Surgical Data Science

Better trained surgeons lead to better patient outcomes. Under the leadership of Professor Debbi Stanistreet, the Surgical Data Science project seeks to identify the key factors that impact on the quality of surgical training in East, Central and Southern Africa.

The team is made up of members of RCSI’s Institute of Global Surgery and researchers from Kamuzu University of Health Sciences, Malawi.

Objectives

The project is competing in the Science Foundation Ireland (SFI) SDG Challenge. The Surgical Data Science project addresses UN SDG 3: Good Health and Wellbeing, and builds on learnings and partnerships formed through the long-standing RCSI/COSECSA Collaboration Programme.

The Surgical Data Science project is engaging with trainers, trainees, programme directors, scholarship bodies and training course providers active in the region, and collating and analysing data from COSECSA’s existing training datasets.

The project aims 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 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)

Surgical Data Science infographic