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

J Clin Epidemiol. 2004 Oct;57(10):1040-8. doi: 10.1016/j.jclinepi.2004.03.002.

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.

Publication types

  • Comparative Study

MeSH terms

  • African Americans
  • Aged
  • Ambulatory Care / economics
  • Cause of Death
  • Chronic Disease
  • Comorbidity*
  • Female
  • Health Care Costs*
  • Health Status Indicators*
  • Humans
  • Male
  • Models, Statistical*
  • Polypharmacy
  • Predictive Value of Tests
  • Prognosis
  • Prospective Studies