Hostname: page-component-f554764f5-sl7kg Total loading time: 0 Render date: 2025-04-20T18:35:05.577Z Has data issue: false hasContentIssue false
  • English
  • Français

369 Precision education and generative AI in surgery utilization study: A framework for global surgical education

Published online by Cambridge University Press:  11 April 2025

Timothy Kintu ,
Mike Nsubuga ,
Allan Bakesiga ,
Helen Please ,
Kelsey Stewart  and
Sergio M. Navarro
Timothy Kintu
Affiliation:
African Centre of Excellence in Bioinformatics and Data Intensive Sciences; The Infectious Diseases Institute, Makerere University, P. O. Box 22418, Kampala, Uganda
Mike Nsubuga
Affiliation:
The Infectious Diseases Institute, Makerere University, P. O. Box 22418, Kampala, Uganda Faculty of Health Sciences, University of Bristol, Bristol, BS40 5DU, UK The African Center of Excellence in Bioinformatics and Data Intensive Sciences, Kampala, Uganda
Allan Bakesiga
Affiliation:
Makerere University, Department of Surgery, Kampala, Uganda Duke University, Department of Surgery, Durham, NC
Helen Please
Affiliation:
Oxford University Hospitals NHS Foundation Trust, Oxford, UK Harris Manchester College, University of Oxford, Oxford, UK
Kelsey Stewart
Affiliation:
Mayo Clinic, Department of Obstetrics and Gynecology, Rochester, MN, US
Sergio M. Navarro
Affiliation:
Mayo Clinic, Department of Surgery, Rochester, MN, US University of Minnesota, Department of Surgery, Minneapolis, MN, US
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Objectives/Goals: Global surgical education is largely driven by high-income countries (HICs), with curricula not tailored to the needs of low- and middle-income countries (LMICs). This study assessed country-specific needs for global surgical curricula and used generative AI to develop tailored curricula. Methods/Study Population: A curriculum framework was developed using expert opinion. Using a focused needs assessment survey, we evaluated international medical students’ and trainees’ needs for structured global surgery curricula, covering research, education, data and develop tailored curriculum templates for each country, ensuring alignment with the distinct needs of respective LMIC and HIC respondents. The AI-generated curricula were then compared across countries to identify variations in content and focus areas. Results/Anticipated Results: A total of 145 respondents from 18 countries and 6 continents participated, with 94 from LMICs and 51 from HICs. Four countries [Uganda (n = 31), Nigeria (n = 34), the USA (n = 23), and the UK (n = 23)] had more than 10 respondents, with the creation of a country specific global surgery curriculum. Curricula developed by HIC trainees focused on access to resources and infrastructure, future directions of global surgical research, and the role of medical students and early career development with a decreased focus on the history of global surgery. LMIC country-based curriculum focused on introducing the concepts of global surgery, quantifying the burden and epidemiology of surgical disease and had a greater emphasis on case studies and use cases, with decreased focus on resources and collaboration. Discussion/Significance of Impact: The research introduces a “precision education” approach that could help close the surgical education access gap globally. Further pilot and qualitative studies are necessary to validate the feasibility of AI-generated needs-based curricula.

Type
Informatics, AI and Data Science
Information
Journal of Clinical and Translational Science , Volume 9 , Issue s1 , April 2025 , pp. 114
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s), 2025. The Association for Clinical and Translational Science