Authors
Nader Francis, Taner Shakir, Esther McLarty, Fares Haddad, Adam Farquharson, Andrew Garnham, Somiah Siddiq, Aidan Bannon, Justin Collins, Nuha Yassin, RCS England RaDaR Delphi Consensus Working Group for Robotic Residents’ Training Curriculum
Published in
Journal of robotic surgery. Volume 20. Issue 1. Aug 29, 2026. Epub Aug 29, 2026.
Abstract
Robotic-assisted surgery is now established across multiple surgical specialties in the United Kingdom, yet training for surgical residents remains variable, resource-dependent, and insufficiently standardised at national level. This study sought multispecialty expert consensus on the essential components of a national robotic surgery training curriculum for UK surgical residents. A four-round modified Delphi study was conducted between September and December 2025 under the RaDaR network of the Royal College of Surgeons of England. Round 1 used open-ended questionnaires with independent dual-coder thematic analysis; Round 2 was a hybrid face-to-face and online meeting with live anonymous electronic voting; Rounds 3 and 4 were online questionnaires addressing statements not yet reaching the pre-defined consensus threshold of 70% agreement or greater. The panel comprised consultant surgeons, surgical trainees, curriculum and training authorities, and industry representatives with deliberately bounded, non-clinical input. 25 participants completed the final round. Of 26 statements, 22 (84%) reached consensus. A three-tier framework of device, basic skills, and procedural training was endorsed, with device training introduced during Phase 1 (76%) and basic skills and procedural training introduced after Phase 1 (96% and 88% respectively). Competency assessment integrated within the Annual Review of Competence Progression was supported (84%), alongside multi-source funding; trainee self-funding was not endorsed. This consensus offers a pragmatic foundation for standardising robotic surgery training for UK residents, contingent on coordinated investment in platform access, simulation infrastructure, and faculty development.
PMID:
42667500
Bibliographic data and abstract were imported from PubMed on 30 Aug 2026.
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