Cesarean delivery risk adjustment for regional interhospital comparisons

The aim of this study was to determine the effect of adjustment for patient population mix on observed, expected, and standardized cesarean delivery rates in regional hospitals.

Multiple logistic regression was applied to a large regional perinatal database comprising 16 hospitals. Variables significantly associated with cesarean delivery were used to calculate cesarean delivery probabilities for individual patients. Probabilities were summed across hospitals to derive expected hospital cesarean delivery rates. A standardized rate for each hospital was then calculated by dividing the observed rate by the expected rate and multiplying by the regional rate.

The regional cesarean delivery rate was 21.9% for 6798 women. Observed hospital rates varied from 17.1% to 39.2%. Twenty-two variables were associated with cesarean delivery. Expected cesarean delivery rates ranged from 18.1% to 26.0%. Among the 5 hospitals with the lowest observed cesarean delivery rates only 2 had rates significantly lower than those of the rest of the region, and only 1 of those 2 rates remained significantly lower after adjustment. One other hospital that had an adjusted rate significantly lower than the crude rate had not appeared statistically different from the rest of the region before standardization. Among the 5 hospitals with the highest cesarean delivery rates, 4 had rates significantly higher than the rest of the region, and 3 of them had significantly higher observed rates than expected rates.

Compared with using observed (crude) cesarean delivery rates, adjustment for differences in patient risk factor mix facilitates more accurate comparison of cesarean delivery rates among hospitals within a region.