A method for risk-adjusting employer contributions to competing health insurance plans.

Biased selection can threaten the viability of multiple choice health systems unless payments to particular plans are adjusted to offset risk differences among employees. We report the results of a study designed to predict medical care utilization and expenditures for groups of fee-for-service plan (FFS) and health maintenance organization (HMO) enrollees, using characteristics commonly available in the personnel files of large employers. Simulation analyses indicate that the six-equation, maximum likelihood model predicts well for groups of 1,000 or more. Additional data are required to reduce prediction errors for smaller groups. This new methodology potentially allows risk-rating of employer contributions to competing health plans, based on the expected utilization of the individuals choosing each plan.