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Implementing the Robson Classification for caesarean sections in Pakistan: experience, challenges, and lessons
Lubna Hassan1, Ana Pilar Betran2, Lauren Woodbury1
1Women's Health Intervention and Development Initiative, Islamabad, Pakistan.
Insights
Pakistan successfully integrated the Robson Classification System into its healthcare system to improve caesarean section rates and maternal health. This initiative established master trainers and a data collection app, paving the way for national scale-up.
Area of Science:
- Maternal and Newborn Health
- Healthcare System Strengthening
- Obstetrics and Gynecology
Background:
- The Robson Classification System is crucial for optimizing caesarean section rates and enhancing maternal and newborn health quality improvement.
- Institutionalizing evidence-based practices like the Robson Classification is vital for healthcare system advancement.
Purpose of the Study:
- To detail the strategy and lessons learned from integrating the Robson Classification System into Pakistan's national health system.
- To establish a sustainable framework for optimizing caesarean section practices and improving maternal care outcomes.
Main Methods:
- Developed a comprehensive training package focused on building capacity among senior clinicians to become master trainers.
- Created a mobile application to facilitate efficient data collection and analysis for the Robson Classification.
- Conducted training workshops in 2020 across selected public tertiary teaching hospitals, followed by a year of comprehensive birth data collection.
Main Results:
- The Robson Classification System has been successfully embedded in 57% of Pakistan's public, tertiary, teaching hospitals.
- A network of master trainers is established in every province, supported by a robust dataset.
- The initiative demonstrates readiness for national scale-up, with established infrastructure and trained personnel.
Conclusions:
- The integration of the Robson Classification System in Pakistan is a significant step towards optimizing caesarean section rates and improving maternal health.
- Sustained government commitment, continuous training, and robust data quality assurance are essential for long-term success.
- The initiative provides a scalable model for other low- and middle-income countries seeking to improve obstetric care quality.
Abstract:
The Robson Classification System is recognised as a first step for optimising the use of caesarean section and as a strategy for continuous quality improvement in maternal and newborn health. This Viewpoint provides a detailed account of the strategy adopted and lessons learned from a collaborative initiative to institutionalise the Robson Classification into Pakistan's health system. We developed a training package which emphasised capacity building of senior clinicians to act as master trainers. We also developed a mobile application for data collection and analysis. Training workshops took place in 2020 in a selection of public sector, tertiary-level, teaching hospitals from across the country and data was collected on all births in participating hospitals' obstetric units for a full year. Pakistan is poised for scale-up with the Robson Classification embedded in 57% of Pakistan's public, tertiary, teaching hospitals. A core group of master trainers is positioned in every province, and a robust dataset is available. However, integration into any health system cannot be thought of as a finite project. It requires government commitment, training and an ongoing process with built-in data quality assurance and feedback to clinicians.
