Identifying strategies to reduce cesarean section rates by using Robson ten-group classification

Abstract

Objective

To assess the cesarean section (CS) rates using Robson ten-group classification system (RTGCS) and the interventions combined with RTGCS which may reduce the CS rates.

Methods

A total of 100,326 deliveries at Zekai Tahir Burak Research and Training Hospital in Ankara, Turkey between 2012 and 2018 were included in this study. Interventions including free mobilization of pregnant women, CS decision with the signature of three obstetricians, re-evaluate the CS decision, strictly obeying the failed induction algorithm to reduce the CS rates were started to be applied in 2017. The CS rates between 2012 and 2017 and in 2017 were compared to evaluate the effects of the interventions on CS rate regarding the Robson groups.

Results

The overall CS rates in between 2012 and 2017 significantly reduced from 37,703/84,279 (44.7%) to 6738/16,047 (42.0%) in 2017, p < .001. Cephalopelvic disproportion and suspected macrosomia rates reduced from 4992/37,703 (13.3%) to 683/6738 (10.0%), p < .001 and from 668/37,703 (1.8%) to 96/6738 (1.4%), p = .030, respectively.

Conclusions

To the best of our knowledge, this study is the first that gives the birth data from Turkey using RTGCS and showed that some interventions combined with RTGCS to reduce CS rates should be properly used.

Keywords:

• Cesarean section
• Robson classification
• ten-group classification system (TGCS)
• tertiary level hospital
• Turkey
• vaginal delivery

Disclosure statement

No potential conflict of interest was reported by the authors.