OBJECTIVES:  We used the composite quality index (CompQualTM) to examine the association between venous thromboembolism (VTE) events and hospital quality for patients who underwent major orthopedic surgery. METHODS: Using the empirical Bayes approach to combine mortality rates with information on hospital volume at each hospital, we created an index to weight observed mortality according to how reliable it is estimated, with remaining weight placed on hospital volume (CompQualTM scoring algorithm). Then, using a national database, all patients who underwent major orthopedic surgery were identified.   Rates for patients who had a VTE event during their initial hospitalization were calculated. By using the algorithm, every provider in the Medicare dataset was ranked according to their quality. Multivariate regression was used to see the effect of quality on VTE event rates. RESULTS: We obtained a sample that included 2,745 patients in the VTE group. After controlling for patients’ demographic and clinical factors, VTE events in low quality hospitals were almost 2.5 times higher than VTE events in high quality hospitals (p=0.000). We also compared the ranking with only volume and only for hospitals. Our combined measure to rank the hospital was more effective and explained more variation than the individual measures (pseudo R-square: 0.46 for composite score, 0.15 for volume only, 0.09 for mortality only). CONCLUSIONS: Using national Medicare data for patients with VTE, we found that a simple composite measure was a strong predictor of subsequent performance for operations. In this regard, it was more effective than individual measures. Such measures would be useful to help patients and payers identify low quality hospitals for major surgery. Any policy implementation that would decrease the variation in hospital quality would have a direct effect on the rates of VTE events.