%
- Public sector (Medicare and Medicaid)
- Growth in Medicare and Medicaid programs
- Medicare
- Medicaid
- Threat to federal and state budgets
- Federal budget (see pie chard in Appendix)
- Medicare, Medicaid, and interest on the federal debt are the 3 big drivers of the current deficit
- This is why the Clinton Administration made health care reform its #1 priority
Without bringing health care under control, one cannot bring the federal budget and deficit under control-unless one is willing to make deep/ painful cuts in other parts of the budget. That is what is happening now. - The arithmetic of the federal budget and the growth of the Medicare and Medicaid programs make these programs an obvious and inevitable target.
- Federal budget (see pie chard in Appendix)
- Managed care provides politicians a great deal of political cover.
- By cutting costs and services through managed care, politicians can let "market forces" make the hard decisions for them.
- No politician is willing to go out front to propose specific program cuts in health care for fearing of stirring up one constituency or another.
- Clinton's health care reform program looked to managed care to make some of the hard decisions.
- The Republicans are doing the same. Not willing to face the wrath of the voters, particularly older voters, when it comes to cutting the Medicare program.
- Bottom line: Managed care, regardless of its excesses or shortcomings, will have the support of the political process as well as the momentum of the economic market place.
The politics of the federal deficit and the economics of health care converge on managed care. Managed care= harmonic convergence of deficit politics and health economics.
- Managed care penetration in Medicare and Medicaid
- Medicare
- End of 1994, 9% of Medicare beneficiaries enrolled in managed care
+32% increase in 1995
+45% increase in 1996 (projected) - By 2000, 25-85% of Medicare will be managed care (estimates)1
- Managed care penetration within selected markets
- End of 1994, 9% of Medicare beneficiaries enrolled in managed care
- Medicaid
- States are moving rapidly to convert their Medicaid programs from traditional FFS to managed care programs (Lewin-VHI, 1995)
- All but 8 states have Medicaid managed care programs of some type
- One-third are now in FFS primary care case management (PCCM)
- By 1998, 85% of Medicaid participants (exclusive of those in nursing homes) will be in some form of managed care.
- §1115 and §1915 waivers. TennCare, Michigan, Rhode Island, New York
- TennCare
- Currently 7 HMOs and 5 PPOs
- 400,000 Medicaid subscribers and 800,000 new eligibles
- Medicare
- Growth in Medicare and Medicaid programs
- Private sector (Slide 5)
II. HOW MANAGED CARE IS RESHAPING HEALTH CARE AND ITS CONSEQUENCES FOR ALLIED HEALTH AND THE REHABILITATION INDUSTRY
- Bear with me here. Trying to make a point which will become more obvious later.
- Health care in general
- Economic drivers
- Economics of MC is forcing individual health care providers to become part of a network of providers that can provide the full continuum of care. The drive toward "vertical integration" and "integrated service networks" (ISNs).
- Minneapolis-St. Paul market
90% MC pentration
3 main networks
- Minneapolis-St. Paul market
- To remain price competitive, provider networks must keep their costs down (and their risks low).
- Cost- and profit-sharing mechanisms are encouraging individual providers to eliminate unnecessary services; reduce hospitalizations in particular.
- The primary care physician (PCP) gate-keeper has become a central figure in determining who gets access to what and how much.
- The PCP shares much of the financial risk. His/her compensation/bonus will depend in large part upon the savings achieved by the network of which he/she is a part.
- Economics of MC is forcing individual health care providers to become part of a network of providers that can provide the full continuum of care. The drive toward "vertical integration" and "integrated service networks" (ISNs).
- Shifting the competition
- Shifting away from prestige competition
- Historically, providers competed on the basis of the latest technology, their academic affiliations, the credentials and size of their medical staffs, their level of specialization, and the bed-size of their institutions.
- This prestige competition has helped to make American health care the most sophisticated and technologically advanced in the world, but it has also led to tremendous excess capacity that has made American health care frightfully expensive.
- Shifting to price competition
- In the new health care system, price has replaced prestige as the defining element in competition
- "... the hospital industry still has a long way to go before excess capacity, costs and waste are fully wrung out of the system."
- Risk competition still remains
- Marketing to groups that are, on average, younger and healthier
- Tweaking benefit plans to attract lower-risk populations
- Discouraging high users from joining or continuing with their plans once large claims are made
- Passing on high-cost users to other health plans
- As a result of risk-based competition, certain groups will be underserved, excluded, or simply priced out of the market.
- Especially true in individual and small-group health markets. (Scism, 1994)2
- Shifting away from prestige competition
- Shifting ownership status: Not-for-profit --> for-profit
- Physician groups
Physician groups tend to be undercapitalized; take too much money out of the group; forced to go to Wall Street to acquire capital needed to:- Finance network expansion
- Finance new capital equipment needed to keep services in-house and to reduce the need to refer patients to hospital-based facilities
- Hospitals
- Debt financing (used by not-for-profits) becomes part of the hospital cost structure that must be recovered by billing and revenues.
- Debt financing cannot as compete well with equity financing.
- Hospitals need major infusions of capital in order to retool or upgrade their facilities and to acquire nonhospital partners.
