Managed Care Contracting and Medical Care for the Uninsured: Untangling Selection from Production

Capitated payment systems used by managed care plans potentially reduce the financial earnings that providers use to cross-subsidize care for the uninsured. Providers that value uninsured care highly, however, may improve production efficiency in response to capitation and thereby maintain or expand uninsured care. Measuring the effect of capitation is complicated by the endogenous selection and censoring processes that determine a provider's involvement in capitated payment systems. This study compares three alternative methods for modeling the effect of capitation—a single-equation generalized estimating equations (GEE) model, a two-stage tobit model, and a discrete factor model using full-information maximum likelihood estimation. Models are estimated using panel data on all U.S. federally-funded community health centers operating during 1992 through 1996 (3185 center-years). Single-equation estimates appear positively biased due to capitation selection and censoring. Estimates from two-stage and discrete factor models show no evidence that capitation adversely affects uninsured care after controlling for this bias. Discrete factor estimates are substantially more precise than two-stage estimates, and indicate that uninsured care actually increases modestly in response to capitation. Discrete factor models, though computationally intensive, offer the advantages of consistency and precision over other econometric models for studies involving censored endogenous variables and selection bias.