Implementation of Robson classification for caesarean section using health insurance claims: the experience of Indonesia

Abstract

AbstractRobson classification has been recommended by the World Health Organization (WHO) as a monitoring tool for caesarean section (CS), however, it has not been implemented in Indonesia. In this study, we hypothesize that the National Health Insurance (NHI) claims data can be used to classify pregnant women into several obstetric groups. This study aims to examine the use of NHI claims database for analyzing CS according to the WHO manual for Robson classification. This study is a cross-sectional analysis using delivery claims from NHI sample set data from 2017 to 2018. We categorized the International Classification of Diseases (ICD) 10 codes in the claims data according to the Robson classification system using the following variables: multiple pregnancy, fetal presentation, previous obstetric record, previous CS record, gestational age, and onset of labor. Data was analyzed using IBM SPSS Statistics. A total of 31,375 deliveries were included in the analysis. Overall, mean age of mothers was 29.2±5.9 years. The CS rate in this population was 37.0% in 2017 and 38.7% in 2018. Highest CS rate was found in nulliparous (group 2: 26.6%) and multiparous women (group 4: 24.8%) if labour induced or had prelabour CS, followed by multiparous women with previous uterine scar (group 5: 22.5%). We found an alarmingly high rate of CS among Indonesian women. Implementation of Robson classification in the National Health Insurance claims data is feasible and should be considered by the policy makers as an audit tool to identify the groups that contributes the most to the CS rate.