An objective approach to evaluate novice robotic surgeons using a combination of kinematics and stepwise cumulative sum (CUSUM) analyses

摘要: Current evaluation methods for robotic-assisted surgery (ARCS or GEARS) are limited to 5-point Likert scales which inherently time-consuming and require a degree of subjective scoring. In this study, we demonstrate method break down complex robotic surgical procedures using combination an objective cumulative sum (CUSUM) analysis kinematics data obtained from the da Vinci® Surgical System evaluate performance novice surgeons. Two HPB fellows performed 40 hepaticojejunostomy reconstructions model portion Whipple procedure. Kinematics system was recorded dV Logger® while CUSUM analyses were each procedural step. Each kinematic variable modeled machine learning reflect fellows’ curves task. Statistically significant variables then combined into single formula create operative index (ORI). The inflection points our overall showed improvement in technical beginning at trial 16. derived ORI strong fit observed (R2 = 0.796) with ability distinguish between intermediate 89.3% accuracy. novel approach objectively on System. We identified associated improved ORI. This demonstrates valuable objective, stepwise fashion. Continued research will be invaluable future training clinical implementation platform.