Comparison of risk-adjustment methodologies for cesarean delivery rates

OBJECTIVE: To compare the two published methods of cesarean delivery rate risk adjustment to determine which should be recommended as a national standard. METHODS: We used 2 years of Washington State Birth Events Record Data (1997 and 1998) to estimate hospitals' risk-adjusted cesarean delivery rates using two different methods: 1) logistic regression modeling and 2) direct standardization. After exclusions, there were 123,850 births and 67 hospitals. Ranked lists of hospitals were produced by each methodology and compared using the Spearman correlation. We used kappa statistics to compare the top 25% and the bottom 25% of the rankings. RESULTS: The Spearman correlation for the ranked lists was strong (.84, P < .001). The kappas were .67 for the top 25% and .69 for the bottom 25%. By the logistic regression method, 19 hospitals had rates significantly higher than expected and 15 had rates significantly lower than expected. Because the direct standardization method had 57% of hospitals with no births in at least one of the risk strata, we could not determine whether these hospitals were statistical outliers. CONCLUSION: Both methods ranked hospitals similarly. If cesarean delivery rate risk adjustment for all hospitals is desirable, the logistic regression method has the advantage of being able to determine if different rates are significantly above or below expected. However, if comparing only two large hospitals is the goal, direct standardization may be simpler to implement, provided all risk strata have at least one delivery.