Multidisciplinary validation study of the da Vinci Skills Simulator: educational tool and assessment device

Despite the increased dexterity and precision of robotic surgery, like any new surgical technology it is still associated with a learning curve that can impact patient outcomes. The use of surgical simulators outside of the operating room, in a low-stakes environment, has been shown to shorten such...

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Bibliographic Details
Published in:Journal of robotic surgery 2013-12, Vol.7 (4), p.365-369
Main Authors: Foell, Kirsten, Furse, Alexander, Honey, R. John D’A., Pace, Kenneth T., Lee, Jason Y.
Format: Article
Language:English
Subjects:
Cameras
Capital costs
Colleges & universities
Consoles
Core curriculum
Correlation coefficients
Digital video recorders
Education
Errors
Gynecology
Handedness
Learning curves
Medicine
Medicine & Public Health
Minimally Invasive Surgery
Needles
Original Article
Realism
Robot learning
Robotic surgery
Simulation
Simulators
Skill development
Skills
Statistical analysis
Surgeons
Surgery
Sutures
Teaching methods
Thoracic surgery
Training
Urology
Validation studies
Validity
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Summary:Despite the increased dexterity and precision of robotic surgery, like any new surgical technology it is still associated with a learning curve that can impact patient outcomes. The use of surgical simulators outside of the operating room, in a low-stakes environment, has been shown to shorten such learning curves. We present a multidisciplinary validation study of a robotic surgery simulator, the da Vinci ® Skills Simulator (dVSS). Trainees and attending faculty from the University of Toronto, Departments of Surgery and Obstetrics and Gynecology (ObGyn), were recruited to participate in this validation study. All participants completed seven different exercises on the dVSS (Camera Targeting 1, Peg Board 1, Peg Board 2, Ring Walk 2, Match Board 1, Thread the Rings, Suture Sponge 1) and, using the da Vinci S Robot (dVR), completed two standardized skill tasks (Ring Transfer, Needle Passing). Participants were categorized as novice robotic surgeon (NRS) and experienced robotic surgeon (ERS) based on the number of robotic cases performed. Statistical analysis was conducted using independent T test and non-parametric Spearman’s correlation. A total of 53 participants were included in the study: 27 urology, 13 ObGyn, and 13 thoracic surgery (Table  1 ). Most participants (89 %) either had no prior console experience or had performed
ISSN:1863-2483
1863-2491
DOI:10.1007/s11701-013-0403-6