American Journal of Epidemiology Vol. 154, No. 9 : 854-864
Copyright © 2001 by The Johns Hopkins University School of Hygiene and Public Health
PRACTICE OF EPIDEMIOLOGY |
Performance of Comorbidity Scores to Control for Confounding in Epidemiologic Studies using Claims Data
1 Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
2 Department of Epidemiology, Harvard School of Public Health, Boston, MA.
3 Pharmacare, Ministry of Health, British Columbia, Canada.
4 Department of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
Comorbidity is an important confounder in epidemiologic studies. The authors compared the predictive performance of comorbidity scores for use in epidemiologic research with administrative databases. Study participants were British Columbia, Canada, residents aged 
65 years who received angiotensin-converting enzyme inhibitors or calcium channel blockers at least once during the observation period. Six scores were computed for all 141,161 participants during the baseline year (1995–1996). Endpoints were death and health care utilization during a 12-month follow-up (1996–1997). Performance was measured by using the c statistic ranging from 0.5 for chance prediction of outcome to 1.0 for perfect prediction. In logistic regression models controlling for age and gender, four scores based on the International Classification of Diseases, Ninth Revision (ICD-9) generally performed better at predicting 1-year mortality (c = 0.771, c = 0.768, c = 0.745, c = 0.745) than medication-based Chronic Disease Score (CDS)-1 and CDS-2 (c = 0.738, c = 0.718). Number of distinct medications used was the best predictor of future physician visits (R2 = 0.121) and expenditures (R2 = 0.128) and a good predictor of mortality (c = 0.745). Combining ICD-9 and medication-based scores improved the c statistics (1.7% and 6.2%, respectively) for predicting mortality. Generalizability of results may be limited to an elderly, predominantly White population with equal access to state-funded health care.
comorbidity; confounding factors (epidemiology); databases; epidemiologic studies; health services
Abbreviations: CDS, Chronic Disease Score; ICD-9, International Classification of Diseases, Ninth Revision; OR, odds ratio; RR, relative risk; SD, standard deviation
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