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Medicare+Choice: Payment and Service Areas. Final Report

Publication Date
Apr 30, 2005

Katie Merrell
Senior Analyst
Center for Health Administration Studies
University of Chicago

Submitted to:
Office of the Assistant Secretary for Planning and Evaluation
U.S. Department of Health and Human Services

Grant # 96ASPE284A


Executive Summary

The Balanced Budget Act of 1997 included a number of changes to Medicare managed care. The newly created Medicare+Choice program differs from its predecessor with regard to payment policies, enrollment and disenrollment policies, and the types of plans that can contract to provide care to Medicare beneficiaries. These changes were designed, in part, to expand the number and mix of private health plan choices available to beneficiaries in different markets across the country.

In fact, no new plan types were offered in the first year of Medicare+Choice and some existing plans withdrew from the program or reduced their service areas. It is difficult to know whether these changes were one-time responses to the new program or represent the types of annual changes that are likely to occur, since little is known about the factors that affect plans' decisions to participate in Medicare. The goal of this analysis is to identify those plan and county factors that are associated with the availability (or not) of Medicare+Choice plans in different markets. The analyses address two main outcomes: participation in Medicare+Choice in 1998 (and inclusion (or not) of each county from commercial service area in Medicare service area) and discontinuing participation (or dropping county from Medicare service area) in 1999.

Data are used from three sources. First, the universe of commercial health maintenance organizations (HMOs) is taken from Interstudy'sCompetitive Edge reports, which include self-reported data on commercial service areas, total enrollment, and other key measures. Second, Medicare+Choice plans and service areas are taken from the Health Care Financing Administration's (HCFA(now known as CMS)) contract reports. Some plans listed by HCFA(now known as CMS) as Medicare+Choice plans could not be matched to a plan in the Interstudy data, so are not included as Medicare+Choice plans in the analysis. Finally, unemployment rate, relative size of the elderly population, and other information about each county is taken the Area Resource File (ARF).

Controlling for other plan and market factors, the plan characteristics associated with higher probabilities of participating in Medicare in 1998 include: not being an independent practice association (IPA) model plan, being federally qualified, also participating in the Federal Employee Health Benefits Plan (FEHBP), having relatively large total enrollment, having relatively fewer enrollees per plan physician, having relatively more enrollees per plan hospital, and undergoing service area consolidation. The same model suggests that important county characteristics include: more commercial HMOs, relatively high Medicare risk index, urban location, higher price-adjusted Medicare payment rate, higher share of the population over 65, low hospital admission rates, high physician-to-population ratio, and high unemployment rate.

With regard to dropping out in 1999, some of the factors significantly associated with increased probability of participating are also significantly associated with staying in the program in 1999. For example, FEHBP participation is significantly associated with participating in Medicare and with NOT dropping out. Urban location, price-adjusted payment rates, and elderly population share all had this same pattern. Some factors, however, have the opposite effect on the drop-out decision than they did on the enrollment decision - fewer enrollees per physician, for example, is associated with higher probability of participating AND with higher probability of dropping out. Commercial service area changes, dramatic changes in total enrollment, number of commercial HMOs, and unemployment all have this effect of increasing both the chance that a plan participated AND that it dropped out. Finally, affiliation with a national chain and relatively lower shares of total enrollment in traditional HMO plan are significantly associated with the decision to drop out but are not important in the participation decision.


The Balanced Budget Act of 1997 (BBA) included provisions that dramatically affect the way that Medicare and its beneficiaries are integrated into the nation's health care system. By expanding the types of private health plans that are able to contract with Medicare, the BBA aims to move the program away from its fee-for-service roots to take advantage of the innovations in managed care service arrangements and financing that have occurred in the past decade. Through Medicare+Choice, beneficiaries in different parts of the country may be able to enroll in a variety of different private plans, presumably reducing their out-of-pocket costs through reduced cost-sharing or expanded benefits or increasing the quality or convenience of access to a full spectrum of care through an integrated plan. Although the BBA changed a number of aspects of how private plans contract with Medicare and receive capitated payments, it left in place some aspects of Medicare's earlier risk program. For example, plans are still able to define the service area covered by a Medicare+Choice contract.

As Medicare+Choice regulations were developed and scheduled for implementation throughout 1998, a large number of plans already in the risk program either decided not to renew their contract or redrew their service area. As a result, the Health Care Financing Administration(now known as Centers for Medicare and Medicaid Services(CMS)) (HCFA(now known as CMS)) reports (, Feb 1, 1999):

These withdrawals and service-area reductions affect slightly more than 400,000 beneficiaries in Medicare risk plans, representing approximately 6.5% of the more than six million risk enrollees. However, slightly more than 50,000 beneficiaries, or less than 1 percent of beneficiaries currently enrolled in Medicare risk plans, will not have access to another managed care plan.

