Risk-Adjustment of Cesarean Delivery Rates: A Practical Method for Use in Quality Improvement

Abstract

Risk-adjustment of cesarean birthrates has been hampered by inadequacies in the existing secondary data sources or by the need for extensive chart review. This study presents an efficient risk-adjustment model for cesarean birth, based on easily retrievable ICD-9 codes and clinical risk factors least influenced by physician practice style. Data are presented for mothers undergoing 7322 deliveries from 1997-1998 at a large academic medical center with a cesarean birth rate of 15.9%. Multiple logistic regression was used to predict the likelihood of cesarean delivery controlled for maternal age, 10 risk factors identified through ICD-9 coding, and 3 additional clinical variables (nulliparity, birth weight, and gestational age) derived from a perinatal (birth certificate) database. All risk factors were significant predictors of cesarean birth, producing an area under the receiver-operating characteristic curve of 0.86 and a 60-fold increase in cesarean delivery from highest to lowest deciles of predicted risk. This methodology can be used widely for quality improvement without the need for extensive chart review.