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Developing Medicare and Medicaid Substance Abuse Treatment Spending Estimates

Publication Date

This is a supplemental report to the final report of a study jointly funded by ONDCP and ASPE (Medicaid Substance Abuse Treatment Spending: Findings Report). This technical report provides more detail on the methods used to make estimates, and it also describes how MPR would make similar estimates of Medicare funding for substance abuse treatment, if requested to do so. [29 PDF pages]

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Introduction

As federal and state substance abuse (SA) agencies work to establish priorities and coordinate their efforts, policymakers need reliable national and state estimates of Medicaid and Medicare SA treatment spending and accurate methods for projecting these estimates forward. Spending estimates and projections are essential for both aligning funding with policy objectives and developing realistic budgets to support treatment and prevention. Given these needs the Office of the Assistant Secretary for Planning and Evaluation in the U.S. Department of Health and Human Services (HHS) and the Office of National Drug Control Policy (ONDCP) contracted with Mathematica Policy Research to conduct this of Medicare and Medicaid SA treatment spending. This study included both methodological and programmatic issues. This technical report addresses two methodological issues:

  • What methods should be used to develop estimates of Medicare SA treatment spending?

  • How should estimates of Medicaid SA treatment spending be projected forward when estimates derived from observed data are not available to policymakers?

A separate findings report produced under this project presents the programmatic findings of this study and addresses methodological issues related to estimating Medicaid SA treatment expenditures in Medicaid Analytic eXtract (MAX) data.

This report contains two sections. The first section presents an approach for developing estimates of SA treatment spending in the Medicare program. The second section presents methods for trending estimates of Medicaid SA treatment.

I. Proposed Methodology for Producing Medicare Substance Abuse Treatment Expenditures Estimates

In this section, we propose a methodology for developing estimates of Medicare SA treatment spending. The methods parallel the approach used to develop Medicaid spending estimates in this project. In Section A, we provide an overview of Medicare coverage of SA treatment services and the payment approaches Medicare uses to reimburse providers for these services. In Section B, we discuss Part A and B expenditures. In Section C, we propose methods for imputing SA treatment expenditures for Medicare Advantage (MA) managed care beneficiaries, based on fee-for-service (FFS) spending on SA treatment services and encounter data (when those data become available for 2012 and later years). Finally, in Section D, we discuss Part D, prescribed drug expenditures.

A. Overview of Medicare Coverage of SA Treatment

In this section, we first describe the SA treatment services covered under the Medicare program. Then, we describe the approaches Medicare uses to reimburse providers for these services.

1. Service Coverage

Medicare covers a full spectrum of SA treatment services:

  • Inpatient hospital care--Medicare covers medically necessary inpatient hospital care for SA with the same coinsurance levels (for example, $1,156 deductible for 2012) and length of stay restrictions (up to 90 days in a benefit period, with a one-time 60-day reserve) as other types of hospitals stays. Medicare covers only a total of 190 days spent in a psychiatric hospital for an entire lifetime. Medicare may cover further inpatient mental health care in a general hospital, but not a psychiatric hospital.

  • Outpatient treatment--Medicare Part B covers outpatient SA treatment. Visits to a doctor or other health professional to diagnose a SA disorder are covered with a 20 percent coinsurance amount. Outpatient treatment of SA is covered with a 40 percent coinsurance in 2012. This coinsurance amount will decrease until 2014, when it will be 20 percent. Partial hospitalization is covered by Medicare if inpatient treatment would be necessary otherwise.

  • Preventive treatment--In October 2011, Medicare Part B initiated a new preventive benefit related to SA. This comprises an annual screening for alcohol misuse and up to four counseling visits to reduce alcohol misuse. Medicare fully covers these services from providers who accept assignment.

  • Prescribed drugs--Medicare Part D covers prescribed drugs for SA treatment at the same coverage levels as other prescribed drugs.

It should be noted that Medicare coverage of SA treatment is increasing from 2010 through 2014 including the reduction in coinsurance for outpatient services to 20 percent by 2014. This increase in coverage results from the implementation of mental health parity and the addition of preventive alcohol use screening in 2011. These enhanced benefits are likely to result in a higher use rate and greater expenditures for SA treatment over time.

2. Payment Method

Medicare provides Part A and B services to beneficiaries through the traditional Medicare FFS or MA managed care plans. When beneficiaries elect to enroll in MA, Medicare pays health plans chosen by beneficiaries a monthly premium to manage their care. For beneficiaries covered under the traditional Medicare FFS program, Medicare maintains administrative data on the services received and the associated Medicare payment amounts. However, until 2012, for beneficiaries enrolled in MA, Medicare maintained administrative data only on premium payment amounts but did not require the MA plans to submit data on the services they provided to their enrollees. Thus, through 2011 for individuals enrolled in FFS Medicare, Medicare administrative data can be used to calculate the number of beneficiaries using SA treatment services and expenditures related to these services. However, for individuals covered under MA, Medicare administrative data cannot be used to analyze service use.

Beginning in 2012, MA plans are required to submit encounter data enumerating the services provided to MA enrollees. It is expected that initial submissions may be incomplete or that other data quality issues may exist (for example, non-uniform coding across plans). The quality of the MA data likely will improve over time, but the analysis of the MA encounter data likely will be more resource intensive in the initial years, as it will require assessment of reporting quality and adjustments to allow for incomplete, inconsistent, or inaccurate reporting. Analyses based on the initial encounter data are also likely to be less accurate. Thus, it likely will be necessary to allow time for the Centers for Medicare and Medicaid Services (CMS) to assess encounter data reporting and work with plans to improve such data before undertaking research using them. Thus, in the near future, we recommend that estimates of Medicare SA spending not rely on MA encounter data reporting and instead use FFS data to impute SA spending among MA enrollees.

Medicare prescription drug coverage, known as Medicare Part D, is provided through private companies approved by Medicare. Medicare pays these plans a monthly premium amount for each Medicare beneficiary covered. Utilization of Part D services is recorded in the CMS administrative data. These utilization data can be used to estimate SA related expenditures for prescribed drugs under Part D.

Table 1 displays the number of MA enrollees in each state and the District of Columbia for the last five years. MA enrollment has been increasing at a rate of 9.4 percent annually, with the rate of increase varying across states. Table 2 displays MA enrollment as a share of overall Medicare enrollment by state for 2011. Overall, almost one-quarter of Medicare enrollees are in an MA plan. Since MA enrollees represent a significant share of overall Medicare enrollment, the expenditures estimated for this population will represent a significant share of the overall estimate of SA treatment spending in Medicare.