If private plans become an increasingly important way for beneficiaries to receive health care, the causes of these types of changes are important to understand, particularly as they relate to specific policy characteristics. Whenever possible, policy design should presumably reduce, not contribute to, the volume of annual changes in the plan offerings to beneficiaries. A number of different factors, including implementation of the BBA itself, are likely to have contributed to these changes in 1998. Although some degree of churning in plan offerings in each community may be inevitable each year, it is important to understand the factors that affect plan decisions so that policymakers can interpret and respond to them.

Medicare policies about service area design are likely to affect plan behavior each year. Unfortunately, there is little information in the research literature about how plans and beneficiaries react to such policy changes. This report therefore addresses two distinct but closely related questions:

  • What are the key factors that led plans to reconfigure their Medicare risk plan service areas in 1998 or to not renew their contracts with Medicare?
  • Should Medicare continue to allow plans to design their own Medicare service areas, or should there be predetermined Medicare+Choice contract areas in each market area?

Ultimately this analysis aims to understand what factors determine whether private plans choose to contract with Medicare under Medicare+Choice. Theoretically, a plan supply equation could be developed and estimated to isolate the effect of local market factors, payment policies, and other relevant factors on plan participation. In addition to the usual challenges underlying such an exercise, this approach has two important problems. First, the historical use of plan-designated service areas complicates the notion of a market-based analysis, since plans' service areas are endogenous to the market phenomenon and policy factors to be analyzed. As a result, it is not clear how (or whether) markets could be defined that are relevant to how plans view their options and ultimately design their service areas. This problem is easily illustrated by the mismatch between plans' reported commercial service areas and their Medicare service areas - which should be taken as defining their appropriate market? Second, it is not clear how (or whether) Medicare participation fits into plans' decisions to enter particular geographic markets at all. Medicare policy and populations may have important effects on the numbers and types of plans that exist in some markets, for example in south Florida, while Medicare participation may be a more simple strategic decision among existing plans in other markets, such as the upper Midwest. If the existence of particular plans in particular markets is due, in part, to an assessment of the potential Medicare market, then a daunting intellectual problem arises. Those plans that considered entering a geographic market and decided NOT to - possibly because of the perceived opportunities (or lack thereof) in the Medicare segment of the market - are unobservable. As a result, any Medicare+Choice plan supply model that simply takes as candidate entrants those plans currently operating in local commercial markets may miss important factors and misstate the effect of studied factors. These two issues combined have foiled previous attempts to develop a credible, robust market Medicare risk plan supply model.

Before undertaking the development of such a model, or modified versions similar to Welch (1996), it is helpful to describe the characteristics of plans that participated in Medicare+Choice, the counties where such plans were available, and then how the two appear to interact. Insights into the plan and county factors that affect participation can then be used to inform analysis of the second main question, whether Medicare should continue to allow plans to describe their own service areas or should adopt predetermined contract areas. Again, before undertaking such an analysis, it is helpful to first describe several candidate geographic constructs that might be used to set such areas.

This report begins with a description of key measures and data sources. The results presented next are descriptive only, but lay the groundwork for more sophisticated analysis. In addition to remaining opportunities for more advanced analyses of these same data, the recent release of information about 2000 plan contracts creates additional opportunities for investigating these issues.

Measures and Data Sources

The analyses described below are based on measures of the Medicare population and policies, commercial plan characteristics, and county attributes (Table 1). These are developed from three main data sources.

Medicare. The Health Care Financing Administration(now known as Centers for Medicare and Medicaid Services(CMS)) (HCFA(now known as CMS)) reports the number of Medicare beneficiaries, risk plan enrollment, service area, and plan participation data on monthly or quarterly bases through its web page. Only risk plans are included in the analysis, so that a plan that switches from a cost contract in 1998 to a risk contract in 1999 is considered a new plan. In general, numbers are used from late in 1998 (typically September) and early in 1999 (typically April) because of the project's focus on service area changes between 1998 and 1999. Although plans can describe their Medicare+Choice service areas to include only parts of counties based on zip code, most available data report numbers of eligible and enrolled beneficiaries by county, not zip code. As a result, county-level data are used, which may overstate the effect of plan service area reductions and new plan offerings.

HCFA(now known as CMS) also reports payment rates by county. Because of price differences by county, some analyses adjust these payment rates by a 1997 wage index. This is an imperfect measure of geographic price differences, but the resulting adjusted "real" payment rate is more comparable across areas than the nominal rate.

HCFA(now known as CMS) data were also used to create a county-level demographic index. Based on 1995 beneficiary data and demographic risk adjustment factors, this index describes differences in beneficiary populations with regard to age, sex, institutional status, working status, and participation in Medicaid.

Commercial Plans. Information about health maintenance organizations' (HMO) commercial enrollment and service areas is available from InterStudy's Competitive Edge. The July 1998 version was used in the analyses below, presumably describing HMOs at about the time they were deciding whether or not to continue (or join) Medicare managed care. Problems with data on commercial HMO products and enrollment have been documented by others (PPRC, 1997). Despite this, the InterStudy data have been widely used by health sector analysts and are considered the best source of standardized information about plans nationwide.

