The Importance of Risk Adjustment in Reporting Total Joint Arthroplasty Outcomes.

BACKGROUND

This study describes and tests a risk adjustment model developed for the California Joint Replacement Registry to report predictors of complication rates.

METHODS

Complication 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.

RESULTS

Age 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.

CONCLUSION

Adequate risk adjustment is a key element in objective comparison of surgeons, hospitals, and devices using total joint arthroplasty registry data.