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

• Published in: Journal of clinical epidemiology Vol. 57; no. 10; pp. 1040 - 1048
• Main Authors: Perkins, Anthony J., Kroenke, Kurt, Unützer, Jürgen, Katon, Wayne, Williams, John W., Hope, Carol, Callahan, Christopher M.
• Format: Journal Article
• Language: English
• Published: New York, NY Elsevier Inc 01.10.2004; Elsevier; Elsevier Limited
• Subjects: African Americans; Aged; Ambulatory care; Ambulatory Care - economics; Analysis. Health state; Biological and medical sciences; Cause of Death; Chronic Disease; Chronic illnesses; Comorbidity; Emergency medical services; Epidemiology; Female; General aspects; Health care; Health Care Costs; Health Status Indicators; Humans; Male; Medical sciences; Models, Statistical; Mortality; Older people; Polypharmacy; Predictive Value of Tests; Prognosis; Prospective Studies; Public health. Hygiene; Public health. Hygiene-occupational medicine; Studies; Utilization; Utilization; Comorbidity; Chronic disease; Mortality; Human; Costs; Evaluation scale; Epidemiology; Care; Concomitant disease; Chronic; Health economy; Economic aspect; Predictive factor; Public health
• ISSN: 0895-4356; 1878-5921
• DOI: 10.1016/j.jclinepi.2004.03.002

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. A prospective cohort study of community-dwelling older adults ( n = 3,496) attending a large primary care practice. 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. 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.