The InterStudy data report a number of plan characteristics. The analyses below use InterStudy as the source for plan enrollment level and growth, tax status, age, affiliation, participation in Medicaid and the Federal Employees Health Benefits Plan (FEHBP), numbers of physicians and hospitals, and service area. Changes in service area are based on comparisons between the InterStudy data from July 1998 and those from January 1995.

Counties. Geographic and demographic data about counties has been used from the Bureau of Health Professions' Area Resource File (ARF). The ARF has been used to describe local health markets (admission rates, beds, physicians) and local economic conditions (unemployment and median incomes (again adjusted for geographic variation in wages)).

Medicare+Choice Participation. The focus on describing plans by whether or not they participated in Medicare+Choice requires merging data from HCFA(now known as CMS) and InterStudy. Some Medicare+Choice plans could not be matched with a commercial plan described by InterStudy. For the purposes of some of the analyses, plans were considered to be in Medicare+Choice only if a match could be made between the HCA and InterStudy data (Figure 1). Not all commercial plans that matched a Medicare+Choice plan reported having Medicare enrollees, nor did all plans that reported Medicare enrollees match a Medicare+Choice plan. The lack of reported Medicare enrollment by some plans that were labeled as Medicare+Choice does not raise serious concerns of erroneously calling plans Medicare+Choice participants when they are not, because the match with HCFA(now known as CMS) data on Medicare+Choice plans was made based on compelling correspondence between plan name, address, and other identifying information. Conversely, since some Medicare+Choice plans could not be matched to InterStudy plans, some plans are incorrectly marked as not being in Medicare+Choice when in fact they are. This will presumably downward bias measured differences between the two groups. This understatement of the number of Medicare+Choice plans and the counties they serve complicates comparisons with information reported by HCFA(now known as CMS).

Similarly, for plan-county level analyses, a county was only considered in Medicare+Choice if it was listed in the commercial service area by InterStudy and the Medicare+Choice service area by HCFA(now known as CMS). In many cases, the Medicare+Choice service area included counties not listed as part of plans' commercial areas, but for these analyses these counties were not included. The plan-county pairs are therefore based solely on the commercial service area, with individual plan-county observations considered to be in Medicare+Choice only if the plan matched a Medicare+Choice plan and the county was in the Medicare+Choice service area, as described by HCFA(now known as CMS). This mismatch between commercial and Medicare+Choice service areas merits additional analysis.


Analyses were done for several different types of measures. First, data from HCFA(now known as CMS) were used to describe counties with regard to changes in Medicare+Choice offerings. Next, plan-level analysis was done based on InterStudy data, with HCFA(now known as CMS) matches taken as Medicare+Choice plans, to investigate plan attributes associated with 1998 Medicare+Choice participation and withdrawals from the program in 1999. County-level analysis was then done to identify county-level attributes associated with these two outcomes. This analysis is designed to match the InterStudy plan analysis, so differs from the initial, HCFA(now known as CMS)-based description of program changes. The plan and county information were then combined to disentangle the effects of plan and county characteristics on the county-level plan decision to participate in 1998 and to withdraw in 1999. The final results describe metropolitan statistical areas (MSAs) as Medicare+Choice areas. As mentioned before, these results are descriptive in nature, so provide the groundwork for more sophisticated modeling of plan behavior and the role of policy factors in participation and withdrawal decisions.

Service Area Changes, 1998-1999. This first analysis of changes in plan Medicare+Choice service areas, withdrawals, and new offerings is based on categorizing counties with regard to changes in Medicare+Choice plan offerings. Seven categories of counties are considered, based on the availability of plans in September of 1998 and how that changed (or not) by April 1999:

Definition of County Type for Analysis of Medicare+Choice Plan Offerings
County type Number of Plans 9/98 Relationship between number plans 4/99 and 9/98 Change in plans?
No plans, no change 0 Equal No
Gained all plans 0 More Yes
No change >0 Equal No
Lost all plans >0 Less Yes
Net gain >0 More Yes
Net loss >0 Less Yes
Balanced change >0 Equal Yes

So, for example, the Balanced Change group differs from the No Change by having had a change in the specific plans offered, although both had the same number of plans available in each time period.

This ignores any sub-county changes - if a plan's service area in 1998 included only a small portion of a county and this was withdrawn in 1999 then the entire county is counted as having lost a plan. As a result, the numbers of beneficiaries affected by changes in plan offerings are likely overstated. This analysis is based solely on information from HCFA(now known as CMS).

According to this categorization, two-thirds of counties had no plans and no change (Table 2). These counties contained about 25 percent of the nation's Medicare beneficiaries as of December 1998. An equal share of beneficiaries live in the 559 counties that had no change in plans offered between the two time periods, so overall about half of beneficiaries were unaffected by changes in plan participation decisions and service area changes. Conversely, nearly 40 percent of beneficiaries live in counties that had a net loss in plan offerings. These 271 counties account for nearly two-thirds of risk plan enrollees.

Nearly 2 percent of beneficiaries live in counties that lost all plans between September 1998 and April 1999. These 84 counties included 1,687 plan enrollees.