B. Part a & B FFS Expenditures

Medicare's Chronic Condition Warehouse (CCW) can provide claims data to estimate total Medicare SA treatment spending for traditional Medicare FFS beneficiaries. Data files with 100 percent of FFS beneficiaries are available, as well as sample files. However, use of SA treatment is rare in the population ages 65 and older. Thus, there may be an insufficient sample of users to develop precise estimates in smaller states if a sample file is used. However, the 5 percent sample should provide sufficient precision for national estimates of SA treatment expenditures.

We recommend using the CCW Institutional and Non-Institutional claims files to estimate SA treatment spending in institutional and non-institutional settings, respectively. In parallel to the analysis of Medicaid SA treatment spending, we recommend that SA expenditures be divided into the following six types:

  • Core--Services included in the Substance Abuse and Mental Health Services Administration's (SAMHSA) definition of SA treatment.

  • Fetal exposure--Medical services primarily resulting from fetal exposure to alcohol or drugs. We expect that few of these services will be identified in the Medicare population, however, they are included as a separate category to parallel the Medicaid estimates.

  • Poisoning--Medical services primarily resulting from poisoning by alcohol or drugs.

  • Supplemental--Medical services primarily related to medical conditions fully attributable to alcohol or drug use.

  • Mental health claim with secondary SA diagnosis--Individuals with an SA disorder often have a co-morbid mental health condition. Thus, it will be desirable to identify claims with a primary mental health diagnosis and a secondary SA diagnosis.

  • Other claim with secondary SA diagnosis--Expenditures on these claims are related primarily to a medical condition other than SA; however, the SA co-morbidity increases the cost of this care to the Medicare program.

SA treatment claims within each of these types will be identified based on diagnosis code. Appendix A, Table A.1 and Table A.2, list diagnosis codes indicating SA treatment. For the first four SA treatment types only the first listed diagnosis on the Medicare claim should be examined. The final column of the Table A.1 and Table A.2 identifies which of these four SA treatment types is associated with each diagnosis code (Core, Fetal, Poisoning, or Supplemental). Claims will be assigned to the fifth group if they have a first listed mental health diagnosis, including any of the codes listed in Table A.3, and a secondary or later diagnosis listed in Table A.1 and Table A.2. All other Medicare claims with a secondary or later diagnosis in Table A.1 and Table A.2 will be classified into the sixth category.

Once claims with an SA diagnosis are identified, the total Medicare payment amount will be summed across the claims to determine the Medicare expenditures for these services.

C. Part C: Medicare Advantage

Because encounter data reporting is not mature for MA enrolled beneficiaries, we propose initially estimating SA treatment expenditures for the MA population based on the average level of expenditures for non-MA enrolled Medicare beneficiaries with similar characteristics. As complete encounter data become available for MA enrollees, the second approach, described below, entailing an estimation of the value of the utilization represented in the encounter data, could be used.

1. Imputation Based on FFS Experience

The following steps can be used to impute SA treatment expenditures for the MA enrolled population:

  • Step 1: Develop homogenous tiers--The Beneficiary Summary File can be used to divide Medicare enrollees into two groups based on whether they were enrolled in an MA plan at any point in the year. Within each of these two groups beneficiaries then should be divided into tiers based on their personal characteristics, including age, gender, state of resident, Medicare status code (aged, disabled, End Stage Renal Disease), and dual-eligible status.

  • Step 2: Calculate mean FFS expenditures per enrolled month--Calculate mean SA treatment expenditure per enrolled month among Medicare beneficiaries never enrolled in MA during the year for each tier created in Step 1 for each of the six SA treatment service types listed in Section B above.

  • Step 3: Calculate total MA enrolled months--For each tier in Step 1, calculate the total number of MA enrolled months.

  • Step 4: Calculate total imputed MA SA expenditures--For each SA service type, multiply the estimated mean FFS expenditure per enrolled month from Step 2 times the total number of MA enrolled months in Step 3 for each tier and sum across the tiers to obtain the total imputed MA SA expenditures for the service type.

This approach adjusts for differences in cost related to beneficiary characteristics observable in the administrative data. However, unobservable characteristics of MA enrollees may influence their treatment use. For example, wellness benefits offered by MA plans may appeal to healthier Medicare beneficiaries. Meanwhile, sicker beneficiaries may be less likely to make the effort to sign up for MA and may desire the broader choice of providers obtainable under traditional Medicare. Adjustment differences in these two groups of beneficiaries not linked to characteristics observable in the administrative data could be assessed by using multiple years of Medicare data and assessing whether MA enrollees had a lower SA treatment use rate prior to enrollment in MA relative to their counterparts who chose to remain in traditional FFS Medicare.

2. Imputation Based on Encounter Data

Once encounter data reporting is mature, encounter claims for SA treatment can be identified based on diagnosis codes in a manner similar to the identification of FFS SA treatment claims, as described in Section B. The encounter claims may not include accurate information on payment amount. If accurate information on the payment amount is not available from the encounter claims, we recommend estimating the price per unit of service based on mean expenditures per unit of service among traditional Medicare beneficiaries receiving the same service types. We also recommend that inpatient and other institutional care be priced per treatment day. Table A.5 can be used to classify outpatient treatment visits into homogeneous service types. The units of service observed in the encounter data then would be multiplied by the unit prices from traditional FFS Medicare and the total expenditures summed across the services types to determine total expenditures.

D. Part D: Prescribed Drug Expenditures

Expenditures for prescribed drugs can be estimated based on the CCW Part D Event file. Prescribed drug expenditures are categorized as core SA treatment services. The Part D Event file includes event records for both traditional Medicare FFS and MA enrollees, as well as the variable product service identification number, which provides the National Drug Code (NDC) of the prescribed drug. Table A.4 lists the NDC codes of pharmaceuticals used to treat SA. Only the first 8 digits of the 11-digit NDC code are used to identify the SA treatment pharmaceuticals. Event records listing these codes should be obtained. The values for the covered D plan paid amount and the non-covered plan paid amount are included in the Part D Event file. However, these values typically cannot be used for research. If they are available to this study then they should be summed to estimate payments under Part D. If they are not available national average payment amounts can be used to value the utilization observed in the Part D Event file.

