Capitation payment: using predictors for medical utilization to adjust rates.
The current adjusted average per capita cost methodology has been strongly criticized because the subgroup classifications explain minimal interpatient variation in utilization, therefore providing incentives for biased selection. In this article, we review previous investigations of predictors of medical utilization that might be included in the adjusted average per capita cost: perceived health status, functional health status, prior utilization, clinical descriptors, sociodemographic characteristics, and other miscellaneous patient characteristics. The existing data are analyzed to assess what is known about the relative strength of various predictors. Gaps in the available literature and the implications for future research and policy are discussed.
D000368:Aged; D002204:Capitation Fee; D003625:Data Collection; D003710:Demography; D005249:Fees and Charges; D006279:Health Maintenance Organizations / Q000706:statistics & numerical data*; D006305:Health Status Indicators; D006801:Humans; D006278:Medicare / Q000706:statistics & numerical data*; D015233:Models, Statistical; D011336:Probability; D011907:Rate Setting and Review; D012959:Socioeconomic Factors; D014481:United States