Those counties that lost all plans typically went from one to zero plans, while those that gained all plans went from zero to one plan (Table 3). Other groups of counties that lost plans - those with a net loss in plan offerings and those with balanced change - still have more plans on average than all other types of counties. This could be evidence that some markets have become (over)saturated with plans while others still have unmet demand for Medicare managed care and so will accommodate new entrants.

At this simple level of analysis, changes in plan offerings at the county level do not obviously correlate with payment rates (Table 3). Although those counties that lost all plans have relatively low payment rates, those counties that went from none to some plans have even lower rates on average. Similarly, those with a net loss in plans have higher rates than those with net gains.

Finally, plan changes at the county level are not obviously associated with general local market economic measures such as the unemployment rate or local wages (Table 4). Areas with net loss of plans had unemployment rates similar to those that had net gains. The wage index was highest in counties that had a net loss of plans and relatively low in counties that gained all plans or that lost all plans. A county-level demographic index, based on the factors historically used by HCFA(now known as CMS) to risk-adjust plan payments, is lowest in the counties that had no plans in both periods and highest in those with net gain in plans or with balanced change. This last finding may reflect how plans consider not only payment rates but also (perceived or real) risk status of local populations in their decisions. It may also relate to inadequacies in the risk adjustment process that will be phased out in 2000 which may be helpful to understand, especially if it would help anticipate plans' likely response to introduction of the new risk adjustment process next year.

To consider these different possibilities, plan-level, county-level, and plan-county analyses were conducted, based on service areas and other plan characteristics as described by InterStudy.

Plan Participation in 1998. Simple descriptive statistics suggest that, compared to all commercial plans, those participating in Medicare+Choice in 1998 were more likely to be federally qualified, have FEHBP enrollees, be part of a national chain, larger, be older, be less physician-intensive, be less hospital-intensive, and have expanded service areas in the past several years (Table 5).

These simple means are difficult to interpret, however, because some of these factors - such as age and size - are likely to be associated with one another. Simple ordinary least-squares regressions were run to analyze the relationships among these factors (Table 6). These results show that, at significance levels of 5 percent or better, there are some important differences between those plans that participated and those that did not. In particular, those that participated in Medicare+Choice in 1998 are:

  • more likely to be federally qualified,
  • less likely to have Medicaid patients,
  • large, and
  • not physician-intensive.

The estimates from this linear-probability model are reliable with regard to sign and significance, but their magnitude should be interpreted with caution. It explains nearly one-third of the variation in plan Medicare+Choice participation.

Plan Withdrawal in 1999. Among the plans that participated in 1998, about 35 withdrew from the program in 1999 (Table 5). Based on mean characteristics, these plans appear to be more likely to be IPA model plans, to be for-profit firms, to have Medicaid enrollees, to not have FEHBP enrollees, to be in a national chain, to be younger, to be physician and hospital intensive, to be less likely to have been involved in a corporate split in the past few years, to have had service area changes in the past few years, and to have non-typical enrollment growth (up or down). Again, however, the relationships between these many characteristics make it hard to interpret these simple means. Based on a linear-probability model, only affiliation with a national chain is associated with a significant difference in dropout probability - those in chains were more likely to withdraw from Medicare+Choice in 1999 (Table 6). Chain affiliation is not associated with a significant difference in joining Medicare+Choice in the first place but, once they've joined, these plans appear somewhat more likely to have dropped out in 1999. Once all of the factors are accounted for, other differences between plans by dropout status are insignificant.

Again, the use of a linear probability model results in estimates that are reliable with regard to sign and statistical significance but not magnitude. This model accounted for only 2 percent of the variance around the dropout decision.

Counties with Medicare+Choice Plans, 1998. Based on a simple comparison of means, counties with Medicare+Choice plans in 1998 appear to be fairly different from all counties in many ways (Table7). Counties with Medicare+Choice plans have different health care markets, with more commercial plans, higher admission rates, fewer hospital beds, and more physicians per capita. They have different populations, with relatively fewer people over 65, although these tend to be in higher demographic risk groups. They also have different local economic characteristics, with higher adjusted incomes and lower unemployment rates.

Most of these differences are statistically significant even when other differences are controlled for (Table 8). In particular, the chance that a county has a Medicare+Choice plan increases if:

  • there are more commercial HMOs;
  • the Medicare demographic risk index is higher;
  • it is in an urban area;
  • it has higher price-adjusted Medicare+Choice payment rate;
  • the population share over 65 is high;
  • hospital admission rates are low;
  • there are more MDs per capita; and
  • the unemployment rate is relatively high.

These factors explain nearly half of the variation in the probability that a county had a Medicare+Choice plan in 1998.

Counties Losing Plans, 1999. Simple means suggest that counties that lost plans in 1999 are fairly similar to those with plans in 1998, with a few exceptions (Table 7). For example, counties losing plans had relatively more commercial plans, were more likely to be in urban areas, had more Medicare+Choice plans, and higher Medicare+Choice enrollment rates than those counties that did not lose a plan.

