Since HMOs do not have a claims database, they were at a disadvantage in participating in Medicare when it was introduced in 1965. After a number of largely unsuccessful efforts, Medicare implemented in 1985 the Adjusted Average Per Capita Costs [AAPCC] payment methodology under authorization from Congress in the Tax Equity and Fiscal Responsibility Act of 1982 [TEFRA]. See Zarabozo [2000] for a history of Medicare''s approaches to paying managed care plans in its first 35 years.
Under TEFRA, Medicare essentially paid participating HMOs a fixed dollar amount for each beneficiary that chose to join the plan. Because HMOs were thought to be more efficient than traditional care providers, the legislation prescribed that the capitated rate should be 95% of the average Medicare Part A [i.e., hospital] plus Part B [i.e., ambulatory] expenditures per beneficiary.
These rates were then adjusted by the mix of beneficiaries the plan enrolled, taking into account their age, gender, Medicaid status, whether or not they were in a nursing home, and whether the beneficiary was an active worker with coverage through an employer. Thus, the AAPCC paid 95% of the county average Medicare Part A and Part B expenditures adjusted for age, gender, Medicaid, institutional, and active worker status. This is analogous to a simple manual rating system.
One government study found that Medicare HMO enrollees had expenditures that were only 63% of the average of all beneficiaries in the six months prior to joining the HMO [Prospective Payment Assessment Commission 1996]. If this is so, Medicare is consistently overpaying for the services provided by Medicare HMOs, and higher-cost beneficiaries may be effectively denied access to a form of healthcare delivery that they may prefer. Improving the AAPCC
Almost immediately, Medicare funded research to try to improve its payment system. Such research requires data on the demographic, health status, and healthcare utilization characteristics of a relatively large number of heterogeneous people over time.
The RAND Health Insurance Experiment provided a data set that approximately satisfied these conditions.
It also recorded demographic and health status characteristics of the participants at baseline. In fact, much of the current knowledge about the measurement of health status had its genesis with this study. Thus, the study is well suited to examine alternative predictive models of utilization based on demographic characteristics, subjective and physiological measures of health status, and prior utilization.
While the analysis was somewhat more complicated than this, the study team essentially ran a series of regressions in which total inpatient and outpatient expenditures of each individual in year t were the dependent variables and were explained by alternative sets of potential risk characteristics. When prior-year utilization measures were included, these were expenditures in year t - 1. Because the overall RAND study was concerned with the effects of health insurance copayment arrangements on expenditures, the regressions also controlled for the health plan in which the person was enrolled. Because their interest was in improving the AAPCC model Medicare used, all of the models include the demographic or AAPCC factors.
The AAPCC variables by themselves explain 1.6% of total expenditures, 0.7% of inpatient expenditures, and 7.2% of outpatient variation. Notice that, in general, outpatient expenditures were more predictable than inpatient spending. This probably reflects the greater extent to which behavioral and chronic factors influence ambulatory use. Notice, too, that the%age of explained variation is quite small. Age, gender, location, and welfare status explained less than 2% of total expenditures.
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