Effects of automated skill assessment on robotic surgery training

Abstract

Background Several automated skill‐assessment approaches have been proposed for robotic surgery, but their utility is not well understood. This article investigates the effects of one machine‐learning‐based skill‐assessment approach on psychomotor skill development in robotic surgery training. Methods N = 29 trainees (medical students and residents) with no robotic surgery experience performed five trials of inanimate peg transfer with an Intuitive Surgical da Vinci Standard robot. Half of the participants received no post‐trial feedback. The other half received automatically calculated scores from five Global Evaluative Assessment of Robotic Skill domains post‐trial. Results There were no significant differences between the groups regarding overall improvement or skill improvement rate. However, participants who received post‐trial feedback rated their overall performance improvement significantly lower than participants who did not receive feedback. Conclusions These findings indicate that automated skill evaluation systems might improve trainee self‐awareness but not accelerate early stage psychomotor skill development in robotic surgery training.

Crossover-effects in technical skills between laparoscopy and robot-assisted surgery

“…However, there is no association between laparoscopic experience and robotic-assisted suturing performance, according to OSATS scores, and there is evidence that assessment forms are not be suitable for the assessment of robotic technical skills and to differentiate between levels of expertise [43,44]. This was confirmed by other recent studies, were novices were assessed during RAS skills training [45,46]. The GEARS increased selfawareness, but did not influence the acquisition of technical skill among trainees, and no correlation was found between technical skill and operative performance.…”