A simple regression suggests that only two of these factors - number of commercial plans and number of Medicare+Choice plans - are significantly significant when other factors are held constant (Table 8). The fact that the number of commercial plans increases both the chance that a county will have Medicare+Choice plans and that it will lose plans suggests that there is some level of plan churning that may be likely to occur once there are a lot of plans in a market. Structural or behavioral models are necessary to test this hypothesis. The simple linear probability model accounts for over one-quarter of the variance around the county dropout probability.

Plan-County Participation, 1998. The inclusion of a particular county in a particular plan's Medicare+Choice service area is a function of both plan and county characteristics. To understand how the two relate, Medicare+Choice participation can be explored at the plan-county level, where plan-county pairs are determined by plan's commercial service areas. As a result, plans with a large number of counties will contribute more cases than other plans, so that means of plan-level characteristics will be weighted toward those plans with many counties in their service areas. So, for example, at the plan-county level, 52 percent were IPA model plans (Table 9), compared with 49 percent of plans at the plan level (Table 5). This implies that IPA plans have more counties in their commercial service areas than other plan types.

At the plan-county level, those in Medicare+Choice in 1998 differed from the universe in most characteristics studied (Table 9). In the regression, the county-level factors had the exact same pattern of sign and significance as they had in the county analysis above (Table 10). There were some differences, however, in the plan-level factors. Several factors that had been insignificant at the plan level are significant at the plan-county level: IPA model, presence of FEHBP enrollees, enrollees per hospital, reduction in plan service area since 1995, and dramatic change in enrollment over two years (up or down). Similarly, the presence of Medicaid patients had a significant negative effect on the probability of participation at the plan level but is insignificant in the plan-county analysis. The change in importance of whether or not a plan serves Medicaid patients in the different models suggests that this variable may have been capturing market characteristics in the plan-level models that are better controlled for in the plan-county models.

Plan-County Dropouts, 1999. At the plan-county level, dropouts look like 1998 Medicare+Choice participants, with many exceptions (Table 9). They are more similar to non-participants with regard, for example, to presence of FEHBP enrollees, enrollees per MD, and enrollees per hospital. Controlling for all other differences, factors associated with dropping out include:

  • presence of Medicaid patients in plan;
  • no presence of FEHBP patients in plan;
  • affiliation with national chain;
  • short time in operation;
  • few enrollees per MD;
  • having reduced service area since 1995;
  • dramatic enrollment changes in past two years;
  • low share of enrollees in traditional HMO product;
  • non-urban location;
  • low price-adjusted payment rate;
  • low population share over 65; and
  • high unemployment rate.

In the plan-level estimates above, only national chain affiliation had a statistically significant association with dropping out. In the county-level estimates, numbers of commercial and Medicare plans had been significant, but they are not at the plan-county level.

MSAs as Medicare+Choice Area. In addition to understanding plan participation and dropout decisions, this analysis also aims to investigate the concept of predetermined Medicare+Choice areas. Analysis of plan response to such a policy change depends on a better understanding of the determinants of plan behavior than is currently available. It is possible, however, to describe candidate areas with regard to Medicare+Choice characteristics and commercial markets. Only metropolitan statistical areas (MSAs) are considered below, although other reasonable candidate area definitions exist, such as Medicare Fee Schedule areas, modal commercial areas, and Bureau of Economic Analysis Economic Areas.

There would be 365 MSA-based areas, 240 of which had at least one Medicare+Choice plan in fall of 1998 (Table 11). According to simple means, these 240 differ from all MSAs in many ways:

  • over 50 percent more Medicare beneficiaries;
  • higher nominal Medicare+Choice payment rates (both at county and beneficiary level); and
  • more commercial plans (11.80 v. 9.92).

Within MSAs with at least one Medicare+Choice plan, there were an average of 4.1 plans. Plans served an average of 3.2 MSAs. Among plans serving more than one MSA, enrollment was fairly evenly spread, with an average of 35 percent of enrollees in each served MSA.


Health Care Financing Administration(now known as Centers for Medicare and Medicaid Services(CMS)),, summer/fall 1999.

InterStudy, Competitive Edge 5.2 Part I: HMO Directory (Minneapolis, MN: InterStudy, 1995).

InterStudy, Competitive Edge 9.1 Part I: HMO Directory (Bloomington, MN: InterStudy, 1999).

Physician Payment Review Commission, Annual Report to Congress 1997(DC: PPRC, 1997).

Welch, W. Pete. "Growth in HMO Share of the Medicare Market, 1989-1994", Health Affairs, Fall 1996. 201-214.

