Academic journal article Health Care Financing Review

Alternative Geographic Configurations for Medicare Payment to Health Maintenance Organizations

Academic journal article Health Care Financing Review

Alternative Geographic Configurations for Medicare Payment to Health Maintenance Organizations

Article excerpt

Alternative geographic configurations for Medicare payments to health maintenance organizations


Provisions of the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA) authorized that full prospective payments to health maintenance organizations (HMOs) for covered services provided to Medicare enrollees be set at a rate of 95 percent of the adjusted average per capita cost (AAPCC). The AAPCC is intended to be the average amount that Medicare would have paid for services had they been furnished in the local fee-for-service (FFS) market. In the implementation of the law, counties were chosen as the geographic unit for computation of AAPCC rates. The purpose of the study presented here was to investigate whether use of the county or some alternative geographic configuration would best comply with legislative requirements and best promote Medicare's policy goals for the HMO payment system.

In the current AAPCC formula, a projected level of national Medicare reimbursements per capita is multiplied by a county geographic index to obtain an estimate of projected per capita costs at the county level. This geographic index is a simple average of the ratios of county to national per capita reimbursements for the 5 most recent years of available data. The result is then multiplied by a third ratio factor accounting for differences in the composition of HMO enrollees versus FFS beneficiaries among the AAPCC risk classes (age, sex, welfare status, and institutional status) to yield the AAPCC. Questions have been raised about the appropriateness of using enrollees' county of residence as the geographic basis for setting capitation rates. County-based payment rates have been criticized for differing inexplicably and dramatically between seemingly similar adjacent counties (Greenlick, 1985). An often-cited example of the county "boundary problem" is the AAPCC rate for Part A for Prince Georges County, Maryland, which is about 50 percent higher than the rate for adjacent Montgomery County, Maryland.

Other than examples of the more extreme boundary differences, no empirical research has shown how much AAPCC rates typically vary between contiguous counties. To briefly explore this, we selected 33 counties comprising the service areas of HMOs in the Medicare Competition Demonstrations and all counties that were contiguous to any of these 33 counties. The simple average absolute percentage difference in the 1987 Part A or Part B rate between pairs of neighboring counties was found to be about 14 percent. This is considerably less than the roughly 25-percent difference between the AAPCC rate for noninstitutionalized, non-Medicaid males 65-69 years of age and the rate for similar males 70-74 years of age.

The year-to-year instability of AAPCC rates has also been an issue of concern (Milliman and Robertson, 1987). It has been suggested that this instability may be the result of a county having a relatively small number of Medicare beneficiaries or high HMO penetration rates. Only about one-third of the more than 3,000 counties in the Nation have Medicare FFS beneficiary populations of more than 5,000. The severity and importance of these potential problems are not entirely clear. However, one might suspect that the appropriateness of the county to represent local markets could vary among areas, because there are substantial variations in the sizes of counties among States and in the population concentration within many counties. Whereas there are 159 counties in the State of Georgia, the much larger State of California contains only 59 counties. The Los Angeles metropolitan statistical area (MSA) is a single county, but the Atlanta MSA is comprised of 18 counties.

Criteria for evaluating

alternative configurations

Geographic location is an important element of a capitation payment system simply because location has some effect on the cost of care. …

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