Modeling Performance of Open Surgical Cases.

Abstract

Previous efforts used digital video to develop computer-generated assessments of surgical hand motion economy and fluidity of motion. This study tests how well previously trained assessment models match expert ratings of suturing and tying video clips recorded in a new operating room (OR) setting. Enabled through computer vision of the hands, this study tests the applicability of assessments born out of benchtop simulations to in vivo suturing and tying tasks recorded in the OR. Compared with expert ratings, computer-generated assessments for fluidity of motion (slope = 0.83, intercept = 1.77, R2 = 0.55) performed better than motion economy (slope = 0.73, intercept = 2.04, R2 = 0.49), although 85% of ratings for both models were within ±2 of the expert response. Neither assessment performed as well in the OR as they did on the training data. Assessments were sensitive to changing hand postures, dropped ligatures, and poor tissue contact-features typically missing from training data. Computer-generated assessment of OR tasks was contingent on a clear, consistent view of both surgeon's hands. Computer-generated assessment may help provide formative feedback during deliberate practice, albeit with greater variability in the OR compared with benchtop simulations. Future work will benefit from expanded available bimanual video records.