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

Published: October 1, 2004
Category: Papers
Authors: Callahan CM, Hope C, Katon W, Kroenke K, Perkins AJ, Unutzer J, Williams JW Jr
Country: United States
Language: null
Type: Care Management
Setting: Academic

J Clin Epidemiol 57:1040-1048.

Indiana University Center for Aging Research, Indianapolis, IN, USA

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.

PMID: 15528055

Mortality Prediction,Cost Burden Evaluation,Co-morbidity,Resource Utilization,United States,African Americans,Aged,Ambulatory Care/economics,Cause of Death,Chronic Disease,Gender,Polypharmacy,Predictive Value of Tests,Prognosis,Prospective Studies

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