The medicaid R-x model - Pharmacy-based risk adjustment for public programs

BACKGROUND. Risk adjustment models typically use diagnoses from claims or e ncounter records to assess illness severity. However, concerns about the av ailability and reliability of diagnostic data raise the potential for alter native methods of risk adjustment. Here, we explore the use of pharmacy dat a as an alternative or complement to diagnostic data in risk adjustment. OBJECTIVES. To develop and test a pharmacy-based risk adjustment model for SSI and TANF Medicaid populations. RESEARCH DESIGN. Pharmacological review combined with empirical evaluation. We developed the Medicaid R-x model, a system that classifies a subset of the National Drug Codes into categories that can be used for risk-assessmen t and risk-adjusted payment. SUBJECTS. Subjects consisted of 362,370 persons with disability and 1.5 mil lion AFDC and TANF beneficiaries in California, Colorado, Georgia, and Tenn essee during 1990-1999. MEASURES. We compare pharmacy and diagnostic classification for three chron ic diseases. We also compare R-2 statistics and use simulated health plans to evaluate the performance of alternative models. RESULTS. Pharmacy and diagnostic classification vary in their ability to id entify specific chronic disease. Using simulated plans, diagnostic models a re better at predicting expenditures than are pharmacy-based models for dis abled Medicaid beneficiaries, although the models perform similarly for TAN F Medicaid beneficiaries. Models that combine diagnostic and pharmacy data have superior overall performance. CONCLUSIONS. The performance of risk adjustment models using a combination of pharmacy and diagnostic data are superior to that of models using either data source alone, particularly among TANF beneficiaries. Concerns regardi ng variations in prescribing patterns and the incentives that may follow fr om linking payment to pharmacy use warrant further research.