Implementation of the Robson classification for caesarean sections in Israel: a 10-year cross-sectional study

Abstract Background In recent decades, caesarean section (CS) rates have dramatically increased; the reasons for this trend are multifactorial and not fully understood. This continuing trend has raised public health concerns regarding higher maternal and perinatal risks, high costs, healthcare efficiency, and inequality of services. We aimed to characterize and evaluate Israel’s CS rate by applying the Robson classification system. Methods This was a national retrospective cross-sectional study. Data from 1,061,786 live births were collected from electronic medical records of women admitted for delivery across all Israeli hospitals between 2014 and 2023. The Robson classification system (also known as the Robson ten group classification system; RTGCS), has been used to monitor, assess, and compare CS rates. Data analysis followed WHO’s RTGCS manual guidelines. Each birth was classified into one of the Robson groups to assess group size, the CS rate within each group, and the contribution to the overall CS rate. Results We found an increasing trend in CS rates, with 19.0% marking the highest rate recorded over the last decade. Group 3 + 4 (multiparous, singleton, cephalic, term pregnancy without previous CS) and 1 (nulliparous, singleton, cephalic, term pregnancy in spontaneous labor) were the most represented (56.1% and 20.7%, respectively). The major contributors to CS included Groups 1, 3 + 4, 5 (multiparous, singleton, cephalic, term pregnancy with a previous CS), 8 (all multiple pregnancies), and 10 (singleton, cephalic, pre-term pregnancy). Conclusions Using a population-based dataset that spanned ten years, this study identified subgroups in need of targeted interventions and offered insight into CS rate dynamics. The study underscores the RTGCS’s potential to optimize maternity outcomes, shape policy, and inform healthcare practices, making a meaningful contribution to the field. The findings highlight the importance of integrating RTGCS into routine data collection and improving obstetric data quality.