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

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Perkins, AJ; Kroenke, K; Unützer, J; Katon, W; Williams, JW; Hope, C; Callahan, CM

Published Date

  • October 2004

Published In

Volume / Issue

  • 57 / 10

Start / End Page

  • 1040 - 1048

PubMed ID

  • 15528055

Pubmed Central ID

  • 15528055

International Standard Serial Number (ISSN)

  • 0895-4356

Digital Object Identifier (DOI)

  • 10.1016/j.jclinepi.2004.03.002

Language

  • eng

Conference Location

  • United States