- Hospitals are prone to look to Wall Street for the financing they need.
- Once publicly traded, facilities are subject to buy-outs and mergers and all the other things that can happen on Wall Street.
- Physician groups
- Economic drivers
- Impact on health care providers in general
- The "bleeding edge" of managed care
- Hospitals
- Some cutting costs by 25% or more in order to retain market share
- Elimination of excess capacity
- Example: hospital beds in Minneapolis-St. Paul market
1981 9,188
1984 7,436
1992 5,348 -42%
- Example: hospital beds in Minneapolis-St. Paul market
- Physicians
- Reduced need/demand for specialty medical care
- Year 2000 surplus of 115,000 specialists (CGME)
- Year 2000 surplus of 165,000 specialists (Weiner, 1994). See table in Appendix.
- Lewin-VHI study on demand for PM&R physicians
- MCOs deselecting physicians on short (30-90 days) notice.
- "Termination-without-cause" clauses.
- For-cause reasons being expanded.
- Physician income
- Income decline
- Modeling income decline
- Shifting from fixed pay to variable pay
- Formation of for-profit, publicly traded national physician corporations
- Physicians selling practices to hospitals to avoid overhead, personnel, and paperwork costs
- Reduced need/demand for specialty medical care
- California health systems and networks
- Even largest medical groups and networks appear to have little market leverage with respect to price.
- Even the best, most highly acclaimed, systems are having difficulty
- Impact on medical rehabilitation in particular
- Providers being forced to reduce costs in order to remain a recognized provider within a health plan (including the referral of patients)
- LOS is shortening dramatically in inpatient medical rehabilitation facilities
- Therapy teams reorganized. The interdisciplinary team model under attack.
- Growth of nonhospital alternatives (see table in Appendix).
- Outpatient programs incl. day treatment
- Subacute, SNF-based rehabilitation
- Home-based rehab
- Vertical integration: Medical rehabilitation being forced to become part of larger health care networks with a continuum of rehabilitation settings.
- Horizontal integration: Medical rehabilitation providers joining forces with like providers in order to acquire market share and strengthen position for managed care contracts
- More for-profit providers
- See article from Managed Care Reporter in Appendix: "Medical Rehabilitation Undergoing Major Shakeup in Advanced Managed Care Markets."
- Buzz words
- Capitation, contact capitation
- Incentive compensation
- Pod-level risk pools
- Market share
- Vertical integration
- Horizontal integration
- Integrated service networks
- Partnering, joint ventures
- Mergers/acquisitions/consolidations
- Reegineering, downsizing, restructuring
- Impact on consumers
- Consumers feel they have lost choice and access
- Employers offering fewer or no choices of health plans
- Health plans limiting the choice of providers
- Both consumers and providers are concerned that managed care may undermine traditional bioethical principles such as those that relate to (a) patient autonomy and (b) the physician's fiduciary responsibility to the patient (Biblo, 1995; Council on Ethical and Judicial Affairs, 1995).
- Mergers, acquisitions, alliances
- Acute hospital industry (Skolnick and Prime, 1994)
Columbia-HCA Healthcare Corp (COL) (see drawing in Appendix)- Grown from 20 hospitals to 340 hospitals & 100+ freestanding surgery centers in just 4 years; $22 billion in annual revenues.
- In late April, completed its $3.3 billion takeover of HealthTrust, a 116-hospital system and is moving its headquarters from Louisville to Nashville (Hilzenrath, 1995)
- Seeks to operate as many as 500 hospitals in a few years.
- Going international. Joint venture with (a) Britain's largest independent health care provider, General Healthcare Group PLC and (b) a health unit of the French conglomerate Groupe Generale des Eaux (Tomsho, 1995).
Columbia/HCA has "an appetite that is seemingly insatiable." - Columbia/HCA's cardinal rule of acquisitions:
"Never pay for an empty bed unless you are buying the facility to close it."
Why buy a facility you intend to close: eliminate competition; "it pays only for the ability to fill up beds in existing facilities by closing the hospitals that it buys."
- Home care industry
- Size
- $22-billion industry, 1995
- $40-billion industry, 2000
- Names
- Coram (CRH)
- RoTech Medical (ROTC)
- Lincare Holdings (LNCR)
- American HomePatient (AHOM)
- Mergers and acquisitions in home health services
- From 1992-94 there were $3.7 billion of mergers and acquisitions in the home care industry.
- In summer 1995, Manor Care, a leading nursing home chain, headquartered in silver Spring, MD, purchases a controlling interest in Home Health Inc. for $42 million.
- The recent Homedco/Abbey merger makes it the largest home care company with revenue of more than $1.1 billion.
