Expenditure models for prospective risk adjustment: choosing the measure appropriate for the problem.

Abstract

Risk adjustment models for health care expenditures typically have been disappointing in their predictive ability for individual enrollees. However, practical applications of risk adjustment often involve groups, not individuals. Therefore, model performance on groups of enrollees may be more meaningful than performance on individuals. The authors propose a new measure of model fit, the sorted-group R2, which measures the correlation between predicted and actual cost averages for groups of enrollees sorted by risk prior to grouping. The authors use this tool to evaluate four models with different explanatory variables and functional complexities. Results indicate that even a model which performs poorly for individual subscriber units and for unselected groups can indeed distinguish between groups of subscriber units where there has been moderate risk selection.