Susanne I Scott1, Torur Dalsgaard2, Jan Vibjerg Jepsen3,4, Christian von Buchwald1, Steven Arild Wuyts Andersen1,4. 1. Department of Otorhinolaryngology, Head & Neck Surgery and Audiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark. 2. Department of Gynaecology, Endometriosis Team and Robotic Surgery Section, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark. 3. Department of Urology, Herlev Hospital, Herlev, Denmark. 4. Copenhagen Academy for Medical Education and Simulation (CAMES), Center for HR, Copenhagen, Denmark.
Abstract
BACKGROUND: The aim of this study was to design and validate a cross-specialty basic robotic surgical skills training program on the RobotiX Mentor virtual reality simulator. METHODS: A Delphi panel reached consensus on six modules to include in the training program. Validity evidence was collected according to Messick's framework with three performances in each simulator module by 11 experienced robotic surgeons and 11 residents without robotic surgical experience. RESULTS: For five of the six modules, a compound metrics-based score could significantly discriminate between the performances of novices and experienced robotic surgeons. Pass/fail levels were established, resulting in very few novices passing in their first attempt. CONCLUSIONS: This validated course can be used for structured simulation-based basic robotic surgical skills training within a mastery learning framework where the individual trainee can practice each module until they achieve proficiency and can continue training on other modalities and more specific to their specialty.
BACKGROUND: The aim of this study was to design and validate a cross-specialty basic robotic surgical skills training program on the RobotiX Mentor virtual reality simulator. METHODS: A Delphi panel reached consensus on six modules to include in the training program. Validity evidence was collected according to Messick's framework with three performances in each simulator module by 11 experienced robotic surgeons and 11 residents without robotic surgical experience. RESULTS: For five of the six modules, a compound metrics-based score could significantly discriminate between the performances of novices and experienced robotic surgeons. Pass/fail levels were established, resulting in very few novices passing in their first attempt. CONCLUSIONS: This validated course can be used for structured simulation-based basic robotic surgical skills training within a mastery learning framework where the individual trainee can practice each module until they achieve proficiency and can continue training on other modalities and more specific to their specialty.