- Size
- Medical rehabilitation industry
- Horizon/CMS, formerly Horizon Healthcare
- In February 1994, Horizon Healthcare buys Greenery Rehabilitation Group (20 facilities and 2,800 beds)
- In August 1994, Horizon Healthcare acquires 13 peopleCare Heritage nursing facilities with 2,200 beds in the Dallas area
- In 1995, Horizon Healthcare buys Hillhaven (nation's second largest nursing home chain, ($1.5 billion in annual revenue)
- In March 1995, Horizon Healthcare acquires Total Rehabilitation, Inc. and Rehabilitation Network, Inc. in Michigan for $6.5 million of Horizon common stock
- In June 1995, Horizon Healthcare acquires buying Continental Medical Systems for $502 million
- Later Horizon/CMS (new name) purchased Pacific Rehabilitation & Sports Medicine, Inc. for $62 million
- HealthSouth = the Columbia/HCA of the rehabilitation industry
- Started in 1984; went public in 1986 with 7 facilities and $12 million in annual revenues
- In September 1994, HealthSouth buys 30 NME hospitals for $300 million cash
- In spring 1995, HealthSouth buys Nova Care hospitals
- In December 1995, HealthSouth buys AdvantageHealth for $325 million3
- In 1995 HealthSouth acquired 130 independent rehabilitation centers
- As of the end of 1995, HealthSouth operates 850 outpatient and rehab facilities in 44 states with projected revenues of $2.5 billion in 1996.
- It now controls about 40% of the nation's rehabilitation hospitals, twice the share of its nearest competitor, Horizon/CMS.
- Growth of subacute providers such as Nova Care and Theratx
- Horizon/CMS, formerly Horizon Healthcare
- Reading (tongue in cheek)
- If you really want to know what is going on in health care, don't read the New England Journal of Medicine or any of the medical literature, read the Wall Street Journal.
- Perhaps time for the Archives of PM&R and the Journal of Head Trauma Rehabilitation to develop investment reports that includes
- Annual and quarterly sales
- Quarterly earnings
- Earnings per share
- High and low stock prices over the last 12 months
- Etc
- Consider following statement from a stock analyst report (name of company has been changed):
"In our opinion our opinion, the ABC Rehabilitation Inc. has maintained impressive rates of internal growth. It is noteworthy for its efficient operations, high margins, excellent receivables management and tremendous cash flow, which have in turned enabled it to make acquisitions without leveraging its balance sheet. While ABC has not actively pursed partnerships to broaden its services horizontally or vertically to reposition itself for managed care, its well-run operations could make it attractive to an acquirer ... We recommend ABC as a buy."
- What's missing from this statement?
- There is no sense of the product, the people who produce it, the people who use it, and its future viability. No sense of the quality of the product.
- There is no sense of the consumer, the drivers of the demand for the services
- There is no sense of the producer of the services, i.e., the professionals in terms of their training, commitment, philosophy, competence, productivity. Human capital not considered.
- It assumes that the driver is quarterly earnings, potential for being a take-over target.
- The statement above seems almost vacuous.
- Yes, efficient operations, decent margins, good receivables management, and excellent cash flow are essential to the well-being of any organization but they cannot replace the fundamentals related to consumer demand, quality of services, and price.
- Nor does it give you a clear picture of the market fundamentals, i.e., the need/demand for the product nor the supply within a given market area.
- You cannot get an adequate read of an organization and its services merely by looking at the brochures and videos produced by the marketing department nor by merely reading the financial statements produced by the accounting department.
In capital markets, these departments are in the business of perception management - they want to create an image of an organization as dynamic and fiscally healthy. They do not necessarily give you a true picture of what is actually happening.
- Restructuring of the health care system = the privatization of health care reform
- Today's shake-out is akin to:
- The shake-out in the banking and financial services industry during the late 1980s and into the 1990s on the heels of the S&L crisis
- The restructuring of the communications industry starting with the break up of AT&T a decade ago and continuing with the convergence of computer, cable, and telephone technologies in the 1990s
- Acute hospital industry (Skolnick and Prime, 1994)
III. EMERGENCE OF THE CONSUMER/DEMAND SIDE OF THE MARKET AND THE STEPS NEEDED TO STRENGTHEN IT
- Historically, consumer side has been weak but the role of the consumer is becoming stronger (as we will see later)
- An informed consumer is essential to a well-functioning market-based system.
- Perfect knowledge = key assumption in the economic theory of perfect competition.
- A market without informed consumers is not a "free market" in the real sense of the term.
- We cannot have market-based solutions to the problems of our health care system without an informed consumer.
- The champions of market-based solutions are being disingenuous when they do not at the same time champion the consumer and his/her right to make informed decisions about health plans and health providers.
- What the champions of market forces really mean is the forces of capital markets, i.e., Wall Street. In my humble opinion, Wall Street is often ill-informed about the fundamentals of health economics. Too much of what happens in health stocks is fueled by the perceptions created by high-flying hospital company CEOs, by marketeers, and by the expectations created by stock analysts' reports. Stock prices often move on the most flimsy information.
- Consumer choice is important at two different stages/levels
- When choosing a health plan
- The more important choice
- Consumers have most clout when choosing a health plan
- When choosing a provider
- Presumes that there is a choice of provider within a health plan or health network
- Consumer choice also constrained by gate-keeper referral
- When choosing a health plan
- Consumer knowledge being strengthened
- Consumer satisfaction
- Ratings of individual health plans
- Ratings of individual providers
- Health outcomes ("report cards")
- For health plans
- For health providers
- Examples:
- Washington, DC area's Consumer Checkbook.
