health care systems. The main advantages to this approach are ease of data acquisition, cost and time efficiency, and lack of reliance on accurate reporting by patients. There are also limitations, such as diagnosis coding errors and omissions (3, 4). However, administrative databases are an important source of data that can efficiently capture comorbidity among large patient populations. Three validated, database-derived comorbidity indices are the Charlson Score, Elixhauser method, and RxRisk-V. The overall goal of these measures is to identify patients' significant chronic illnesses as comprehensively as possible, through the use of electronic medical records, and to create a valid method of coding and scoring that captures the burden of illness. However, there are some significant differences in these measures, including the method of development, type of data used, and the number and type of diseases included. The Charlson Score has been the most widely used comorbidity index. Originally developed for use with medical record abstraction (5), this score has also been adapted for administrative databases that use the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) (6). The Charlson Score has been shown to predict mortality and hospitalization outcomes in a variety of patient populations (6-8). The Elixhauser method also uses ICD-9-CM codes and has been shown to predict mortality and hospitalization outcomes (9, 10). In contrast to the Charlson Score, the original Elixhauser method involves retaining individual binary indicators for each disease category (rather than creating a summary score by adding indicators for all diseases). Two recent studies suggest that the Elixhauser method is a superior predictor of mortality compared with the Charlson Score (10, 11). The RxRisk-V is a pharmacy-based comorbidity index that is a revision and expansion of the Chronic Disease Score (12). Studies have shown that the RxRisk-V is a significant predictor of total health care costs (13, 14). To date, these comorbidity measures have not been validated specifically among groups of patients with arthritis or other rheumatic conditions, and studies have not compared these 3 measures in the same sample. Two of these indices (the Charlson Score and the Elixhauser method) were developed on the basis of predicting mortality and/or hospitalization-related outcomes (5, 6, 9, 15), but their ability to predict other health service outcomes has not been well documented. This is a limitation for research in the rheumatic diseases, where health service outcomes such as physician visits and medication use may be of greater relevance than mortality. The purpose of this study was to compare the ability of the Charlson Score, Elixhauser method, and RxRisk-V to predict overall health service use among individuals with OA. Specifically, we examined the ability of these comorbidity indices to predict physician visits, hospitalization, and prescription drug use. Participants were veterans who were under care for OA at the Veterans Affairs (VA) Medical Center in Durham, NC. We selected a random 10% sample of patients (n = 306) who were identified by an ICD-9-CM code for OA (715) between October 1998 and September 1999, using national VA inpatient and outpatient databases. All comorbidity scores were calculated using 1 fiscal year of data (October 1998–September 1999). National VA inpatient and outpatient clinic files were used to create the 2