Pharmacy costs groups - A risk-adjuster for capitation payments based on the use of prescribed drugs

BACKGROUND. Adequate risk-adjustment is critical to the success of market-o riented health care reforms in many countries. A common element of these re forms is that consumers may choose among competing health insurers, which a re largely financed through premium-replacing capitation payments mostly ba sed on demographic variables. These very crude health indicators do not ref lect expected costs accurately. OBJECTIVE. This study examines whether the demographic capitation model can be improved by incorporating information on the presence of chronic condit ions deduced from the use of prescribed drugs. The revised Chronic Disease Score was used to incorporate this information in the model. METHODS. A panel data set comprising annual costs and information on prescr ibed drugs for 3 successive years from Dutch sickness fund members of all a ges, is used for the empirical analyses (N = 55,907). The predictive perfor mance of the demographic model is compared with that of a chronic condition s and a Pharmacy Costs Groups (PCG) model, which is a demographic model ext ended with information on clustered chronic conditions. RESULTS. The predictive accuracy of the demographic model substantially imp roved when the model was extended with dummy variables for chronic conditio ns. The 23 chronic conditions could be clustered into six PCGs without affe cting the predictive accuracy. Based on these PCGs 17% of the members were bad risks with a mean predictable loss that exceeds the overall average exp enditures. CONCLUSIONS. The use of information on chronic conditions derived from clai ms for prescribed drugs is a promising option for improving the system of r isk-adjusted capitation payments.