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Using Real-time Feedback To Improve Surgical Performance on a Robotic Tissue Dissection Task

Laca, Jasper A. and Kocielnik, Rafal and Nguyen, Jessica H. and You, Jonathan and Tsang, Ryan and Wong, Elyssa Y. and Shtulman, Andrew and Anandkumar, Anima and Hung, Andrew J. (2022) Using Real-time Feedback To Improve Surgical Performance on a Robotic Tissue Dissection Task. European Urology Open Science, 46 . pp. 15-21. ISSN 2666-1683. doi:10.1016/j.euros.2022.09.015.

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Background: There is no standard for the feedback that an attending surgeon provides to a training surgeon, which may lead to variable outcomes in teaching cases. Objective: To create and administer standardized feedback to medical students in an attempt to improve performance and learning. Design, setting, and participants: A cohort of 45 medical students was recruited from a single medical school. Participants were randomly assigned to two groups. Both completed two rounds of a robotic surgical dissection task on a da Vinci Xi surgical system. The first round was the baseline assessment. In the second round, one group received feedback and the other served as the control (no feedback). Outcome measurements and statistical analysis: Video from each round was retrospectively reviewed by four blinded raters and given a total error tally (primary outcome) and a technical skills score (Global Evaluative Assessment of Robotic Surgery [GEARS]). Generalized linear models were used for statistical modeling. According to their initial performance, each participant was categorized as either an innate performer or an underperformer, depending on whether their error tally was above or below the median. Results and limitations: In round 2, the intervention group had a larger decrease in error rate than the control group, with a risk ratio (RR) of 1.51 (95% confidence interval [CI] 1.07–2.14; p = 0.02). The intervention group also had a greater increase in GEARS score in comparison to the control group, with a mean group difference of 2.15 (95% CI 0.81–3.49; p < 0.01). The interaction effect between innate performers versus underperformers and the intervention was statistically significant for the error rates, at F(1,38) = 5.16 (p = 0.03). Specifically, the intervention had a statistically significant effect on the error rate for underperformers (RR 2.23, 95% CI 1.37–3.62; p < 0.01) but not for innate performers (RR 1.03, 95% CI 0.63–1.68; p = 0.91). Conclusions: Real-time feedback improved performance globally compared to the control. The benefit of real-time feedback was stronger for underperformers than for trainees with innate skill. Patient summary: We found that real-time feedback during a training task using a surgical robot improved the performance of trainees when the task was repeated. This feedback approach could help in training doctors in robotic surgery.

Item Type:Article
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URLURL TypeDescription CentralArticle
Kocielnik, Rafal0000-0001-5602-6056
Nguyen, Jessica H.0000-0003-0454-8463
Shtulman, Andrew0000-0002-4687-3099
Anandkumar, Anima0000-0002-6974-6797
Hung, Andrew J.0000-0002-7201-6736
Additional Information:© 2022 The Author(s). Published by Elsevier B.V. on behalf of European Association of Urology Under a Creative Commons license. Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) This work was supported by the National Science Foundation under grant #2030859 to the Computing Research Association for the CIFellows Project. The sponsor played a role in analysis and interpretation of the data and review of the manuscript.
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Record Number:CaltechAUTHORS:20221122-564647900.20
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ID Code:118004
Deposited By: Research Services Depository
Deposited On:07 Dec 2022 18:44
Last Modified:23 May 2023 20:57

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