TABLE 1. MA Enrollment 2007-2011
State 2007 2008 2009 2010 2011 Annual %
  Increase 2007-2011  
Alabama 115,569 148,889 170,475 176,216 174,202 10.8
Alaska 73 162 394 124 120 13.2
Arizona 263,637 266,647 279,833 331,444 342,978 6.8
Arkansas 38,567 51,037 60,177 71,654 75,645 18.3
California 1,449,282 1,412,343 1,547,064 1,663,441 1,734,900 4.6
Colorado 163,998 174,566 185,673 203,035 206,116 5.9
Connecticut 54,825 70,232 82,334 101,430 108,766 18.7
Delaware 3,140 4,276 5,074 4,882 5,149 13.2
District of Columbia   6,251 6,423 6,675 7,476 7,567 4.9
Florida 771,603 855,488 919,561 1,000,565 1,072,453 8.6
Georgia 94,412 126,626 153,374 250,725 269,574 30.0
Hawaii 68,224 71,525 75,142 84,418 88,986 6.9
Idaho 40,546 48,248 55,464 62,366 63,070 11.7
Illinois 136,851 153,977 167,047 168,636 163,256 4.5
Indiana 91,768 117,454 139,203 156,636 172,124 17.0
Iowa 55,755 56,579 61,156 64,737 64,749 3.8
Kansas 27,522 33,780 39,191 42,728 45,560 13.4
Kentucky 63,617 80,431 92,212 113,633 121,501 17.6
Louisiana 111,436 131,631 145,465 160,276 164,979 10.3
Maine 6,366 13,189 23,760 31,872 35,414 53.6
Maryland 37,104 42,526 49,058 60,424 61,840 13.6
Massachusetts 159,051 167,209 174,549 197,798 185,692 3.9
Michigan 237,200 334,732 383,595 255,650 389,983 13.2
Minnesota 206,593 216,208 237,035 321,109 349,715 14.1
Mississippi 31,003 38,503 42,584 44,821 46,676 10.8
Missouri 147,011 167,229 185,281 204,265 213,298 9.8
Montana 18,187 22,590 26,085 28,792 24,349 7.6
Nebraska 22,534 26,549 28,071 29,555 28,771 6.3
Nevada 93,213 98,477 102,090 106,276 109,757 4.2
New Hampshire 4,961 8,473 11,845 14,439 12,593 26.2
New Jersey 112,637 126,013 148,061 161,670 169,125 10.7
New Mexico 59,177 64,021 69,416 75,661 81,106 8.2
New York 674,029 746,644 802,917 885,826 918,606 8.0
North Carolina 190,081 219,180 241,331 257,240 262,974 8.5
North Dakota 6,247 7,225 7,458 7,789 9,472 11.0
Ohio 315,607 453,920 487,578 620,138 640,245 19.3
Oklahoma 66,441 74,625 81,765 88,723 89,678 7.8
Oregon 215,613 226,220 243,304 253,412 254,056 4.2
Pennsylvania 675,179 771,986 813,279 854,489 865,200 6.4
Rhode Island 59,740 60,309 60,713 62,751 63,553 1.6
South Carolina 56,316 75,797 89,143 118,221 123,989 21.8
South Dakota 4,863 7,162 8,504 9,623 11,663 24.4
Tennessee 170,217 193,201 211,865 251,137 265,842 11.8
Texas 373,014 440,729 492,428 569,606 600,193 12.6
Utah 45,406 60,705 71,429 83,301 88,115 18.0
Vermont 1,522 2,644 3,362 4,107 5,407 37.3
Virginia 95,991 121,193 141,101 155,855 155,941 12.9
Washington 170,145 190,271 209,878 237,487 247,229 9.8
West Virginia 60,515 66,944 72,009 71,267 73,222 4.9
Wisconsin 174,345 202,829 230,406 261,377 273,527 11.9
Wyoming 2,000 2,515 2,964 4,037 3,360   13.8  
United States   8,049,384     9,060,132     9,938,378     10,993,140     11,542,286   9.4


TABLE 2. MA Enrollment as a Share of Overall Medicare Enrollment, 2011
State   Medicare Beneficiaries     MA Enrollees     MA Share (%)  
Alabama 852,740 174,202 20.4
Alaska 65,356 120 0.2
Arizona 933,435 342,978 36.7
Arkansas 536,817 75,645 14.1
California 4,806,469 1,734,900 36.1
Colorado 631,387 206,116 32.6
Connecticut 571,020 108,766 19.0
Delaware 151,077 5,149 3.4
District of Columbia   78,860 7,567 9.6
Florida 3,390,801 1,072,453 31.6
Georgia 1,256,047 269,574 21.5
Hawaii 210,009 88,986 42.4
Idaho 232,471 63,070 27.1
Illinois 1,854,402 163,256 8.8
Indiana 1,014,432 172,124 17.0
Iowa 519,726 64,749 12.5
Kansas 435,802 45,560 10.5
Kentucky 767,801 121,501 15.8
Louisiana 692,718 164,979 23.8
Maine 267,012 35,414 13.3
Maryland 794,039 61,840 7.8
Massachusetts 1,067,929 185,692 17.4
Michigan 1,669,386 389,983 23.4
Minnesota 791,566 349,715 44.2
Mississippi 501,142 46,676 9.3
Missouri 1,009,613 213,298 21.1
Montana 171,499 24,349 14.2
Nebraska 280,441 28,771 10.3
Nevada 359,968 109,757 30.5
New Hampshire 221,168 12,593 5.7
New Jersey 1,336,988 169,125 12.6
New Mexico 316,973 81,106 25.6
New York 3,009,756 918,606 30.5
North Carolina 1,505,942 262,974 17.5
North Dakota 108,878 9,472 8.7
Ohio 1,909,462 640,245 33.5
Oklahoma 607,465 89,678 14.8
Oregon 625,594 254,056 40.6
Pennsylvania 2,290,509 865,200 37.8
Rhode Island 183,433 63,553 34.6
South Carolina 783,904 123,989 15.8
South Dakota 137,314 11,663 8.5
Tennessee 1,067,534 265,842 24.9
Texas 3,044,936 600,193 19.7
Utah 286,630 88,115 30.7
Vermont 112,831 5,407 4.8
Virginia 1,155,428 155,941 13.5
Washington 983,167 247,229 25.1
West Virginia 383,035 73,222 19.1
Wisconsin 918,344 273,527 29.8
Wyoming 80,994 3,360 4.1
United States 47,672,971 11,542,286 24.2


II. Proposed Methods and Resources Required for Updating Medicaid Estimates with Future Years of Data

ONDCP develops the annual National Drug Control Strategy Budget Summary and so needs an approach for updating the estimates of Medicaid SA treatment spending annually. We recommend direct derivation of the estimates of SA treatment spending from MAX files every 5-7 years or after major policy changes take place, such as implementation of the Affordable Care Act. For the intervening years, we recommend projecting base year estimates forward using the CMS-64 reporting and Medicaid enrollment data. The CMS-64 report summarizes annual Medicaid expenditures for each state. Information from the forms is currently available through FY 2011 for each state by service category. The benefit of using the information from the CMS-64 reports is that the available trends are state and service specific, and are available with only limited lag. One drawback to the CMS-64 data is that they are not broken out by eligibility group. Another limitation is that they are based on date of payment, therefore lump sum adjustments or lags in payment processing can impact trends artificially. Since SA treatment utilization varies by age, gender, and eligibility, we propose using Medicaid enrollment information in combination with the CMS-64 data.