- National Committee for Quality Insurance (NCQA) HEDIS 2.5 (Health Plan Employer Data and Information Set). HEDIS 3.0 to be released in early 1997.
Information on 200 NCQA-rated health plans available on the Internet at http://www.ncqa.org - Health Pages which currently rates health plans and health providers in 5 markets (Atlanta, Boston, Columbus-Cincinnati, Pittsburgh, St Louis) and was scheduled to start in 4 other markets starting this fall (Phoenix, Denver, S Florida, Los Angeles)
- Cleveland Health Quality Choice Program - outcomes and pt. satisfaction among 29 Cleveland area hospitals. Includes severity adjustments.
- North Central Texas HEDIS Coalition developed a report card on 7 HMOs on HEDIS performance measures and member satisfaction data from independent surveys.
- Denver - NCQA and Health Pages released an HMO report card comparing HEDIS performance of Denver-based Cigna, FHP International, Kaiser, MetraHealth, Pru and Sloan Lake.
- Pittsburgh Business Group on Health spearheaded a similar cross-HMO comparison involving HealthAmerica HMO, Keystone Health Plan West, and US Healthcare.
- Consumer satisfaction
- Leading role of the large employer
- Demanding that health plans, particularly managed care plans, provide standardized outcome and consumer satisfaction data
- Large businesses more likely to demand this information than small businesses. Smaller employers are mainly concerned about price.
- Have market power akin to purchasing cooperative or health alliance
- National HMO Purchasing Coalition involving 10 employers, e.g., Sears. All HMOs must meet Sears' quality specs
- Information interests of large purchasers and small consumers are, in many ways, similar
- Jackson Hole II, June 1995:
- "Monitoring quality = the next battlefield."
- Demanding that health plans, particularly managed care plans, provide standardized outcome and consumer satisfaction data
IV. IMPLICATIONS FOR REHABILITATION AND ALLIED HEALTH PROVIDERS
- The price imperative (short-term)
- The quality imperative (long-term)
- Providers will be bargained down by payers if the competition remains largely on the basis of costs and price.
- It is in the provider's interest to see that the competition shifts from one largely based on price to one that is based on price and quality (i.e., consumer satisfaction and outcomes)
- Price and quality competition is in the interest of both the consumer and the provider. Here is where the interests of consumers and providers converge.
- The challenge for rehabilitation: How consumers choose a health plan
- One of the great challenges facing medical rehabilitation in a consumer-driven health care system is how to reach out to, and communicate with, the consumer who is making a health plan choice.
- Most consumers, especially younger ones, never envision a need for medical rehabilitation services and many will not even know what these services are. The need for medical rehabilitation services is often considered by the average consumer to be a remote possibility and, as such, will not be carefully scrutinized by the consumer when making a health plan decision.
- Thus, consumers are not likely to make much of an investment in learning about rehabilitation and the quality of various providers within plans when making a health-plan choice.
- Four actions
This state of affairs will require four actions on the part of the medical rehabilitation industry:- The industry will need to develop, in collaboration with a more neutral entity (e.g., NCQA), as well as the business community and the consumer community, a single standardized rehabilitation score (with possible subscores) by which health plans will be rated based on the capabilities and performance of the plan's entire network of rehabilitation providers. Such a score would be largely outcome based (and risk adjusted). Such a score would also create enormous peer pressure to exclude subpar providers and encourage collaboration in helping to improve the plan's overall rehabilitation score.
- The industry will have to convince various health system governing boards, large employers, and health insurance purchasing cooperatives that a rehabilitation rating system is needed to help consumers make their annual side-by-side comparison of competing health plans. Without such a rating, consumers will overlook the rehabilitation component of a health plan and health plans may not be adequately motivated to include the best possible network of rehabilitation providers.
- The industry will have to adopt the single-score concept (with possible subscores) as the basis for rating individual providers. Such ratings would guide consumers, physician gate-keepers, and health plan case managers in selecting a within-plan or out-of-plan provider when a rehabilitation need arises.
- The medical rehabilitation industry will have to undertake an education strategy to inform consumers, physician gate-keepers, and case managers what rehabilitation scores or ratings mean for the choices they need to make when choosing a plan or selecting a provider.4, 5
- Another way to frame the challenge: The spark-plug and sound-system analogy
- Will consumers choose a health plan based on the quality score of a rehabilitation provider network associated with the plan?
- Consumers probably will not choose a health plan based solely on who is the rehabilitation provider
- Consumers do not buy an automobile based on the brand or quality of the spark plug in the automobile; they might choose an automobile based on the brand-name sound system in the automobile (Pioneer, Bose).
- Consumers do choose a health plan based on quality and reputations of key providers. Examples:
- The primary care physician or gate-keeper (e.g., a pediatrician)
- The OB-GYN
- A specialist with whom the consumer has had a long-standing relationship (e.g., a neurologist)
- Other providers (e.g., oncologists) if the consumer perceives that he/she is a risk of acquiring a particular health condition (e.g., oncology practice).
