records at the time of this study. However, large, automated national pharmacy databases are increasingly available and accessible, which improves the feasibility and efficiency of pharmacy-based comorbidity measures. There are also several specific characteristics of the RxRisk-V and Elixhauser methods that should be considered, particularly when using these measures among patients with arthritis or other rheumatic diseases. The RxRisk-V includes indicators for analgesic and antiinflammatory medications. This may be an advantage, because medications are a significant component of arthritis-related health care costs (22). However, analgesic and antiinflammatory medications are used for other conditions, and the RxRisk-V does not include specific indicators for either OA or RA. The Elixhauser method includes a relatively comprehensive measure of rheumatic diseases. However, it does not include the diagnosis code for OA. This may be a particular disadvantage when examining outcomes that are significantly affected by OA, including prescription medication use, overall health care costs, and health-related quality of life (22, 23). In addition to their differences in identifying arthritis and other rheumatic conditions, the RxRisk-V and Elixhauser method vary in their treatment of other conditions of importance among this patient population (i.e., depression, obesity, gastric acid disorders) (18-20, 24). The RxRisk-V includes a more comprehensive assessment of gastric acid disorders than the Elixhauser method (which identifies only peptic ulcers and not milder conditions or symptoms). The RxRisk-V also identified a larger number of individuals with depression than the Elixhauser method. However, only the Elixhauser method includes an indicator for obesity. There are some limitations to this study. The data were collected from one VA medical center, and the sample was predominantly male. Additional studies should compare and validate these measures for health service use outcomes among other patient populations. The size of our sample did not allow us to estimate the predictive ability of the original Elixhauser method (with individual disease indicators) for our binary hospitalization outcome. However, this is likely to be a general limitation of the original Elixhauser method. Because of the large number of binary disease indicators in the Elixhauser method, sample sizes must be very large to avoid overfitting models. Studies should continue to examine the validity and utility of a summed Elixhauser score, as was tested in this study. In summary, 3 comorbidity measures, the Charlson Score, RxRisk-V, and Elixhauser method, were found to be significant predictors of health service use among a group of patients with OA. However, the RxRisk-V and Elixhauser measures were somewhat better predictors than the Charlson Score. The RxRisk-V is based on prescription medication use and the Elixhauser method is based on ICD-9-CM codes. Therefore these measures provide different options that may be more feasible for different health care institutions, depending on the type of electronic medical record data available. The RxRisk-V and Elixhauser measures each have strengths, limitations, and other features (i.e., inclusion/omission of some diseases or disease categories) that should be carefully considered in the context of specific studies. However, these results support the validity of both the RxRisk-V and Elixhauser scores for predicting overall health service use