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Evaluating health care programs by combining cost with quality of life measures: a case study comparing capitation
Richard Grieve1, Jasjeet S Sekhon, Teh-Wei Hu
1Department of Public Health and Policy, London School of Hygiene and Tropical Medicine, Keppel St., London WC1E7HT, UK. Richard.Grieve@lshtm.ac.ok
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.
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