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Published on: May 20, 2018
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Active control time: an objective performance metric for trainee participation in robotic surgery
Julie M Clanahan1, Andrew Yee2, Michael M Awad3
1Department of Surgery, Section of Minimally Invasive Surgery, Washington University School of Medicine, 660 South Euclid Avenue, Mailstop 8109-22-9905, Campus Box 8109, St. Louis, MO, 63110-1093, USA. julie.clanahan@wustl.edu.
Journal of Robotic Surgery
|May 26, 2023
Summary
Active control time (ACT) effectively measures trainee participation in robotic surgery. This metric increases with trainee experience and is higher in standard compared to complex cases, validating its use in surgical education.
Area of Science:
- Surgical Education
- Robotic Surgery
- Medical Technology Assessment
Background:
- Trainee participation in robotic general surgery is not well-defined.
- Objective metrics are needed to track performance in computer-assisted surgery.
Purpose of the Study:
- To validate active control time (ACT) as a novel metric for assessing trainee involvement in robotic-assisted surgeries.
- To analyze the relationship between trainee level, case complexity, and ACT.
Main Methods:
- Retrospective analysis of da Vinci Surgical System data from 123 robotic cases over 10 months.
- Inclusion of 18 general surgery residents and 1 fellow.
- Calculation of percent ACT (trainee console time / total active console time) and statistical analysis using Kruskal-Wallis and Mann-Whitney U tests.
Main Results:
- Median %ACT significantly increased with trainee level (PGY1 to fellow, p < 0.0001).
- Median %ACT was higher in standard cases than complex cases for PGY5 residents (60% vs. 36%, p = 0.0002) and fellows (74% vs. 47%, p = 0.0045).
Conclusions:
- Active control time (ACT) is a valid, objective measure of trainee participation in robotic surgery.
- ACT demonstrates increasing proficiency with trainee level and differences based on case complexity.
- Further research into task-specific ACT can refine robotic surgical training and performance evaluation.
Keywords:
Automated performance metricsObjective performance metricsRobotic educationRobotic surgeryRobotic training
