Task-Level vs. Segment-Level Quantitative Metrics for Surgical Skill Assessment

S. Swaroop Vedula, Anand Malpani, Narges Ahmidi, Sanjeev Khudanpur, Gregory Hager, Chi Chiung Grace Chen

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


Objective Task-level metrics of time and motion efficiency are valid measures of surgical technical skill. Metrics may be computed for segments (maneuvers and gestures) within a task after hierarchical task decomposition. Our objective was to compare task-level and segment (maneuver and gesture)-level metrics for surgical technical skill assessment. Design Our analyses include predictive modeling using data from a prospective cohort study. We used a hierarchical semantic vocabulary to segment a simple surgical task of passing a needle across an incision and tying a surgeon's knot into maneuvers and gestures. We computed time, path length, and movements for the task, maneuvers, and gestures using tool motion data. We fit logistic regression models to predict experience-based skill using the quantitative metrics. We compared the area under a receiver operating characteristic curve (AUC) for task-level, maneuver-level, and gesture-level models. Setting Robotic surgical skills training laboratory. Participants In total, 4 faculty surgeons with experience in robotic surgery and 14 trainee surgeons with no or minimal experience in robotic surgery. Results Experts performed the task in shorter time (49.74 s; 95% CI = 43.27-56.21 vs. 81.97; 95% CI = 69.71-94.22), with shorter path length (1.63 m; 95% CI = 1.49-1.76 vs. 2.23; 95% CI = 1.91-2.56), and with fewer movements (429.25; 95% CI = 383.80-474.70 vs. 728.69; 95% CI = 631.84-825.54) than novices. Experts differed from novices on metrics for individual maneuvers and gestures. The AUCs were 0.79; 95% CI = 0.62-0.97 for task-level models, 0.78; 95% CI = 0.6-0.96 for maneuver-level models, and 0.7; 95% CI = 0.44-0.97 for gesture-level models. There was no statistically significant difference in AUC between task-level and maneuver-level (p = 0.7) or gesture-level models (p = 0.17). Conclusions Maneuver-level and gesture-level metrics are discriminative of surgical skill and can be used to provide targeted feedback to surgical trainees.

Original languageEnglish (US)
Pages (from-to)482-489
Number of pages8
JournalJournal of surgical education
Issue number3
StatePublished - May 1 2016


  • decomposition
  • objective skill assessment
  • robotic surgical skills
  • segment-level skill metrics
  • task-level skill metrics

ASJC Scopus subject areas

  • Surgery
  • Education


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