Tables and Figure

Table 1: Key Measures and Their Source

Measure Source
Medicare+Choice participation HCFA(now known as CMS); match between HCFA(now known as CMS) and InterStudy 9.1
Plan model type (IPA, staff, group, mixed, etc.) InterStudy 9.1
Plan tax status (not-for-profit, for profit) InterStudy 9.1
Federally qualified InterStudy 9.1
Plan reports Medicaid enrollees InterStudy 9.1
Plan reports FEHBP enrollees InterStudy 9.1
National chain InterStudy 9.1
Total plan enrollment InterStudy 9.1
Plan age (yrs.) InterStudy 9.1
Enrollees per MD InterStudy 9.1
Enrollees per hospital InterStudy 9.1
Plan changes since 1995: 
Split into two or more plans
Smaller service area
Larger service area
InterStudy 9.1; InterStudy 5.2
High enrollment growth between 1996 and 1998 InterStudy 9.1
Decline in enrollment between 1996 and 1998 InterStudy 9.1
Percent enrollees in traditional HMO products InterStudy 9.1
Number commercial HMOs in county InterStudy 9.1
County demographic risk index HCFA(now known as CMS)
County in an MSA? ARF
County price-adjusted M+C rate HCFA(now known as CMS)
Percent county population over 65 ARF
County admission rate per ARF
County beds per ARF
County MDs per ARF
Price-adjusted median income ARF; HCFA(now known as CMS)
Unemployment rate 1996 ARF
Number Medicare plans 1998 HCFA(now known as CMS)
Change in payment rate HCFA(now known as CMS)
Medicare enrollment rate 1998 HCFA(now known as CMS)

Table 2: County-level Mean Medicare Beneficiaries and Managed Care Enrollees, by Change in Risk Plans Available 9/98-4/99

County Type Number Counties Medicare Beneficiaries, 12/98 Medicare Risk Enrollees, 12/98
County Mean Total Number Beneficiaries Percent All Beneficiaries County Mean Total Number Enrollees Percent All Enrollees
No plans, no change 2076 4768 9,899,045 25.64 2 4,486 0.08
Gained all plans 16 12101 193,609 0.50 3 52 0.00
No change 559 17623 9,851,375 25.52 2388 1,334,796 22.66
Lost all plans 84 9093 763,852 1.98 20 1,687 0.03
Net gain 35 21614 756,498 1.96 2286 80,018 1.36
Net loss 271 56292 15,255,112 39.51 14009 3,796,545 64.45
Balanced change 32 58979 18,87,318 4.89 21039 673,250 11.43
ALL COUNTIES 3073 12563 38,606,809 100.00 1917 5,890,834 100.00

Source: Analysis of Health Care Financing Administration(now known as Centers for Medicare and Medicaid Services(CMS)) data.

Table 3: County-Level Mean Number of Risk Plans and Payment Rates by Change in Risk Plans Available 9/98-4/99

County Type Number Counties Mean Number Risk Plans in County, 9/98 Mean Number Risk Plans in County, 4/99 Mean County Medicare Payment Rate, 1998 Mean County Medicare Payment Rate, 1999
No plans, no change 2076 0 0 401.10 411.67
Gained all plans 16 0 1 385.42 395.53
No change 559 2 2 435.94 445.70
Lost all plans 84 1 0 405.41 415.16
Net gain 35 2 3 436.21 445.80
Net loss 271 5 4 488.89 498.86
Balanced change 32 5 5 525.81 537.02
ALL COUNTIES 3073 1 1 416.92 427.26

Source: Analysis of Health Care Financing Administration(now known as Centers for Medicare and Medicaid Services(CMS)) data.

Table 4: County-Level Mean Unemployment, Wage Index, and Demographic Index by Change in Risk Plans Available 9/98-4/99

County Type Number Counties Mean County Unemployment Rate, 1996 Mean County HCFA(now known as CMS) Wage Index, 1997 Mean County Demographic Index, Medicare Beneficiaries, 1995
No plans, no change 2076 6.07 0.78 1.01
Gained all plans 16 6.69 0.84 1.04
No change 559 6.01 0.87 1.04
Lost all plans 84 5.96 0.87 1.04
Net gain 35 5.45 0.89 1.06
Net loss 271 5.51 1.01 1.05
Balanced change 32 6.26 0.94 1.06
ALL COUNTIES 3073 6.00 0.82 1.02

Source: Analysis of Health Care Financing Administration(now known as Centers for Medicare and Medicaid Services(CMS)) and Area Resource File data.

Table 5: Characteristics of Plans that Participated in Medicare+Choice in 1998 and Those that Dropped Out in 1999

  All commercial plans 1998 Was in M+C 1998 Was in M+C 1998, Dropped in 1999
IPA model 49% 50 66
Not for profit 27% 25 17
Federally qualified 37% 57 57
Has Medicaid pts 38% 40 46
Has FEHBP pts 34% 49 43
National chain 59% 73 83
Total enrollment (log) 10.70 11.73 11.58
Plan age 11.38 yrs 14.37 12.96
Total enrollees per MD 40 50 25
Total enrollees per hospital 3312 4977 2338
Plan changes since 1995:
   Split 4% 6 0
   Smaller service area 9% 10 14
   Larger service area 42% 52 57
High total enroll growth 11% 14 17
Decline in total enrollment 20% 20 17
Percent total enrollment in traditional HMO model 12% 14 13
N 647 248 35

Source: Analysis of data from InterStudy Competitive Edge 9.1 and the Health Care Financing Administration(now known as Centers for Medicare and Medicaid Services(CMS))

Note: Only those Medicare+Choice plans that could be matched with an InterStudy plan are included in this analysis. Plan characteristics are taken from InterStudy.