- Rehabilitation providers will have to convince would-be consumers that they are the moral equivalent of a Bose sound system; that they are at risk of acquiring a condition that will require rehabilitation (stroke = "brain attack")
- The situation is different for those who already have an impairment that has required, or may, in the future, require rehabilitation
- These consumers already understand their risk
- The rehabilitation provider's franchise with the consumer would be even stronger if it saw itself not only as a provider of rehabilitation services but also as the gate keeper or PCP that will meet the ongoing needs of the disabled population.
- Will consumers choose a health plan based on the quality score of a rehabilitation provider network associated with the plan?
- Rehabilitation providers as PCP/gate keeper for people with disabilities
- Rehab needs to position itself at the front end of the health care "food chain," not at the back end; need to become an "up-stream" provider instead of a "down-stream" provider.
- Rehabilitation providers understand the ongoing health care needs of the disabled population better than most primary care physicians. Rehab physicians understand how various up-front interventions can avert the "down-stream" (specialist and hospital) costs that person with disability is otherwise likely to incur.
- Many primary care physicians consider people with disabilities as a "drag" on their practice - can't turn patients around fast enough.
- In many instances, rehab providers already serve as the de facto primary care provider.
- In the near term, there are remarkable opportunities to cut win-win-win deals with managed care organizations:
- The consumer
- Needs a reliable source of primary care currently not available
- Needs an informed gate-keeper who understands his/her particular constellation of health care needs
- The provider
- Needs to capture a population such that he/she is not left at the vulnerable end of the "food chain"
- Capitating a high-cost population can be financially profitable
CMA in Boston capitated at approx. $27,000 per enrollee per year
In California, a 14-physician oncology group practice negotiated a carve-out with a MCO and found that their income increased 40% at a time when national average income for oncologists decreased.
Rehab providers may, in the short term, want to team up with PCPs in order to shore up their network's primary care capabilities. - The payer
- Wants some certainty about costs managing a higher-cost population
- The consumer
- Are rehabilitation providers in the business of rehabilitation or in the business of health care for people with disabilities?
- Significant implications for training of rehab physicians and allied rehab professionals
V. OTHER STEPS THAT NEED TO BE TAKEN (longer term)
- Develop risk adjusters
- Essential to developing a more risk-neutral health care system
- Need to risk adjust outcomes
- Outcomes adjusted on basis of risk, severity of impairment, severity of illness, functional limitation upon admission
- Without risk adjustment for outcomes, one program cannot be compared fairly with another
- Need to risk adjust health plans
- Health plans will continue to discriminate against high-end users of health care such as people with disabilities and chronic health conditions without some form of risk adjustment
- Difficulty
- Development of an appropriate risk adjustment methodology for health plans and providers is probably the single greatest analytic challenge for the remainder of the 1990s
- Need to start with simple risk adjusters and learn how to refine them over time.
- Develop a standard benefits package
- Essential to minimizing risk competition
- Essential in helping consumers make informed choices among health plans when making side-by-side comparisons
- Addresses the "homogeneous product" assumption in the theory of perfect competition
- Get people to understand the important role of government
- Even for those who would like to see a reduced role for government in the provision of health care, need to understand the importance of government in creating a more level-playing field in health care.
- Government essential to the development of rules that will result in a more consumer-driven, risk-neutral, market-based system
- Even for those who would like to see a reduced role for government in the provision of health care, need to understand the importance of government in creating a more level-playing field in health care.
- Initiate antitrust action, where necessary, to preserve effective competition in local and regional markets
- The present trend of mergers, acquisitions, and consolidations reflects market-share competition. Everybody wants to be part of a larger system so they will not lose out in obtaining managed care contracts.
- Some within-market consolidation is needed to help achieve some economies of scale that will make health care cheaper.
- Excessive within-market consolidation represents the single greatest threat to the development of genuinely competitive consumer-driven market.
- Health care reform would have helped put the brakes on excessive consolidation.
- We still have a window of opportunity to structure Medicare and Medicaid managed care to insure effective competition. In the absence of comprehensive reform, we can do a lot to make sure that Medicare and Medicaid managed care adheres to principles of market competition.
- This is another area in which consumers and providers can collaborate for the remainder of the 1990s.
VI. SUMMARY CHECKLIST: STEPS THAT NEED TO BE TAKEN
- Near-term (next 2 years)
Rehabilitation providers (individually or collectively)- Reposition. Redefine your business. Get into the business of providing health care for people with disabilities and chronic health conditions, not just the rehabilitation business.
- Research what health plans are currently spending annually on the health care needs of disabled populations that rehabilitation providers are qualified to manage.
- Consult with consumers to determine what they need/want, what they seek in a health plan, and how they want to have their care managed.
- Reorient. Become the PCP/gate-keeper for selected groups of people with disabilities. Retrain.
- Work with other provider groups to develop a provider network than can deliver a continuum of care for people with disabilities (including primary care, outpatient care, acute inpatient, inpatient rehabilitation, subacute rehabilitation).
- Negotiate capitated carve-outs with MCOs. Offer MCOs the possibility of risk-sharing in managing the health care needs of a high-user population. Offer going full-risk after 3 years.
