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

Abstract

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.

Standard Comorbidity Measures Do Not Predict Patient-reported Outcomes 1 Year After Total Hip Arthroplasty

“…Based on an extensive review, Sharabiana et al [23] found that if a comorbidity measure were necessary, the Elixhauser comorbidity score might be the best choice, but they had reservations that the results might differ based on the patient group and the outcome being investigated. However, one must consider that predictive performance of all the comorbidity index scores was not only outcome; the risk-adjustment method also had bearing [17], as was seen in patients with osteoporosis [6,15]. Based on our results, we conclude that if consideration of patient comorbidities is necessary to achieve a particular purpose, then the Elixhauser comorbidity score would seem the best for predicting patient HRQoL, pain, and satisfaction 1 year after THA.…”

Obesity Increases Length of Stay and Direct Medical Costs in Total Hip Arthroplasty

“…In contrast to a previous analysis from our institution [4], we examined BMI as a continuous variable and in eight categories, which avoided loss of information and loss of power. In addition, we identified and adjusted for comorbidities using the Elixhauser algorithm, which is more strongly associated with healthcare use and costs than the Charlson classification [8]. Two studies [14,21] relied on administrative data from the Nationwide Inpatient Sample to address the impact of obesity on some THA outcomes, including costs.…”

A comparison of charlson and elixhauser comorbidity measures to predict colorectal cancer survival using administrative health data

“…13 Of the 70 citations using Elixhauser in cancer research since 2005, only 1 compared Elixhauser with Charlson. 14 Weight loss and obesity are included in the Elixhauser but not the Charlson measure.…”