Table 6: Regression Estimates - 1998 Plan Participation and 1999 Dropouts

  Was in M+C 1998 Dropped M+C in 1999
Coefficient estimate p-value Coefficient estimate p-value
Intercept -1.35 0.0001 0.21 0.4712
IPA model 0.02 0.6068 0.09 0.0660
Not for profit -0.05 0.2854 0.02 0.8126
Federally qualified 0.10 0.0115 0.03 0.5155
Has Medicaid pts -0.09 0.0152 0.09 0.0862
Has FEHBP pts 0.05 0.1875 -0.06 0.2637
National chain 0.06 0.1485 0.13 0.0387
Total enrollment (log) 0.16 0.0001 -0.02 0.0535
Plan age (yrs.) 0.005 0.1039 -0.001 0.8875
Total enrollees per MD -0.001 0.0003 -0.0005 0.4340
Total enrollees per hospital 0.000 0.0780 -0.000 0.6445
Plan changes since 1995:
Split 0.10 0.2856 -0.15 0.1766
Smaller service area 0.07 0.2907 0.07 0.3757
Larger service area -0.04 0.3588 0.01 0.8258
High total enrollment growth 0.02 0.6973 0.02 0.8159
Decline in total enrollment -0.06 0.1750 0.01 0.9105
Percent total enrollment in traditional HMO model -0.00 0.4685 -0.01 0.2490
Dependent variable mean 0.39 0.14
N 605 235
R2 0.3112 0.0202

Source: Analysis of data from InterStudy Competitive Edge 9.1 and the Health Care Financing Administration(now known as Centers for Medicare and Medicaid Services(CMS))

Note: Only those Medicare+Choice plans that could be matched with an InterStudy plan are included in this analysis. Plan characteristics are taken from InterStudy.

Table 7: Characteristics of Counties with Medicare+Plans in 1998 and that Lost Plans in 1999

  Mean, All Counties Counties with M+C Plans, 1998 Counties that Lost M+C Plans, 1999
Number commercial HMOs 5.3 10.23 11.9
Demographic risk index 1.02 1.05 1.05
In an MSA 27% 76 83
Price-adjusted M+C rate $512 496 498
Pop share > 65 17% 14 13
Admission rate per pop 87 101 101
Beds per population 4.2 3.5 3.4
MDs per population 1.1 1.8 1.9
Price-adjusted median income $22040 22729 22970
Unemployment rate 1996 6.0% 5.5 5.5
Number Mcare plans 9/98 0.9 4.2 5.5
Change in payment rate 2.5% 2.1 2.1
Mcare enrollment rate 98 3% 14 17
N 3073 585 308

Source: Analysis of data from InterStudy Competitive Edge 9.1 and the Health Care Financing Administration(now known as Centers for Medicare and Medicaid Services(CMS))

Note: Only those Medicare+Choice plans that could be matched with an InterStudy plan are included in this analysis.

Table 8: Regression Estimates - Presence of M+C Plan in County in 1998 and Loss of Plan in 1999

  County has M+C plan(s) 1998 County loses plan 1999
Parameter estimate p-value Parameter estimate p-value
Intercept -1.07 0.0001 1.09 0.0374
Number commercial HMOs 0.05 0.0001 0.02 0.0097
Demographic risk index 0.69 0.0001 -0.88 0.0597
In an MSA 0.24 0.0001 -0.02 0.7669
Price-adjusted M+C rate 0.0003 0.0001 -0.0001 0.5497
Pop share > 65 0.36 0.0051 -0.76 0.0949
Admission rate per pop -0.0003 0.0016 -0.0001 0.8087
Beds per population 0.001 0.3358 0.002 0.8020
MDs per population 0.04 0.0001 -0.02 0.3709
Price-adjusted median income -0.000 0.8451 0.000 0.2999
Unemployment rate 1996 0.005 0.0081 0.01 0.0906
Number Mcare plans 9/98     0.08 0.0001
Change in payment rate     -0.07 0.1144
Mcare enrollment rate 98     0.26 0.1835
Mean of dependent variable 0.19 0.53
N 3072 584
R2 0.4478 0.2757

Source: Analysis of data from InterStudy Competitive Edge 9.1 and the Health Care Financing Administration(now known as Centers for Medicare and Medicaid Services(CMS))

Note: Only those Medicare+Choice plans that could be matched with an InterStudy plan are included in this analysis.

