Common comorbidity scales were similar in their ability to predict health care costs and mortality

Abstract

Objective To compare the ability of commonly used measures of medical comorbidity (ambulatory care groups [ACGs], Charlson comorbidity index, chronic disease score, number of prescribed medications, and number of chronic diseases) to predict mortality and health care costs over 1 year. Study Design and Setting A prospective cohort study of community-dwelling older adults ( n = 3,496) attending a large primary care practice. Results For predicting health care charges, the number of medications had the highest predictive validity ( R 2 = 13.6%) after adjusting for demographics. ACGs ( R 2 = 16.4%) and the number of medications (15.0%) had the highest predictive validity for predicting ambulatory visits. ACGs and the Charlson comorbidity index (area under the receiver operator characteristic [ROC] curve = 0.695–0.767) performed better than medication-based measures (area under the ROC curve = 0.662–0.679) for predicting mortality. There is relatively little difference, however, in the predictive validity across these scales. Conclusion In an outpatient setting, a simple count of medications may be the most efficient comorbidity measure for predicting utilization and health-care charges over the ensuing year. In contrast, diagnosis-based measures have greater predictive validity for 1-year mortality. Current comorbidity measures, however, have only poor to moderate predictive validity for costs or mortality over 1 year.