We propose using the following steps to develop projections for each state:

  • Step 1: Obtain data. The CMS-64 reports, containing cost and service data, can be downloaded from the CMS website.1 Medicaid monthly enrollment data for December and June can be obtained from the Kaiser Commission on Medicaid and the Uninsured website.2 Data currently are compiled through June 2011. Projections of SA treatment spending by SA care group and type of SA Spending for FY 2011 are provided in Appendix B. These estimates would be trended forward until updated estimates are directly derived from MAX.

  • Step 2: Map CMS-64 service categories to the five SA care groups. Map the service categories available in CMS-64 data to the five SA care groups included in the FY 2011 projections (Table B.1) developed from MAX data for the base year of the data (FY 2011 for the first round) and the desired year of the estimates. Map services in two steps. (a) First, group together individual categories from the CMS-64 into broader service groups shown in Table 3. Include relevant “C” categories, which represent expenses reported for Medicaid expansion Children's Health Insurance Program (CHIP) populations, and “T” categories, which account for expenses in those states that qualify to expend 20 percent of their CHIP allotment on the Medicaid program and still receive the enhanced CHIP match rate. Table 3 shows the groups by care setting developed based on the 2011 CMS-64 categories. (b) Next, crosswalk these groups to the five SA care groups included in the FY 2011 projections. Table 4 shows this crosswalk.3

  • Step 3: Estimate overall Medicaid expenditures. Estimate the overall level of Medicaid spending represented in the CMS-64s for each state in each SA care group in the base year and the most recent year of CMS-64 data available. Also, estimate the overall level of Medicaid spending for the state in the base year and the most recent year of data available.

  • Step 4: Calculate spending per enrolled month. Divide the total Medicaid spending for each state in each SA care group and overall by 12 times the number of Medicaid enrolled months in the state in June of the given year. The June months are multiplied by 12 to represent a full year of enrollment.

  • Step 5: Estimate the trend in spending per enrolled month. Estimate the overall Medicaid expenditure trend for each state for each SA care group and overall from the base period through the most recent year available.4 In rare cases, where trends for a particular service category indicates more than a 35 percent increase or decrease, replace the service category-specific trend with the overall trend in state Medicaid spending.

  • Step 6: Adjust overall Medicaid general health expenditure trends for the historical difference in growth between SA treatment and general health care spending. Between 1986 and 2005, the estimated trend in Medicaid SA treatment spending based on the SAMHSA Spending Estimates (SSE) was 98 percent of the National Health Expenditure Accounts (NHEA) estimated trend in Medicaid spending. Given that the rate of growth in SA treatment expenditures (as identified in the SSE) historically has fallen below that of general health care expenditures (as identified in the NHEA), multiply the annual trend estimates developed in Step 5 by 0.98.

  • Step 7: Estimate the trend in adult/disabled enrollment. Medicaid expenditures on SA are concentrated in the adult/disabled populations. Ideally, expenditure trend estimates specific to SA treatment services and Medicaid adults would be developed, however, since the CMS-64s are not developed by eligibility nor demographic group and do not include categories tailored to SA, the method proposed in Steps 1-6 uses the expenditure trends per enrolled month across all Medicaid enrollees in each SA care group as a proxy for trends in SA expenditures which are primarily for adults. Since enrollment information is available by eligibility group in this step the Medicaid enrollment information obtained from the June Kaiser enrollment report should be limited to the adult and disabled populations. Then, the enrollment trend between the base and the most recent year of data available should be calculated.

  • Step 8: Project the base period MAX estimates to the most recent year of data available. Multiply the base year SA spending in each SA care group by the trend in expenditures per enrolled month for the group, adjusted for the historical difference between the general health and SA expenditure trends (the latter is 98 percent of the former). Then multiply this product by the trend in enrollment for the adult and disabled population for the same period. Estimates for the non-core SA treatment expenditures reported in Table B.2 were not developed by type of care, so they cannot be trended by SA care groups. Instead, trend these estimates based on the overall spending per enrolled month trend for Medicaid times 0.98 times the enrollment trend for the adult and disabled population.

  • Step 9: Project beyond the observed data. If projections beyond the most recent period of available CMS-64 and Kaiser enrollment data are needed, assess available information on the likely trend in Medicaid expenditures. Although the NHEA projections largely reflect trends in services other than SA treatment, these trends incorporate both anticipated enrollment changes and change in economic conditions. Since the SA treatment expenditure trend is 98 percent of the general health trend in the historical data, 98 percent of the projected increase in Medicaid spending in the NHEA projections could be used to project SA treatment expenditures beyond the period for which observable data is available. Another approach would be to assume that the trend observed in CMS-64 and Kaiser enrollment data for the recent historical period will continue. If there are no economic or policy-related factors that caused shifts in the recent past or are likely to cause a substantial shift in the future trends, then this approach would be reasonable. Under this approach, annualize the trend in expenditures per enrolled month between the base year and most recent year of data available as calculated in Step 5. Multiply the annualized trend by 0.98 reflecting the historical difference between growth in SA treatment spending and overall health care spending. Then annualize the enrollment trend between the base year and the most recent year of data available as calculated in Step 7. Multiply the projection for the most recent period of CMS-64 data available as calculated in Step 8 by the annualized trend in expenditures per enrolled month and the annualized trend in enrollment in the historical data. Repeat this multiplication for each additional year of trend desired.

