Predictive Validity of a Training Protocol Using a Robotic Surgery Simulator

Abstract

Robotic surgery simulation may provide a way for surgeons to acquire specific robotic surgical skills without practicing on live patients. Five robotic surgery experts performed 10 simulator skills to the best of their ability, and thus, established expert benchmarks for all parameters of these skills. A group of credentialed gynecologic surgeons naive to robotics practiced the simulator skills until they were able to perform each one as well as our experts. Within a week of doing so, they completed robotic pig laboratory training, after which they performed supracervical hysterectomies as their first-ever live human robotic surgery. Time, blood loss, and blinded assessments of surgical skill were compared among the experts, novices, and a group of control surgeons who had robotic privileges but no simulator exposure. Sample size estimates called for 11 robotic novices to achieve 90% power to detect a 1 SD difference between operative times of experts and novices (α = 0.05). Fourteen novice surgeons completed the study-spending an average of 20 hours (range, 9.7-38.2 hours) in the simulation laboratory to pass the expert protocol. The mean operative times for the expert and novices were 20.2 (2.3) and 21.7 (3.3) minutes, respectively (P = 0.12; 95% confidence interval, -1.7 to 4.7), whereas the mean time for control surgeons was 30.9 (0.6) minutes (P < 0.0001; 95% confidence interval, 6.3-12.3). Comparisons of estimated blood loss (EBL) and blinded video assessment of skill yielded similar differences between groups. Completing this protocol of robotic simulator skills translated to expert-level surgical times during live human surgery. As such, we have established predictive validity of this protocol.