Demonstrating the effectiveness of the fundamentals of robotic surgery (FRS) curriculum on the RobotiX Mentor Virtual Reality Simulation Platform.

Fundamentals of robotic surgery (FRS) is a proficiency-based progression curriculum developed by robotic surgery experts from multiple specialty areas to address gaps in existing robotic surgery training curricula. The RobotiX Mentor is a virtual reality training platform for robotic surgery. Our aims were to determine if robotic surgery novices would demonstrate improved technical skills after completing FRS training on the RobotiX Mentor, and to compare the effectiveness of FRS across training platforms. An observational, pre-post design, multi-institutional rater-blinded trial was conducted at two American College of Surgeons Accredited Education Institutes-certified simulation centers. Robotic surgery novices (n = 20) were enrolled and trained to expert-derived benchmarks using FRS on the RobotiX Mentor. Participants' baseline skill was assessed before (pre-test) and after (post-test) training on an avian tissue model. Tests were video recorded and graded by blinded raters using the Global Evaluative Assessment of Robotic Skills (GEARS) and a 32-criteria psychomotor checklist. Post hoc comparisons were conducted against previously published comparator groups. On paired-samples T tests, participants demonstrated improved performance across all GEARS domains (p < 0.001 to p = 0.01) and for time (p < 0.001) and errors (p = 0.003) as measured by psychometric checklist. By ANOVA, improvement in novices' skill after FRS training on the RobotiX Mentor was not inferior to improvement reported after FRS training on previously published platforms. Completion of FRS on the RobotiX Mentor resulted in improved robotic surgery skills among novices, proving effectiveness of training. These data provide additional validity evidence for FRS and support use of the RobotiX Mentor for robotic surgery skill acquisition.

Performance variability during training on simulators is associated with skill transfer.

BACKGROUND: Expert performance is characterized by consistency. The degree of variability of performance from repetition to repetition during proficiency-based simulator training could potentially indicate acquisition of expertise. We hypothesized that learners with less variability in performance during simulator training would achieve greater performance at the end of training and improved transfer of skills to a live, anesthetized, porcine model. METHODS: The performance of 93 subjects (surgery residents and medical students) who had participated in 3 randomized controlled trials was analyzed for variability. All participants had trained in laparoscopic suturing on the Fundamentals of Laparoscopic Surgery (FLS) simulator. Their performance had been assessed on the simulator before (baseline) and after training (posttest) and on a live, anesthetized, porcine model (transfer test). We computed the coefficient of variations of suturing scores during training for each participant. Linear regression was used to assess whether variability in performance during training predicted posttest and transfer-test scores. RESULTS: Decreased practice variability in performance was associated with greater scores in posttests and transfer tests. For each percent decrease in variability performance, posttest scores increased by 3.8 points (P < .001) and transfer-test scores increased by 3.0 points (P < .001). Greater mean scores during practice were associated with greater scores on the transfer test (P < .001). CONCLUSION: Decreased variability in performance during practice on simulators is associated with improved performance at the end of training and during transfer to a live, anesthetized, porcine model. These findings suggest that variability in performance during simulator training may be used to track the progress and readiness of a trainee for the clinical environment. Further studies are needed to verify the robustness of this potentially new metric of performance.