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

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• 作者：S. Swaroop Vedula ; MBBS ; PhD^* ; ^{vedula@jhu.edu" class="auth_mail" title="E-mail the corresponding author} ; Anand Malpani ; MSE^* ; Narges Ahmidi ; PhD^* ; Sanjeev Khudanpur ; PhD^&dagger ; ; Gregory Hager ; PhD^* ; Chi Chiung Grace Chen ; MD^&Dagger ;
• 关键词：task decomposition ; segment-level skill metrics ; objective skill assessment ; task-level skill metrics ; robotic surgical skills
• 刊名：Journal of Surgical Education
• 出版年：2016
• 出版时间：May-June 2016
• 年：2016
• 卷：73
• 期：3
• 页码：482-489
• 全文大小：1078 K

文摘

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.