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Background <p>Training in robotic surgery entails a stepwise progression, starting with technology training. This aspect, which includes setup and docking, is an intricate process, which can be performed by the wider surgical team, including trainees and surgical care practitioners. Despite this, no uniform accreditation framework exists for assessing competence in robotic system setup, with our aim to establish a robust mechanism for this.</p> Methods <p>An international Delphi consensus was conducted to develop a stepwise accreditation protocol for robotic surgical setup. A granular checklist was developed by a steering committee, divided into five key phases of setup (system knowledge, port placement, docking, instrument exchange, and undocking) on the da&#xa0;Vinci&#xa0;Xi platform. Opinions on methods of accreditation, competency cut-offs, and assessors were also surveyed.</p> Results <p>54 experts from 13 countries participated (73% consultant surgeons, 19% surgical care practitioners, 8% fellows). The majority had extensive robotic experience (61.9% involved in &gt; 500 cases). Key findings included knowledge of port placement, the need for reverse communication with instrument changes, and standardised emergency undocking workflows. 85% of respondents supported certification for bedside assistants, preferably assessed by experienced robotic surgeons or assistants (82%). Based upon the protocol, competency was deemed to be demonstrated by a score of 80% or 90% by 81% of respondents. Statements were formulated into a freely usable online form.</p> Conclusion <p>This Delphi consensus formulated a standardised accreditation curriculum for robotic system setup. The protocol provides a tool which can guide training and assessment of competency in robotic docking and setup, addressing a gap in robotic surgery training. Adoption of this framework could benefit training for surgical teams and improve safety. Future validation will be necessary to correlate use with improved performance.</p>

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Development of a platform-specific objective assessment tool for the accreditation of robotic setup and docking

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月7日

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  • T. Shakir,
  • G. Lingam,
  • M. Boal,
  • M. Chand,
  • N. Francis

摘要

Background

Training in robotic surgery entails a stepwise progression, starting with technology training. This aspect, which includes setup and docking, is an intricate process, which can be performed by the wider surgical team, including trainees and surgical care practitioners. Despite this, no uniform accreditation framework exists for assessing competence in robotic system setup, with our aim to establish a robust mechanism for this.

Methods

An international Delphi consensus was conducted to develop a stepwise accreditation protocol for robotic surgical setup. A granular checklist was developed by a steering committee, divided into five key phases of setup (system knowledge, port placement, docking, instrument exchange, and undocking) on the da Vinci Xi platform. Opinions on methods of accreditation, competency cut-offs, and assessors were also surveyed.

Results

54 experts from 13 countries participated (73% consultant surgeons, 19% surgical care practitioners, 8% fellows). The majority had extensive robotic experience (61.9% involved in > 500 cases). Key findings included knowledge of port placement, the need for reverse communication with instrument changes, and standardised emergency undocking workflows. 85% of respondents supported certification for bedside assistants, preferably assessed by experienced robotic surgeons or assistants (82%). Based upon the protocol, competency was deemed to be demonstrated by a score of 80% or 90% by 81% of respondents. Statements were formulated into a freely usable online form.

Conclusion

This Delphi consensus formulated a standardised accreditation curriculum for robotic system setup. The protocol provides a tool which can guide training and assessment of competency in robotic docking and setup, addressing a gap in robotic surgery training. Adoption of this framework could benefit training for surgical teams and improve safety. Future validation will be necessary to correlate use with improved performance.