TABLE 3. Mapping CMS-64 Categories into Groups, 2011
Inpatient Hospital
C-Inp. Hosp. Services -- DSH
C-Inp. Hosp. Serv. -- Reg. Payments
C-Inpatient Mental Health -- DSH
C-Inpatient Mental Health -- Reg. Payment
Critical Access Hospitals
Inpatient Hospital -- GME Payments
Inpatient Hospital -- Reg. Payments
Inpatient Hospital -- DSH
Inpatient Hospital -- Sup. Payments
T-Critical Access Hospitals
T-Inp Hosp -- DSH
T-Inp Hosp -- GME Payments
T-Inp Hosp -- Reg. Payments
T-Inp Hosp -- Sup. Payments
Residential Treatment
C-Other Services
Other Care Services
T-Other Care Services
Prescribed Drug
C-Drug Rebate -- National
C-Drug Rebate -- State
C-Prescribed Drugs
Drug Rebate Offset
Drug Rebate Offset -- State Sidebar Agreement  
Prescribed Drugs
T-Drug Rebate Offset -- National
T-Drug Rebate Offset -- State Sidebar Agreement  
T-Prescribed Drugs
Managed Care
Increased ACA OFFSET -- MCO
MCO -- National Agreement
MCO -- State Sidebar Agreement
MCO -- Natl Agreement
Medicaid -- MCO
Prepaid Ambulatory Health Plan
Prepaid Inpatient Health Plan
T-Increased ACA OFFSET -- MCO
T-MCO -- National Agreement
T-MCO -- State Sidebar Agreement
T-Medicaid -- MCO
T-Prepaid Ambulatory Health Plan
T-Prepaid Inpatient Health Plan
Outpatient Care Group
C-Clinic Services
Clinic Services C-Outpatient Hospital Services
C-Outpatient Mental Health
C-Physician/Surgical
C-Screening Services
Diagnostic Screen & Preventive Services
EPSDT Screening
Federally Qualified Health Center Outpatient Hospital Service -- Reg. Payments  
Outpatient Hosp Service -- Sup. Payments
Phys & Surgical Service -- Reg. Payments
Phys & Surgical Service -- Sup. Payments
Rehabilitative Services
T- Diagnostic Screening and Preventive Services
T-Clinic Services
T-EPSDT Screening
T-Federally Qualified Health Center
T-Outpatient Hospital Services -- Reg. Payments
T-Outpatient Hospital Services -- Sup. Payments
T-Physician & Surgical Services -- Reg. Payments
T-Physician & Surgical Services -- Sup. Payments
T-Rehabilitative Services (non-school-based)
T-Rehabilitative Services (non-school-based)
Mental Health Facility -- DSH
Mental Health Facility Services -- Reg. Payments
T-Mental Health Facility -- DSH
T-Mental Health Facility Services -- Reg. Payments
Case management -- Statewide
C-Case Management
Targeted Case Management Services -- Com. Case-Man.
T-Case Management -- Statewide
T-Targeted Case Management Service -- Com. Case-Man.  
T-Emergency
T-Emergency Hospital Services
Emergency Hospital Services


TABLE 4. Crosswalk of CMS-64 Groups to Study Categories
Study Category   CMS-64 Group Used for Trend  
Inpatient Hospital Residential Treatment  
Outpatient Care Prescribed Drugs
Managed Care (Imputed Expenditures)
Inpatient Group
Other Care Services Group
Outpatient Services Group
Prescribed Drugs Group
Managed Care Group

Notes

  1. Available at https://www.cms.gov/Research-Statistics-Data-and-Systems/Computer-Data-and-Systems/MedicaidBudgetExpendSystem/CMS-64-Quarterly-Expense-Report.html. Accessed July 26, 2012.

  2. Available at http://www.kff.org/medicaid/enrollmentreports.cfm. Accessed July 26, 2012.

  3. Note that we found some differences between the CMS-64 categories for 2008 and 2011. Some new categories were added to the CMS-64 in 2010 and 2011 that were not included in the CMS-64 in prior years. If the CMS categories change again in the future, it will be necessary to map the categories in the CMS-64 in the base and estimate year as closely as possible so that trends can be developed.

  4. Estimate the trend as Tt = (St/Sb)(1/(t-b)) . Where T is the trend, S is Medicaid spending per enrolled month from Step 4, t is current year, and b is base year.

Appendices

Appendix A: Diagnosis Codes

TABLE A.1. Alcohol Abuse Diagnosis Codes
  ICD-9-CM   Description   Category of Service  
291 Alcoholic psychoses Core
2910 Delirium tremens Core
2911 Alcohol amnestic syndrome Core
2912 Alcoholic dementia NEC Core
2913 Alcohol hallucinosis Core
2914 Pathologic alcohol intoxication Core
2915 Alcoholic jealousy Core
2918 Alcoholic psychosis NEC Core
2919 Alcoholic psychosis NOS Core
303 Alcohol dependence syndrome Core
3030 Acute alcohol intoxication Core
3039 Alcohol dependency NEC/NOS Core
3050 Alcohol abuse Core
9800 Toxic effects of ethyl alcohol Poisoning
9801 Toxic effects of methyl alcohol Poisoning
E8600 Accidental poisoning by alcoholic beverages   Poisoning
E8601 Accidental poisoning by ethyl alcohol Poisoning
E8602 Accidental poisoning by methyl alcohol Poisoning
E8609 Accidental poisoning by unspecified alcohol Poisoning
7903 Excessive blood level of alcohol Poisoning
3575 Alcoholic polyneuropathy Supplemental
4255 Alcoholic cardiomyopathy Supplemental
5353 Alcoholic gastritis Supplemental
5710 Alcoholic fatty liver Supplemental
5711 Acute alcoholic hepatitis Supplemental
5712 Alcoholic cirrhosis of liver Supplemental
5713 Alcoholic liver damage, unspecified Supplemental
6554 Suspected damage to fetus from alcohol addiction   Fetus
76071 Fetal alcohol syndrome Fetus


TABLE A.2. Drug Abuse Diagnosis Codes
  ICD-9-CM   Description   Category of Service  
292 Drug psychoses Core
2920 Drug withdrawal syndrome Core
2921 Drug paranoid/hallucinosis Core
2922 Pathologic drug intoxication Core
2928 Other drug mental disease Core
2929 Drug mental disorder NOS Core
304 Drug dependence Core
3040 Opioid type dependence Core
3041 Barbiturate dependence Core
3042 Cocaine dependence Core
3043 Cannabis dependence Core
3044 Amphetamine dependence Core
3045 Hallucinogen dependence Core
3046 Drug dependence NEC Core
3047 Opioid/other drug dependence Core
3048 Combinations of drug dependence NEC   Core
3049 Drug dependence NOS Core
305 Non-dependent drug abuse Core
3052 Cannabis abuse Core
3053 Hallucinogen abuse Core
3054 Barbiturate abuse Core
3055 Opioid abuse Core
3056 Cocaine abuse Core
3057 Amphetamine abuse Core
3058 Antidepressant abuse Core
3059 Drug abuse NEC/NOS Core
6483 Drug dependence in pregnancy Fetus
357.6 Polyneuropathy due to drugs Supplemental
6555 Suspected damage to fetus from drugs Fetus
76072 Fetus affected by narcotics Fetus
76073 Fetus affected by hallucinogenic agents Fetus
76075 Fetus affected by cocaine Fetus
7795 Drug withdrawal symptoms in newborns Fetus
965 Poisoning related to narcotics Poisoning
967 Poisoning by sedatives and hypnotics Poisoning
968 Poisoning by central nervous system muscle tone depressants   Poisoning
969 Poisoning by psychotropic agents Poisoning
970 Poisoning by central nervous system stimulants Poisoning
E850-E858 Accidental poisoning by drugs, medicaments, and biologicals Poisoning
E863 Accidental poisoning by agricultural and horticultural chemical and pharmaceutical preparations other than plant food and fertilizer   Poisoning
E950.0-E950.6 Suicide and self-inflicted injury by drugs or medicinal substances Poisoning


