BACKGROUND: The clinical application of robotic-assisted surgery (RAS) is rapidly increasing. The da Vinci Surgical System™ is currently the only commercially available RAS system. The skills necessary to perform robotic surgery are unique from those required for open and laparoscopic surgery. A validated laparoscopic surgical skills curriculum (fundamentals of laparoscopic surgery or FLS™) has transformed the way surgeons acquire laparoscopic skills. There is a need for a similar skills training and assessment tool specific for robotic surgery. Based on previously published data and expert opinion, we developed a robotic skills curriculum. We sought to evaluate this curriculum for evidence of construct validity (ability to discriminate between users of different skill levels). METHODS: Four experienced surgeons (>20 RAS) and 20 novice surgeons (first-year medical students with no surgical or RAS experience) were evaluated. The curriculum comprised five tasks utilizing the da Vinci™ Skills Simulator (Pick and Place, Camera Targeting 2, Peg Board 2, Matchboard 2, and Suture Sponge 3). After an orientation to the robot and a period of acclimation in the simulator, all subjects completed three consecutive repetitions of each task. Computer-derived performance metrics included time, economy of motion, master work space, instrument collisions, excessive force, distance of instruments out of view, drops, missed targets, and overall scores (a composite of all metrics). RESULTS: Experienced surgeons significantly outperformed novice surgeons in most metrics. Statistically significant differences were detected for each task in regards to mean overall scores and mean time (seconds) to completion. CONCLUSIONS: The curriculum we propose is a valid method of assessing and distinguishing robotic surgical skill levels on the da Vinci Si™ Surgical System. Further study is needed to establish proficiency levels and to demonstrate that training on the simulator with the proposed curriculum leads to improved robotic surgical performance in the operating room.
BACKGROUND: The clinical application of robotic-assisted surgery (RAS) is rapidly increasing. The da Vinci Surgical System™ is currently the only commercially available RAS system. The skills necessary to perform robotic surgery are unique from those required for open and laparoscopic surgery. A validated laparoscopic surgical skills curriculum (fundamentals of laparoscopic surgery or FLS™) has transformed the way surgeons acquire laparoscopic skills. There is a need for a similar skills training and assessment tool specific for robotic surgery. Based on previously published data and expert opinion, we developed a robotic skills curriculum. We sought to evaluate this curriculum for evidence of construct validity (ability to discriminate between users of different skill levels). METHODS: Four experienced surgeons (>20 RAS) and 20 novice surgeons (first-year medical students with no surgical or RAS experience) were evaluated. The curriculum comprised five tasks utilizing the da Vinci™ Skills Simulator (Pick and Place, Camera Targeting 2, Peg Board 2, Matchboard 2, and Suture Sponge 3). After an orientation to the robot and a period of acclimation in the simulator, all subjects completed three consecutive repetitions of each task. Computer-derived performance metrics included time, economy of motion, master work space, instrument collisions, excessive force, distance of instruments out of view, drops, missed targets, and overall scores (a composite of all metrics). RESULTS: Experienced surgeons significantly outperformed novice surgeons in most metrics. Statistically significant differences were detected for each task in regards to mean overall scores and mean time (seconds) to completion. CONCLUSIONS: The curriculum we propose is a valid method of assessing and distinguishing robotic surgical skill levels on the da Vinci Si™ Surgical System. Further study is needed to establish proficiency levels and to demonstrate that training on the simulator with the proposed curriculum leads to improved robotic surgical performance in the operating room.
Authors: Neal E Seymour; Anthony G Gallagher; Sanziana A Roman; Michael K O'Brien; Vipin K Bansal; Dana K Andersen; Richard M Satava Journal: Ann Surg Date: 2002-10 Impact factor: 12.969
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Authors: Daniel G Davila; Melissa C Helm; Matthew J Frelich; Jon C Gould; Matthew I Goldblatt Journal: Surg Endosc Date: 2017-12-06 Impact factor: 4.584
Authors: Beiqun Zhao; Jenny Lam; Hannah M Hollandsworth; Arielle M Lee; Nicole E Lopez; Benjamin Abbadessa; Samuel Eisenstein; Bard C Cosman; Sonia L Ramamoorthy; Lisa A Parry Journal: Surg Endosc Date: 2019-07-08 Impact factor: 4.584