Choudhry, O. orcid.org/0000-0003-4434-3550 Global Variations in Minimally Invasive Surgery Training Pathways - A Narrative Review. In: ALSGBI 2025 Annual Scientific Meeting, 03-04 Nov 2025, London, UK. (Unpublished)
Abstract
Minimally invasive surgery (MIS) offers smaller incisions, reduced blood loss, less scarring, quicker recovery and shorter hospital stays, yet 5 billion people lack access to the same quality of surgeons as those in high-income countries, with an unmet need of approximately 143,000,000 surgical cases, and 11% of deaths in LMICs treatable and 80% preventable. This narrative review examines global variations in laparoscopic and robotic surgical training pathways, identifies disparities in training infrastructure and certification requirements, and proposes evidence-based recommendations for optimising MIS education worldwide. Marked disparities were found: the United States mandates 850 total operative procedures over five years including 75 complex and 60 basic laparoscopic cases for chief residents, with Fundamentals of Laparoscopic Surgery certification compulsory since 2010 and 87% pass rates, whereas the COSECSA region reports only 0.9% of 68,659 surgical cases as laparoscopic, only 16.5% of Mexican public health system procedures are performed laparoscopically, and the Baltic states completely lack robotic systems, affecting 6 million people. Robotic surgery remains unstandardised, with costs of $0.5M to $2.5M per robot and around $200,000 per year, use in 19% of all UK surgeries in 2023 and 524% uptake between 2016 and 2023, but no formal ACGME robotic requirements despite 78.6% of programme directors supporting mandatory console training. The review concludes that the current training landscape perpetuates a two-tier global system, and recommends standardised competency-based certification with tiered simulation requirements and sustainable funding, a minimum of 20 console cases based on learning curve data, telecoaching as a temporary measure, and international credentialing reciprocity alongside retention strategies.
Metadata
| Item Type: | Conference or Workshop Item |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | This poster, which was originally presented at the ALSGBI 2025 Annual Scientific Meeting, is reproduced here with the permission of the author. |
| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
| Date Deposited: | 20 Aug 2026 09:40 |
| Last Modified: | 20 Aug 2026 09:44 |
| Status: | Unpublished |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:243939 |

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