- Convince large employers, health purchasing cooperatives, and others representing the consumer side of the market that a rehabilitation rating system is needed to help consumers make their annual side-by-side comparison of health plans
Providers and consumers- Begin working together to develop a composite quality/outcome score and subscores that will be meaningful to consumers and referral choices when choosing a health plan or a rehabilitation provider. Seek government funding for the development of such composite scores.
- Read the Wall Street Journal, not JAMA or NEJM to know what is really happening in health care.
Consumers- As Medicare moves toward managed care, insist that Medicare subscribers have a choice of at least 3 viable health plans in each market areas.
- As state Medicaid programs move toward managed care, insist that Medicaid participants have a choice of at least 3 viable health plans in each market area.
- Petition to initiate antitrust action if Steps 10 and 11 are not implemented and if there is excessive concentration in local markets.
- Longer term (2-5 years)
Providers- Work to make rehabilitation the sound system, not the spark plug, of health plans.
- Expand the current MREF education strategy to inform consumers, physician gate-keepers, and case managers what rehabilitation scores or ratings mean for the choices they need to make when choosing a health plan or selecting a provider.
- Provide full disclosure of outcome data across all rehabilitation providers; eliminate selective self-serving disclosure; abolish secrecy.
Consumers- Join forces with large employers in getting health plans to adopt disability ratings and rehabilitation scores.
- Insist that each health plan include a report care in its marketing material that includes a disability service and rehabilitation score as certified by an independent organization.
- Demand full outcome disclosure (risk adjusted to the extent possible) from rehabilitation providers.
- Make quality/outcome scores and subscores available on the Internet in a manner that will enable consumers and referrals sources to probe more deeply when attempting to make informed choices.
- Keep a watchful eye for excessive within-market concentration and anticompetitive practices that limit consumer choice and raise prices artificially.
Providers and consumers- Update methods for quality/outcome scores and subscores.
- Work with NCQA, health plans, and other organizations in developing risk adjusters that will minimize risk competition and can be used to risk adjust quality and outcome measures.
Remember: An informed consumer is the single most important element in truly consumer-driven health care system
VII. IN CLOSING
- Strong believer in market-based approaches
- More creative, more dynamic, and ultimately more responsive
- However, we need to make sure that the conditions for a market-based health care system are effectively in place. We mentioned a few of them:
- Standard benefit package
- Consumer knowledge
- Competition on price and quality/outcomes, not price, risk, and market share
- Organized consumer groups are essential in making sure that we develop a genuinely competitive market system.
- Also believe in the principles of managed care provided managed care is organized on a level-playing field
- Moving from a provider-driven payer-driven consumer driven health care system
- Differences between these systems are outlined in table in Appendix.
- In a payer-driven system, both the consumer and provider are disadvantaged; a consumer-driven system is the provider's best hope for a more level playing field
- A consumer-driven system will empower the consumer to make choices and enable the provider to compete on a level playing field.
- I believe that the movement toward a consumer-driven system is inexorable and unstoppable. There are threats to the development of such a system. However, effective collaboration between consumers and providers is our best hope for achieving the outcomes we all want.
Gerben DeJong, Ph.D. is Director of the National Rehabilitation Hospital (NRH) Research Center; Director of the Research and Training Center in Medical Rehabilitation Services and Health Policy; and Professor in the Department of Family Medicine, Georgetown University, Washington, DC.
National Rehabilitation Hospital Research Center Mailing Address: 102 Irving Street, N.W., Washington, DC 20010-2949. Street Address: 1016 16th Street, N.W., Fourth Floor, Washington, DC 20036, (202)466-1900; FAX (202)466-1911
NOTES
A presentation made to the Forum on Managed Care in Missouri sponsored by the Tri-Alliance for Rehabilitation and the School of Health Related Professions, University of Missouri-Columbia. Columbia, MO.
The preparation of this outline was supported in part by the NRH Research Center's Research and Training Center on Medical Rehabilitation Services and Health Policy (RTC-MRS&HP) which is funded with a grant from the National Institute on Disability and Rehabilitation Research (NIDRR). Grant #H133B40025.
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By covering increasing out-of-pocket costs for prescription drugs, managed care companies are luring Medicare subscribers into Medicare managed care plans. This was the same enticement that the Clinton health care reform plan had: It tried to secure the endorsement of the retirement-age population by including Medicare coverage for prescription drugs.
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A Wall Street Journal article (Scism, 1994) on the Golden Rule Insurance Company illustrates this problem well:
Screening insurance applicants carefully, Golden rule tries to sell policies only to the healthy or to those whose existing medical problems can be exempted from coverage. And when cherry picking fails and the company gets stuck with someone with a big medical problem that isn't exempt from coverage, it still does well ... because its hardball legal tactics often carry the day.
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Just before being acquired by HealthSouth, AdvantageHealth purchased the 202-bed Harmarville Rehabilitation Center in Pittsburgh and its 7 affiliated outpatient centers.
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A rating system such as the one outlined have will require collaboration between organizations such as the Uniform Data System for Medical Rehabilitation (UDSMR) and the Commission on Accreditation of Rehabilitation Facilities (CARF). UDSMR for example, might well become the principal provider of standardized performance data and CARF will likely become the principal evaluator of provider capabilities. I believe that, in a consumer-driven health care system, the role of CARF, for example, will shift from its conventional accreditation function to also becoming producer of standardized data on which provider capabilities will be evaluated and translated for consumer consumption.
