Utilising an Accelerated Delphi Process to Develop Guidance and Protocols for Telepresence Applications in Remote Robotic Surgery Training

Justin Collins(University College London), Ahmed Ghazi(University of Rochester Medical Center), Danail Stoyanov(University College London), Andrew J. Hung(Keck Hospital of USC), Mark Coleman(University Hospitals Plymouth NHS Trust), Tom Cecil(Hampshire Hospitals NHS Foundation Trust), Anders Ericsson(Florida State University), Mehran Anvari(St. Joseph’s Healthcare Hamilton), Yulun Wang(InTouch Health (United States)), Yanick Beaulieu(Université de Montréal), Nadine Haram(Royal Free London NHS Foundation Trust), Ashwin Sridhar(University College Hospital), Jacques Marescaux(Institut de Recherche contre les Cancers de l’Appareil Digestif), Michèle Diana(Institut de Recherche contre les Cancers de l’Appareil Digestif), Hani J. Marcus(University College London), Jeffrey A. Levy, Prokar Dasgupta(King's College London), Dimitrios Stefanidis(Indiana University – Purdue University Indianapolis), Martin A Martino(University of South Florida), Richard H. Feins(University of North Carolina at Chapel Hill), Vipul Patel, Mark Slack(Addenbrooke's Hospital), Richard M. Satava(University of Washington Medical Center), John D. Kelly(University College London)
European Urology Open Science
November 6, 2020
Cited by 41Open Access
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Abstract

CONTEXT: The role of robot-assisted surgery continues to expand at a time when trainers and proctors have travel restrictions during the coronavirus disease 2019 (COVID-19) pandemic. OBJECTIVE: To provide guidance on setting up and running an optimised telementoring service that can be integrated into current validated curricula. We define a standardised approach to training candidates in skill acquisition via telepresence technologies. We aim to describe an approach based on the current evidence and available technologies, and define the key elements within optimised telepresence services, by seeking consensus from an expert committee comprising key opinion leaders in training. EVIDENCE ACQUISITION: This project was carried out in phases: a systematic review of the current literature, a teleconference meeting, and then an initial survey were conducted based on the current evidence and expert opinion, and sent to the committee. Twenty-four experts in training, including clinicians, academics, and industry, contributed to the Delphi process. An accelerated Delphi process underwent three rounds and was completed within 72 h. Additions to the second- and third-round surveys were formulated based on the answers and comments from the previous rounds. Consensus opinion was defined as ≥80% agreement. EVIDENCE SYNTHESIS: There was 100% consensus regarding an urgent need for international agreement on guidance for optimised telepresence. Consensus was reached in multiple areas, including (1) infrastructure and functionality; (2) definitions and terminology; (3) protocols for training, communication, and safety issues; and (4) accountability including ethical and legal issues. The resulting formulated guidance showed good internal consistency among experts, with a Cronbach alpha of 0.90. CONCLUSIONS: Using the Delphi methodology, we achieved international consensus among experts for development and content validation of optimised telepresence services for robotic surgery training. This guidance lays the foundation for launching telepresence services in robotic surgery. This guidance will require further validation. PATIENT SUMMARY: Owing to travel restrictions during the coronavirus disease 2019 (COVID-19) pandemic, development of remote training and support via telemedicine is becoming increasingly important. We report a key opinion leader consensus view on a standardised approach to telepresence.


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