Flaws in capitation created a ``Case Mix Adjustment'' cottage industry. Capitation systems start with payments deemed adequate, but not excessive, for a population. The population is a mix of epidemiologically significant characteristics that influence costs. Even if capitation rates are correct, on average, some providers are overpaid, and others underpaid, despite receiving identical per patient capitation payments. Payment-cost disparities arise for two reasons: Main factor effects when providers' portfolios differ from the population on epidemiologically relevant characteristics; and Increased PLRE variability, due to small portfolios.
Correcting capitation rates for main factor effects, through case mix adjustments, is simple but inadequate, because small providers are less efficient insurers than . Case mix adjusted capitation rates cannot compensate providers because the providers need higher Portfolio Risk Adjusted Premiums to compensate for their inefficient insurance operations. Case mix adjustments, while necessary, are insufficient corrections for the providers' risks.
Only providers who believe their costs are higher than appropriate, will request case mix adjustments, the ``Lake Wobegon'' effect: ``All Lake Wobegon providers believe their costs are above average.'' No Lake Wobegon providers ever requests reduced case mix payments. Provider initiated case mix adjustments result in inefficient increases in aggregate capitation payments, even if the original capitation payments were correct. Some successful case mix adjustments correct for inefficient insurance operations, not epidemiological differences in expected Claims Costs, so these increased capitation payments are inefficient. Even when capitation payments are perfect, providers are either underpaid, or underpaid, for their future costs, because provider's costs, including profit margins, are almost never equal to capitation payments, because the most significant sources of providers' Claims Cost variations are not corrected by case mix adjustments.
Worse still, provider's portfolios are almost never random selections from the population for which capitation rates were calculated. Patient-provider matching is almost always non-random due to geography, transportation routes, age, gender, current and prior health status, and socioeconomic factors. ``Park Avenue'' providers avoid poor patients and rich patients avoid providers in poor areas. Real insurers are statutorily forbidden from ``Red Lining'' neighborhoods, in marketing and underwriting activities, while risk assuming health care providers freely ``Red Line'' neighborhoods as they select service locations and set operating hours, and discouraging undesirable patients in pre-appointment screening. Provider portfolios are almost never random, increasing barriers to care for some patients.