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The consumer-driven medical rehabilitation assessment system envisioned here will also come to replace the physician-based assessment used by organizations such as the US News and World Report in conducting its annual survey of the 10 best rehabilitation hospitals. Such surveys are based largely on physician-peer perceptions that are shaped less by the provider's quality of patient care and more by the provider's academic and research prowess and by the provider's marketing and public relations capabilities.
REFERENCES
Boodman, Sandra G. 1995 "Doctors Learn to Generalize: Primary, Not Specialty, Care is HMOs' Focus." Washington Post (April 25), A-1 and A-4)
Batavia, Andrew I. 1993 "Health Care Reform and People with Disabilities." Health Affairs (Spring).
Biblo, Joan D., Myra J. Christopher, Linda Johnson, Robert Lyman Potter 1995 Ethical Issues in Managed Care: Guidelines for Clinicians and Recommendations to Accrediting Organizations. Kansas City, MO: Midwest Bioethics Center.
Consortium for Citizens with Disabilities Health Task Force 1994 "Testimony on Behalf of the Consortium for Citizens with Disabilities Health Task Force." Testimony before the Committee on Labor and Human Resources, US Senate. Washington, DC. February 22.
Council on Ethical and Judicial Affairs, American Medical Association 1995 "Ethical Issues in Managed Care." JAMA Vol. 273, No.4:330-35.
Council on Ethical and Judicial Affairs, American Medical Association 1995 "Managed Care Jekyll or Hyde?" JAMA Vol. 273, No.4:338-39.
DeJong, Gerben 1993 "Health Care Reform and Disability: Reaffirming the Commitment to Community." Archives of Physical Medicine and Rehabilitation, 74 (October), 1017-1024. Based on the John Stanley Coulter Lecture presented at the annual meetings of the American Congress of Rehabilitation Medicine. Denver, CO. June 27, 1993.
DeJong, Gerben and Janet P. Sutton 1995 "Rehab 2000: The Evolution of Medical Rehabilitation in American Health Care." Lead chapter in Outcome Oriented Rehabilitation: Principles, Strategies, and Tools for Effective Program Management, Pat Kitchell Landrum, et al., eds. Gaithersburg, MD: Aspen Publishers, Inc. (in press).
Ezekiel, J. Emanuel, Nancy Neveloff Dubler 1995 "Preserving the Physician-Patient Relationship in the Era of Managed Care." JAMA Vol. 273, No.4:323-29.
Foster Higgins, (1994). National Survey of Employer Sponsored Health Plans. New York.
Governance Committee, The 1995 To the Greater Good: Recovering the American Physician Enterprise. Washington, DC: The Advisory Board Company, 1995.
Health Pages-Wisconsin (1993) 1(1).
Health Pages-St. Louis (1993) 1(1).
Hilzenrath, David S. 1995 "National Orthopaedic Turns to Managed Care: Columbia/HCA Healthcare to Run Hospital." Washington Post (Washington Business), (May), 14.
Hilzenrath, David S. 1995 "Manor Care to Enter Home Nursing Field: $42 Million Deal Reflects Shift in Industry," Washington Post (May 4), B-11
Hodapp, Thomas E. and Michael Samols 1995 Mounting Momentum for New York Medicaid Managed Care Mandate Spells Massive Membership Gains. San Francisco, CA: Robertson Sephens & Company.
Hurley, Robert E., Deborah A. Freund, John E. Paul 1993 Managed Care in Medicaid: Lessons for Policy and Program Design. Ann Arbor, Michigan: The Association for Health Services Research, Health Administration Press.
Iezzoni, Lisa I. 1994 Risk Adjustment for Measuring Health Care Outcomes. Ann Arbor, MI: Health Administration Press.
Kertesz, L. 1994 A Blue Streak for Managed Care. Modern Healthcare. 24(37):63-66,68,70.
Lewin-VHI 1995 States as Payers: Managed care for Medicaid Populations. Washington, DC: National Institute for Health Care Management.
Marion Merrell Dow 1994 Managed Care Digest, HMO Edition. Kansas City: Marion Merrell Dow Inc.
Marion Merrell Dow 1994 Managed Care Digest, Long Term Care Edition. Kansas City: Marion Merrell Dow Inc.
Mathews, Jessica 1995 "Before Medicare Goes Belly-Up." Washington Post. (May 2), A19.
Newhouse, Joseph P. 1994 "Patients at Risk: Health Care Reform and Risk Adjustment." Health Affairs 13(Spring) 133-146.
Rich, Spencer 1994 "New York State's Stumble in Health Reform Raises Warning Signals on Hill." Washington Post (September 22), A-8.
Scism, Leslie 1994 "Picking Cherries: Health Insurer Profits by Being Very Choosy in Selling its Policies." Wall Street Journal (Eastern edition), 224 (September 20), A-1.
Sofaer, Shoshanna 1993 "Informing and Protecting Consumers under Managed Competition." Health Affairs (Supplement) No. 12, 76-86.