Table 9: Characteristics of Plan-County Pairs, for All, 1998 Participants, and 1999 Dropouts

  Mean, All Plan-County Pairs 1998 M+C 1999 Dropouts
Plan characteristics:
IPA model 52% 49 48
Not for profit 22% 20 11
Federally qualified 39% 59 49
Has Medicaid pts 38% 42 50
Has FEHBP pts 36% 51 35
National chain 64% 74 87
Total enrollment (log) 11.1 12.0 11.9
Plan age (yrs.) 11.7 years 14.6 12.7
Total enrollees per MD 41 51 26
Total enrollees per hospital 2822 5282 2828
Plan changes since 1995:
    Split 5% 3 4
    Smaller service area 6% 13 18
    Larger service area 54% 55 48
High total enrollment growth 13% 15 21
Decline in total enrollment 22% 22 25
Percent total enrollment in traditional HMO model 14% 13 15
County characteristics: 
Number commercial HMOs 8.1 11.2 11.8
Demographic risk index 1.03 1.05 1.05
In an MSA 45% 80 77
Price-adjusted M+C rate $505 506 492
Pop share > 65 15% 14 13
Admission rate per pop 90.5 104.4 97.1
Beds per population 3.7 3.6 3.6
MDs per population 1.3 2.0 2.0
Price-adjusted median income $22284 23153 23189
Unemployment rate 1996 5.78% 5.48 5.69
Number Mcare plans 9/98 2.0 5.2 5.5
Change in payment rate 2.4% 2.1 2.1
Mcare enrollment rate 98 6% 16 15
N 16340 2041 415

Source: Analysis of data from InterStudy Competitive Edge 9.1 and the Health Care Financing Administration(now known as Centers for Medicare and Medicaid Services(CMS))

Note: Only those Medicare+Choice plans that could be matched with an InterStudy plan are included in this analysis. Plan characteristics are taken from InterStudy.

Table 10: Regression Estimates - Plan-County 1998 Inclusion in M+C and 1999 Drop Outs

  Plan-county in M+C 1998 Plan-county dropped in 1999
  Coeff est p-value Coeff est p-value
Intercept -0.91 0.0001 0.52 0.0836
Plan characteristics:
IPA model -0.03 0.0001 -0.01 0.4490
Not for profit -0.01 0.0806 0.03 0.3302
Federally qualified 0.05 0.0001 0.009 0.6519
Has Medicaid pts 0.002 0.7672 0.08 0.0002
Has FEHBP pts 0.04 0.0001 -0.14 0.0001
National chain 0.01 0.1466 0.22 0.0001
Total enrollment (log) 0.03 0.0001 0.01 0.1951
Plan age (yrs.) 0.001 0.1037 -0.003 0.0226
Total enrollees per MD -0.0004 0.0001 -0.001 0.0001
Total enrollees per hospital 0.000 0.0001 -0.000 0.5427
Plan changes since 1995:
    Split 0.04 0.0874 -0.04 0.4327
    Smaller service area 0.08 0.0001 0.11 0.0006
    Larger service area -0.04 0.0001 -0.05 0.0171
    High total enrollment growth 0.02 0.0117 0.07 0.0124
Decline in total enrollment 0.02 0.0006 0.09 0.0002
Percent total enrollment in traditional HMO model -0.000 0.1491 -0.001 0.0382
County characteristics:
Number commercial HMOs 0.01 0.0001 0.005 0.1324
Demographic risk index 0.18 0.0031 -0.25 0.2938
In an MSA 0.11 0.0001 -0.08 0.0044
Price-adjusted M+C rate 0.0005 0.0001 -0.0004 0.0013
Pop share > 65 0.19 0.0040 -1.21 0.0001
Admission rate per pop -0.0002 0.0001 -0.0002 0.3705
Beds per population 0.001 0.4216 0.003 0.5387
MDs per population 0.02 0.0001 -0.002 0.8052
Price-adjusted median income 0.000 0.6372 0.000 0.4238
Unemployment rate 1996 0.003 0.0019 0.02 0.0001
Number Mcare plans 9/98     -0.001 0.0700
Change in payment rate     0.01 0.7249
Mcare enrollment rate 98     0.15 0.0973
Mean of dependent variable 0.13 0.21
N 14602 1913
R2 0.1740 0.1479

Source: Analysis of data from InterStudy Competitive Edge 9.1 and the Health Care Financing Administration(now known as Centers for Medicare and Medicaid Services(CMS))

Note: Only those Medicare+Choice plans that could be matched with an InterStudy plan are included in this analysis. Plan characteristics are taken from InterStudy.

Table 11: Medicare+Choice Payment Rates and Enrollment by MSA

  All MSAs Had Medicare+Choice Plan September 1998
Number 365 240
Mean number counties 8.4 8.9
Mean Medicare eligibles 1998 105,788 162,323
Mean M+C enrollees 1998 16,141 24,539
Mean M+C payment rate 1997:
    County $425 $446
    Eligibles $467 $481
    Enrollees $517 $518
Mean number commercial plans 9.92 11.80
Mean number M+C plans   4.13
Mean number areas per plan   3.20
Mean median plan share within area, excluding plans in 1 area   35%

Source: Analysis of data from InterStudy Competitive Edge 9.1 and the Health Care Financing Administration(now known as Centers for Medicare and Medicaid Services(CMS)).

Location- & Geography-Based Data
County Data