TABLE A.3. MH Diagnosis Codes
  ICD-9-CM   Description   Analytical Classification  
295 Schizophrenic disorders Schizophrenia
2950 Simple schizophrenia Schizophrenia
2951 Hebephrenia Schizophrenia
2952 Catatonic schizophrenia Schizophrenia
2953 Paranoid schizophrenia Schizophrenia
2954 Acute schizophrenic episode Schizophrenia
2955 Latent schizophrenia Schizophrenia
2956 Residual schizophrenia Schizophrenia
2957 Schizoaffective type Schizophrenia
2958 Schizophrenia NEC Schizophrenia
2959 Schizophrenia NOS Schizophrenia
296 Affective psychoses Other affective disorder
2960 Manic disorder, single episode Bipolar I
2961 Manic disorder, recurrent episode Bipolar I
2962x (x = 3 or 4) Depressive psychosis, single episode, severe Major depression, severe
2962x (x ne 3 or 4)   Depressive psychosis, single episode, non-severe   Major depression, non-severe
2963x (x = 3 or 4) Depressive psychosis, recurrent episode, severe Major depression, severe
2963x (x ne 3 or 4) Depressive psychosis, recurrent episode, non-severe   Major depression, non-severe
2964 Bipolar affective, manic Bipolar I
2965 Bipolar affective, depressive Bipolar I
2966 Bipolar affective, mixed Bipolar I
2967 Bipolar affective NOS Bipolar I
2968 Manic-depressive NEC/NOS Other or unspecified bipolar
2969 Affective psychoses NEC/NOS Other affective disorder
297 Paranoid states Delusional disorder
2970 Paranoid state, simple Delusional disorder
2971 Paranoia Delusional disorder
2972 Paraphrenia Delusional disorder
2973 Shared paranoid disorder Delusional disorder
2978 Paranoid states NEC Delusional disorder
2979 Paranoid state NOS Delusional disorder
298 Other non-organic psychoses Other MH diagnosis
2980 Reactive depressive psychosis Other MH diagnosis
2981 Excitative-type psychosis Other MH diagnosis
2982 Reactive confusion Other MH diagnosis
2983 Acute paranoid reaction Other MH diagnosis
2984 Psychogenic paranoid psychosis Other MH diagnosis
2988 Reactive psychosis NEC/NOS Other MH diagnosis
2989 Psychosis NOS Other MH diagnosis
299 Psychoses of childhood Other MH diagnosis
2990 Infantile autism Other MH diagnosis
2991 Disintegrative psychosis Other MH diagnosis
2998 Early childhood psychoses NEC   Other MH diagnosis
2999 Early childhood psychosis NOS Other MH diagnosis
300 Neurotic disorders Anxiety disorder
3000 Anxiety states Anxiety disorder
3001 Hysteria Anxiety disorder
3002 Phobic disorders Anxiety disorder
3003 Obsessive-compulsive disorder Anxiety disorder
3004 Neurotic depression Anxiety disorder
3005 Neurasthenia Anxiety disorder
3006 Depersonalization syndrome Anxiety disorder
3007 Hypochondriasis Anxiety disorder
3008 Neurotic disorders NEC Anxiety disorder
3009 Neurotic disorder NOS Anxiety disorder
301 Personality disorders Other personality disorder
3010 Paranoid personality Other personality disorder
3011 Affective personality Other personality disorder
3012 Schizoid personality Other personality disorder
3013 Explosive personality Other personality disorder
3014 Compulsive personality Other personality disorder
3015 Histrionic personality Other personality disorder
3016 Dependent personality Other personality disorder
3017 Antisocial personality Antisocial personality disorder
3018 Other personality disorder Other personality disorder
3019 Personality disorder NOS Other personality disorder
302 Sexual disorders Other MH diagnosis
3020 Egodystonic homosexuality Other MH diagnosis
3021 Zoophilia Other MH diagnosis
3022 Pedophilia Other MH diagnosis
3023 Transvestism Other MH diagnosis
3024 Exhibitionism Other MH diagnosis
3025 Transsexualism Other MH diagnosis
3026 Psychosexual identity disorder Other MH diagnosis
3027 Psychosexual dysfunction Other MH diagnosis
3028 Psychosexual disorder NEC Other MH diagnosis
3029 Psychosexual disorder NOS Other MH diagnosis
306 Psychophysiologic disease Other MH diagnosis
3060 Psychogenic musculoskeletal disease   Other MH diagnosis
3061 Psychogenic respiratory disease Other MH diagnosis
3062 Psychogenic cardiovascular disease Other MH diagnosis
3063 Psychogenic skin disease Other MH diagnosis
3064 Psychogenic GI disease Other MH diagnosis
3065 Psychogenic GU disease Other MH diagnosis
3066 Psychogenic endocrine disease   Other MH diagnosis
3067 Psychogenic sensory disease Other MH diagnosis
3068 Psychogenic disorder NEC Other MH diagnosis
3069 Psychogenic disorder NOS Other MH diagnosis
307 Special symptom NEC Other MH diagnosis
3070 Stammering and stuttering Other MH diagnosis
3071 Anorexia nervosa Other MH diagnosis
3072 Tics Other MH diagnosis
3073 Stereotyped movements Other MH diagnosis
3074 Non-organic sleep disorder Other MH diagnosis
3075 Eating disorders NEC/NOS Other MH diagnosis
3076 Enuresis Other MH diagnosis
3077 Encopresis Other MH diagnosis
3078 Psychalgia Other MH diagnosis
3079 Special symptom NEC/NOS Other MH diagnosis
308 Acute reaction to stress Acute reaction to stress
3080 Stress reaction, emotional Acute reaction to stress
3081 Stress reaction, fugue Acute reaction to stress
3082 Stress reaction, psychomotor Acute reaction to stress
3083 Acute stress reaction NEC Acute reaction to stress
3084 Stress reaction, mixed disorder Acute reaction to stress
3089 Acute stress reaction NOS Acute reaction to stress
309 Adjustment reaction Adjustment reaction
3090 Brief depressive reaction Adjustment reaction
3091 Prolonged depressive reaction Adjustment reaction
3092 Adjustment reaction/other emotion Adjustment reaction
3093 Adjustment reaction -- conduct disorder   Adjustment reaction
3094 Adjustment reaction -- emotion/conduct Adjustment reaction
3098 Other adjustment reaction Adjustment reaction
3099 Adjustment reaction NOS Adjustment reaction
310 Non-psychotic brain syndrome Other MH diagnosis
3100 Frontal lobe syndrome Other MH diagnosis
3101 Organic personality syndrome Other MH diagnosis
3102 Postconcussion syndrome Other MH diagnosis
3108 Non-psychotic brain syndrome NEC Other MH diagnosis
3109 Non-psychotic brain syndrome NOS Other MH diagnosis
311 Depressive disorder NEC Other depressive disorder
312 Conduct disturbance NEC Conduct disorder
3120 Unsocialized aggression Conduct disorder
3121 Unsocialized, unaggressive Conduct disorder
3122 Socialized conduct disorder Conduct disorder
3123 Impulse control disorder NEC Conduct disorder
3124 Mixed disturbance conduct/emotion Conduct disorder
3128 Other conduct disturbance Conduct disorder
3129 Conduct disturbance NOS Conduct disorder
313 Emotional disorder child/adolescent Other MH diagnosis
3130 Overanxious disorder Other MH diagnosis
3131 Misery and unhappiness disorder Other MH diagnosis
3132 Sensitivity and withdrawal Other MH diagnosis
3133 Relationship problems Other MH diagnosis
3138 Other emotional disturbance, child Other MH diagnosis
3139 Emotional disturbance, child, NOS Other MH diagnosis
314 Hyperkinetic syndrome Other MH diagnosis
3140 Attention deficit disorder Other MH diagnosis
3141 Hyperkinetic with developmental delay   Other MH diagnosis
3142 Hyperkinetic conduct disorder Other MH diagnosis
3148 Other hyperkinetic syndrome Other MH diagnosis
3149 Hyperkinetic syndrome NOS Other MH diagnosis
6484 Mental disorders in pregnancy Other MH diagnosis
V402 Mental problems NEC MH V-code
V403 Behavioral problems NEC MH V-code
V409 Mental/behavior problems NOS MH V-code
V61 Other family circumstances MH V-code
V610 Family disruption MH V-code
V611 Marital problems MH V-code
V612 Parentchild problems MH V-code
V613 Problem with aged parent MH V-code
V614 Health problem in family MH V-code
V615 Multi-parity MH V-code
V616 Illegitimate pregnancy MH V-code
V617 Unwanted pregnancy NEC MH V-code
V618 Family circumstances NEC MH V-code
V619 Family circumstance NOS MH V-code
V663 Mental disorder convalescence MH V-code
V673 Psychiatric followup MH V-code
V701 Psychiatric exam -- authority required MH V-code
V702 General psychiatric exam NEC MH V-code
V710 Observation for mental conditions MH V-code
E950.7-E950.9, E951-E959 Suicide and self-inflicted injury by cause other than drugs or medicinal substances   Suicide and self-inflicted injury
MH = Mental Health.
ne = not equal.


