Comparison of three comorbidity measures for predicting health service use in patients with osteoarthritis

• Published in: Arthritis and rheumatism Vol. 53; no. 5; pp. 666 - 672
• Main Authors: Dominick, Kelli L., Dudley, Tara K., Coffman, Cynthia J., Bosworth, Hayden B.
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc., A Wiley Company 15.10.2005
• Subjects: Comorbidity; Computerized medical record systems; Data Interpretation, Statistical; Databases, Factual - utilization; Epidemiologic Studies; Forecasting; Health Services Needs and Demand - statistics & numerical data; Health Services Needs and Demand - trends; Health Services Needs and Demand - utilization; Humans; Medical Records Systems, Computerized; Models, Economic; North Carolina - epidemiology; Osteoarthritis; Osteoarthritis - epidemiology; Osteoarthritis - pathology; Risk adjustment; North Carolina
• ISSN: 0004-3591; 1529-0131
• DOI: 10.1002/art.21440

Objective To compare the ability of 3 database‐derived comorbidity scores, the Charlson Score, Elixhauser method, and RxRisk‐V, in predicting health service use among individuals with osteoarthritis (OA). Methods The study population comprised 306 patients who were under care for OA in the Veterans Affairs (VA) health care system. Comorbidity scores were calculated using 1 year of data from VA inpatient and outpatient databases (Charlson Score, Elixhauser method), as well as pharmacy data (RxRisk‐V). Model selection was used to identify the best comorbidity index for predicting 3 health service use variables: number of physician visits, number of prescriptions used, and hospitalization probability. Specifically, Akaike's Information Criterion (AIC) was used to determine the best model for each health service outcome variable. Model fit was also evaluated. Results All 3 comorbidity indices were significant predictors of each health service outcome (P < 0.01). However, based on AIC values, models using the RxRisk‐V and Elixhauser indices as predictor variables were better than models using the Charlson Score. The model using the RxRisk‐V index as a predictor was the best for the outcome of prescription medication use, and the model with the Elixhauser index was the best for the outcome of physician visits. Conclusion The Rx‐Risk‐V and Elixhauser are suitable comorbidity measures for examining health services use among patients with OA. Both indices are derived from administrative databases and can efficiently capture comorbidity among large patient populations.