Skolnick, Sheryl R., Gianna C. Prime 1994 Acute Care Hospitals: Building Earnings through Market Share. San Francisco: Robertson Stephens & Company. November 22.
Tomsho, Robert 1995 "Columbia/HCA Finalizes Venture Plan in London, Providing Toehold in Europe." The Wall Street Journal (May 24), B-8.
Weiner, Jonathan P. 1994 "Forecasting the Effects of Health Reform on US Physician Workforce Requirement." JAMA (July 20)
Wohl, Vivian R., Scott R. Davidson 1995 Home Care '95: Parterning for Performance. San Francisco: Robertson Stephens & Company. March 21.
Wolk, S., Blair, T. 1994 Trends in Medical Rehabilitation. Reston, VA: American Rehabilitation Association.
APPENDIX
| Projected Surplus by Specialty1 | |||
|---|---|---|---|
| Specialty | Projected Supply in Year 20002 | Projected Demand in Year 2000 | Percentage Range of Surplus |
| Neurosurgery | 4,285 | 1,449-2,736 | 57-196% |
| Plastic Surgery | 5,204 | 1,882-2,311 | 125-177% |
| Cardiology | 14,999 | 7,002-9,792 | 53-114% |
| Anestesiology | 28,161 | 14,426-16,143 | 74-95% |
| Ophthalmology | 17,141 | 9,014-10,946 | 57-90% |
| Neurology | 8,265 | 4,542-5,400 | 53-82% |
| Radiology | 26,324 | 15,706-18,496 | 42-68% |
| General Surgery | 33,058 | 20,313-21,815 | 52-64% |
| Gastroenterology | 7,346 | 4,752-4,967 | 48-55% |
| Orthopedics | 19,896 | 13,103-16,537 | 20-52% |
|
|||
| How Markets Evolve | ||||
|---|---|---|---|---|
| Stage 1 | Stage 2 | Stage 3 | Stage 4 | Stage 5 |
Unstructured
|
Loose framework
|
Consolidation
|
Managed competition
|
Endgame
|
Markets
|
Markets
|
Markets
|
Markets
|
Markets
|
| SOURCE: Hospitals & Health Networks, 1995; APM Inc. and University Hospital Consortium, 1995 Editor's note: This chart presents a view from APM Inc. and the University Hospital Consortium of stages of health care markets evolving as a result of reform and identifies markets in the various stages. |
||||
| Yearly Estimates of the Number of Rehabilitation Facilities, SNFs, and Long-Term Care Hospitals in the U.S.: 1985-1994 | |||||||
|---|---|---|---|---|---|---|---|
| Type of Facility | 1985 | 1987 | 1989 | 1991 | 1993 | 19946 | Percent Change 1985-1994 |
| Rehabilitation Hospitals1 | 68 | 88 | 125 | 152 | 180 | 187 | +175 |
| Rehabilitation Units2 | 386 | 539 | 642 | 672 | 783 | 804 | +118 |
| Long-term Care Hospitals3 | 86 | 87 | 89 | 91 | 109 | 113 | +31 |
| Skilled Nursing Facilities (SNFs)4 | 6,725 | 7,379 | 8,688 | 10,061 | 11,309 | 11,436 | +70 |
| Comprehensive Outpatient Rehabilitation Facilities (CORFs)5 | 86 | 141 | 184 | 201 | 229 | 237 | +176 |
|
|||||||
| Comparing Provider-, Payer-, and Consumer-driven Health Care Systems | |||
|---|---|---|---|
| Dimension | Provider-driven (supply side) |
Payer-driven (intermediary) |
Consumer-driven (demand side) |
| Key value | Provider autonomy | Cost minimization | Consumer sovereignty |
| Basis of competition | Prestige & risk | Price & risk | Price & quality |
| Economic goals | Revenue maximization | Market share/profit maximization | Cost-effectiveness (efficiency) |
| Pricing | "Usual & customary" | Discounting | Value-based |
| Method of payment | Fee-for-service | Case-mix (eg, DRGs, FRGs), RBRVS capitation | Risk-adjusted capitation, carve-outs |
| Quality | Accreditation Credentialing | Perception of quality, CQI, TQM | Outcomes, consumer satisfaction |
| Access | Provider-controlled | Payer-controlled | Consumer choice |
| Capacity | Excess capacity | Reduced capacity | Balanced capacity |
| Utilization | Overutilization | Underservice | Balanced |
| Utilization review | Retrospective | Prospective | Not needed |
| Costs | Not important | Very important | Relative to outcome |
| Outcomes | Elimination of pathology, "satisficing" | Reduced utilization, reduced costs | Health status, functional status, quality of life, consumer satisfaction |
| Outcome disclosure | Confidential/secret | Selective disclosure | Full disclosure |
| Providers as price takers | No | Yes | Yes |
| Homogeneous product | No | No | Yes, standard benefit package |
| Knowledge & expertise | Rests with provider | Second-guessed by payer | Made accessible to consumer |
| Rating | Experience rating | Experience rating | Community rating |
| Risk adjustment | No | Some case-mix adjustment | Yes |
| Governance | Provider dominated | Payer dominated | Consumer dominated |
| SOURCE: DeJong & Sutton (1995) | |||
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