Article ID Journal Published Year Pages File Type
4059978 The Journal of Arthroplasty 2016 6 Pages PDF
Abstract

BackgroundThis study describes and tests a risk adjustment model developed for the California Joint Replacement Registry to report predictors of complication rates.MethodsComplication rates were analyzed for 9960 patients enrolled in the California Joint Replacement Registry at 22 medical centers. Multivariable logistic risk models were created to analyze risks of postoperative complications.ResultsAge and American Society of Anesthesiologists class were the strongest predictors of complication rates (P < .0001). Congestive heart failure and peripheral vascular disease were also statistically significant predictors of complications. Three hospitals were found to have statistically significantly worse than expected complication rates, and one was found to have a better than expected complication rate after case mix risk adjustment.ConclusionAdequate risk adjustment is a key element in objective comparison of surgeons, hospitals, and devices using total joint arthroplasty registry data.

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