Evaluating health care programs by combining cost with quality of life measures: a case study comparing capitation and fee for service.

OBJECTIVE To demonstrate cost-effectiveness analysis (CEA) for evaluating different reimbursement models. DATA SOURCES/STUDY SETTING The CEA used an observational study comparing fee for service (FFS) versus capitation for Medicaid cases with severe mental illness (n=522). Under capitation, services were provided either directly (direct capitation [DC]) by not-for-profit community mental health centers (CMHC), or in a joint venture between CMHCs and a for-profit managed behavioral health organization (MBHO). STUDY DESIGN A nonparametric matching method (genetic matching) was used to identify those cases that minimized baseline differences across the groups. Quality-adjusted life years (QALYs) were reported for each group. Incremental QALYs were valued at different thresholds for a QALY gained, and combined with cost estimates to plot cost-effectiveness acceptability curves. PRINCIPAL FINDINGS QALYs were similar across reimbursement models. Compared with FFS, the MBHO model had incremental costs of -$1,991 and the probability that this model was cost-effective exceeded 0.90. The DC model had incremental costs of $4,694; the probability that this model was cost-effective compared with FFS was <0.10. CONCLUSIONS A capitation model with a for-profit element was more cost-effective for Medicaid patients with severe mental illness than not-for-profit capitation or FFS models.