Risk adjustment alternatives in paying for behavioral health care under Medicaid

Objective. To compare the performance of various risk adjustment models in behavioral health applications such as setting mental health and substance abuse (MH/SA) capitation payments or overall capitation payments for popula tions including MH/SA users. Data Sources/Study Design. The 1991-93 administrative data from the Michiga n Medicaid program were used. We compared mean absolute prediction error fo r several risk adjustment models and simulated the profits and losses that behavioral health care carve outs and integrated health plans would experie nce under risk adjustment if they enrolled beneficiaries with a history of MH/SA problems. Models included basic demographic adjustment, Adjusted Diag nostic Groups, Hierarchical Condition Categories, and specifications design ed for behavioral health. Principal Findings. Differences in predictive ability among risk adjustment models were small and generally insignificant. Specifications based on rel atively few MH/SA diagnostic categories did as well as or better than model s controlling for additional variables such as medical diagnoses at predict ing MH/SA expenditures among adults. Simulation analyses revealed that amon g both adults and minors considerable scope remained for behavioral health care carve outs to make profits or losses after risk adjustment based on di fferential enrollment of severely ill patients. Similarly, integrated healt h plans have strong financial incentives to avoid MH/SA users even after ad justment. Conclusions. Current risk adjustment methodologies do not eliminate the fin ancial incentives fur integrated health plans and behavioral health care ca rve-out plans to avoid high-utilizing patients with psychiatric disorders.