Observation of a quality improvement initiative to contextually adapt and use Robson classification in real time to collect data around CS delivery and to develop strategies to reduce CS rate

Abstract

The rising trend in caesarean section (CS) rate is a global concern and, in this hospital too, it rose from 21.5% in 2010 to 32.6% in 2018. The team followed the point of care quality improvement methodology and conducted a series of Plan–Do–Study–Act cycles to contextually modify and adapt Robson classification into the existing workflow to improve the process of documentation and data collection for CS in the first 6 months (January 2019–June 2019) and then to use these data to develop strategies to reduce CS rate below 30% in the next 18 months.To evaluate the impact of developed strategies, the team plotted the data on Statistical Process Control (XmR) chart. The baseline mean CS rate was 32.6%. The team observed a shift in the CS rate data twice, between April 2020 and December 2020 and between August 2021 and February 2021 with the mean 27.8% and 28.9%, respectively. October 2021 onwards, the team also observed a sustained reduction in the CS rate in women undergoing CS who had one previous CS. The mean CS rate reduced from 94% to 86%.The reductions in the CS rate were not sustained and followed by an increase again. The project highlighted the complexity of the factors related to CS delivery and the multidimensional barriers of sustaining the reduction in the CS rate. This is a well-sustained ongoing QI intervention and the team is further working on identifying the underlying factors to improve the efficacy of the interventions to sustain the reduction in the CS rate.This hospital represents the general population of North India seeking care in public healthcare facilities. Therefore, despite being a single-centre study, the population served and interpretations drawn from this study are generalisable to other hospitals with similar settings.