Adjusting cesarean delivery rates for case mix

Area of Science:

• Obstetrics and Gynecology
• Health Services Research
• Biostatistics

Background:

• Cesarean delivery rates are reported by agencies as measures of hospital performance.
• Adjusting cesarean rates for case mix is crucial for accurate performance evaluation.
• Developing reliable clinical predictors is essential for valid case-mix adjustment.

Purpose of the Study:

• To describe challenges in creating a clinical predictor for cesarean delivery.
• To enable adjustment of reported cesarean rates for case mix.
• To compare the performance of a developed predictor against simpler alternatives.

Main Methods:

• Retrospective analysis of merged hospital and birth certificate data from Washington State (1989-1990).
• Development of variables and statistical models to predict cesarean delivery probability.
• Evaluation using clinical and statistical criteria, comparing a full model with a simpler four-category classification.

Main Results:

• Merged data improved predictor variable development compared to single-source data.
• A four-category classification explained 30% of individual cesarean rate variance.
• A full clinical model explained 37% of variance; hospital rates strongly depend on the proportion of first births.

Conclusions:

• Both simple and complex case-mix measures can adjust reported cesarean rates, depending on data availability.
• Adjustments, while not drastically altering hospital rankings, enhance the validity and acceptability of reported rates.
• Not all variables related to cesarean rates should be included in adjustments for optimal validity.