TABLE A.4. Prescription Drug Codes
Drug Name NDC Code
Alcoholism Medications
Campral 0456-3330
Naltrexone HCl (Revia) 51285-275, 0555-0902, 52152-105, 185-39, 406-1170, 16590-897, 16729-81, 47335-326, 60793-430, 60793-431, 60793-433, 60793-434, 60793-435, 60793-437
Vivitrol 63459-300, 65757-300, 65757-301
Disulfiram (Antabuse) 51285-523, 51285-524, 64980-171, 64980-172, 65473-706
Opiate and Heroin Addition Medications
Subutex 12496-1310, 12496-1278
Suboxone 12496-1202, 12496-1208, 54868-5707, 54868-5750, 63629-4028, 63629-4034
Vivitrol 65757-300, 65757-301
Naltrexone HCl (Revia) See above
Nalmefene Hydrochloride (Revex)   10019-315, 10019-311, 11098-311
Other Drug Abuse Medications
Naloxone Hydrochloride (Narcan) 63481-365, 63481-368, 63481-359, 0409-1212, 0409-1215, 0409-1219, 63481-358, 63481-3771, 52584-469, 52584-782, 16590-556, 63739-463, 54868-2062,54868-6259, 60429-570, 68387-531, 548-1469, 548-3369, 43063-142, 43386-680, 52584-212, 52584-215, 409-1782
SOURCE: FDA's NDC database.
NOTE: NDCs are for the listed drug and for any generic equivalent.


TABLE A.5. Classification of SA/MH Treatment Services by Type
Types of SA Treatment Services SA-Specific Codes Other Behavioral Health Codes* Other Types of Identifiers
Emergency room care NA NA OT file claim with place of service code = 23
Inpatient care H0008, H0009    
Residential treatment H0010, H0011 H0017, H0018, H0019, S5145, S5146, T2048  
Intensive treatment program H0015, S9475, H2036, S9480, S9485, H0035, T2034  
Treatment program service H2035, S0201 H2012  
Individual/group psychotherapy   90804, 90805, 90807, 90808, 90809, 90810, 90811, 90812, 90813, 90814, 90815, 90816, 90817, 90818, 90819, 90821, 90822, 90823, 90824, 90826, 90827, 90828, 90829, 90875, 90876, 90846, 90847, 90849, 90853, 90857, G0410, G0411  
Other assessment/ screening/ intervention/ evaluation/ prevention/ treatment planning H0001, H0003, H0022, H0028, H0049, H0050, H0007, H0048, H0026, G0396, G0397, T1007, 99408 H0030, H2011, S9484, 90801, S9083, H0002, H1011, 96150, 96151, 90802, H0031, T1001, H1000, 90889, 90801, 90885, 96101, 96102, 96103, 96100, 96125, 99456, S9446, H1003, H0023, H0032, 00100, G8405 G8404, 96115, 96116, 96117, T2010, T2011, T1023, 96105, 96111, 96110, 96125  
Other medication management H0020, J0592, J1230, J3490, J2315, J8499, S0109 90862, H0034, H2010, H0033, M0064, T1502  
Other counseling/ therapy H0005, T1006 H0004, 90806, 90845, 90870, 90871, 90880, 96152, 99510, H2032, G0176, 96153, 96154, 96155  
Other case management or community supports H0006, T1007, T1012, T1009 T1016, T1017, H0037, H2015, H2016, H2021, G0177, S5110, H5111, T1027, H2014, H2017, H2018, H2027, H0025, H2023, H2024, H2025, H2026, H2019, H2020, S0280, S0281, 90882, H0039, H0040, T1024, H1004, H0036, H2022, S9482, H2033 H0038, T2040, T2041, G0409  
Detoxification H0012, H0013, H0014    
Housing (including halfway house) H2034 H0043, H0044  
Other H0016, H0047, T1010, T1011, T1013, T2025, H2037 90899  
* These behavioral health codes will be classified as SA treatments when they are associated with a primary SA diagnosis.
NA = not available.

