Surgical Data Science
Better trained surgeons lead to better patient outcomes. In 2022, under the leadership of Professor Debbi Stanistreet, the Surgical Data Science project sought to identify the key factors that impact on the quality of surgical training in East, Central and Southern Africa.
The team comprised members of RCSI’s Institute of Global Surgery and researchers from Kamuzu University of Health Sciences, Malawi.
The project competed in the concept phase of the Science Foundation Ireland (SFI) SDG Challenge. The Surgical Data Science project addressed UN SDG 3: Good Health and Wellbeing, and built on learnings and partnerships formed through the long-standing RCSI/COSECSA Collaboration Programme.
Objectives
The Surgical Data Science project engaged with trainers, trainees, programme directors, scholarship bodies and training course providers active in the region, and collated and analysed data from COSECSA’s existing training datasets.
The project aimed to uncover the key factors that have the greatest impact on trainees’ progression through training, and that enable trainees to graduate and practice as independent consultant surgeons, and empower training hospitals to improve.
The project findings are currently being written up for publication and are expected to inform further training quality improvement efforts.
The team
- Debbi Stanistreet (RCSI Public Health and Epidemiology)
- Wakisa Mulwafu (Kamuzu University of Health Sciences)
- Eric O’Flynn (RCSI Institute of Global Surgery)
- Payao Mkandawire (Kamuzu University of Health Sciences)
- Lawa Shaban (RCSI Institute of Global Surgery)
- Deirdre Mangaoang (RCSI Institute of Global Surgery)