Appendix B. FY 2011 SA Treatment Spending

TABLE B.1. FY 2011 SA Treatment Spending by SA Care Group
(in $ thousand)
State Inpatient Hospital Residential Treatment Outpatient Care Prescribed Drugs Managed Care Total
Alabama 6,215 0 3,790 630 0 10,635
Alaska 1,894 163 6,741 313 0 9,112
Arizona 2,447 10 42,201 0 116,417 161,075
Arkansas 4,127 0 1,589 132 0 5,848
California 24,577 0 221,880 1,069 171,971 419,497
Colorado 13,104 0 8,532 551 50,959 73,146
Connecticut 16,101 5,850 66,172 2,532 1,888 92,543
Delaware 723 23 4,909 483 7,425 13,563
District of Columbia 2,940 0 1,533 493 11,458 16,424
Florida 15,250 27 17,050 578 17,332 50,238
Georgia 5,698 3 7,968 136 8,288 22,092
Hawaii 457 1,111 2,775 126 4,735 9,204
Idaho 2,370 0 804 228 0 3,402
Illinois 46,377 1,094 59,062 2,664 4,534 113,731
Indiana 4,924 206 8,984 620 17,583 32,318
Iowa 1,920 0 660 244 7,985 10,809
Kansas 2,384 133 388 169 16,308 19,383
Kentucky 16,450 1,299 17,037 3,621 1,534 39,941
Louisiana 8,772 0 2,483 112 0 11,367
Maine* NA NA NA NA 0 55,107
Maryland 6,442 0 9,025 201 71,167 86,835
Massachusetts 14,015 1,980 47,085 12,474 32,344 107,899
Michigan 4,884 0 1,245 1,457 74,845 82,430
Minnesota 19,442 343 20,581 702 20,181 61,250
Mississippi 16,946 0 4,397 598 0 21,941
Missouri 11,266 1,913 28,979 1,112 30,595 73,865
Montana 3,851 826 2,419 482 0 7,579
Nebraska 10,066 810 2,499 120 2,579 16,073
Nevada 1,922 78 1,226 133 7,758 11,117
New Hampshire 1,479 0 5,328 635 0 7,443
New Jersey 9,863 411 17,547 1,517 56,433 85,771
New Mexico 910 0 907 22 34,176 36,014
New York 291,580 0 508,596 15,585 515,774 1,331,535
North Carolina 8,044 2,973 40,028 1,687 222 52,954
North Dakota 1,182 493 2,540 92 0 4,306
Ohio 16,361 0 84,892 1,429 100,836 203,518
Oklahoma 4,976 408 5,170 490 0 11,043
Oregon 2,048 4 6,705 109 51,299 60,165
Pennsylvania 8,565 14 2,719 4,802 111,738 127,838
Rhode Island 2,939 387 9,508 180 14,901 27,916
South Carolina 3,936 5,237 5,154 666 5,432 20,426
South Dakota 779 4,161 1,302 16 0 6,257
Tennessee 2,855 0 1,175 4,539 8,909 17,477
Texas 6,689 0 6,186 1,664 14,961 29,501
Utah 2,159 3 4,652 1,042 0 7,856
Vermont 2,228 7,583 6,711 5,284 0 21,806
Virginia 3,269 650 6,088 1,265 10,422 21,695
Washington 6,894 4,241 50,785 349 104,640 166,909
West Virginia 6,482 1,025 4,528 1,790 13,032 26,857
Wisconsin 14,634 176 12,711 2,668 13,758 43,947
Wyoming 767 4 1,002 86 0 1,859
Total 664,205 43,639 1,376,252 77,894 1,734,421 3,951,517
* Expenditures for Maine were imputed because only prescribed drug claims data were available in MAX 2008 for Maine. Imputations are only available overall. SA care group estimates were not developed.


TABLE B.2. FY 2011 Non-Core SA Treatment Spending
(in $ thousand)
State Fetal Exposure or Poisoning Other Conditions MH Expenditures with Secondary SA Diagnosis Non-MH Expenditures with Secondary SA Diagnosis
Alabama 637 397 1,528 9,752
Alaska 1,050 764 7,787 3,807
Arizona 1,999 4,573 21,894 71,397
Arkansas 325 1,146 12,252 3,581
California 6,790 47,412 78,013 155,809
Colorado 2,313 5,030 48,716 62,696
Connecticut 613 2,481 43,503 43,035
Delaware 239 968 3,684 14,638
District of Columbia 421 1,993 20,697 66,679
Florida 15,658 6,382 15,841 198,955
Georgia 1,275 4,937 13,669 86,666
Hawaii 222 483 3,735 14,598
Idaho 175 776 4,108 8,936
Illinois 1,275 15,166 70,014 173,238
Indiana 1,296 3,586 34,794 51,116
Iowa 739 2,428 8,815 32,533
Kansas 548 3,568 12,105 37,841
Kentucky 6,142 848 13,594 74,532
Louisiana 493 3,439 13,951 28,853
Maine 531 1,499 27,464 20,151
Maryland 2,849 6,895 93,516 89,845
Massachusetts 5,516 8,541 35,704 127,036
Michigan 1,970 10,397 40,099 126,295
Minnesota 10,591 5,713 48,642 59,004
Mississippi 340 1,560 23,396 25,790
Missouri 358 3,957 35,988 26,617
Montana 109 1,069 4,026 7,780
Nebraska 263 1,296 6,367 17,217
Nevada 506 1,325 8,364 15,619
New Hampshire 641 445 1,760 5,894
New Jersey 3,014 5,015 59,312 77,158
New Mexico 1,015 2,293 21,889 24,272
New York 6,749 36,190 334,403 714,649
North Carolina 875 6,400 29,894 87,035
North Dakota 20 406 3,880 6,585
Ohio 3,347 15,584 52,883 195,056
Oklahoma 190 3,056 16,519 35,687
Oregon 949 3,317 32,342 35,039
Pennsylvania 3,642 15,875 74,367 209,702
Rhode Island 320 1,407 11,097 6,031
South Carolina 294 3,056 6,887 60,448
South Dakota 68 727 3,210 5,254
Tennessee 1,580 3,394 2,675 37,071
Texas 2,496 24,491 32,925 184,274
Utah 319 1,063 498 9,574
Vermont 269 311 5,590 7,918
Virginia 1,343 3,254 15,931 90,353
Washington 2,307 8,183 81,123 125,621
West Virginia 278 1,762 24,629 20,923
Wisconsin 3,258 6,461 17,405 62,276
Wyoming 17 385 4,859 4,402
Total 98,236 291,703 1,586,344 3,659,241
Populations
Medicare Beneficiaries
Program
Medicare