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Setting Benchmarks for the New User: Training on the Robotic Simulator

BACKGROUND AND OBJECTIVES: Data showing the impact of the robotic simulator on fellowship training are limited. This study was conducted to determine whether simulator scores reflect the experience of the robotic gynecologic surgeon and to develop a simulator curriculum for trainees in gynecologic o...

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Autores principales: Dioun, Shayan M., Fleming, Nicole D., Munsell, Mark F., Lee, Joseph, Ramirez, Pedro T., Soliman, Pamela T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Laparoendoscopic Surgeons 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5737239/
https://www.ncbi.nlm.nih.gov/pubmed/29279661
http://dx.doi.org/10.4293/JSLS.2017.00059
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author Dioun, Shayan M.
Fleming, Nicole D.
Munsell, Mark F.
Lee, Joseph
Ramirez, Pedro T.
Soliman, Pamela T.
author_facet Dioun, Shayan M.
Fleming, Nicole D.
Munsell, Mark F.
Lee, Joseph
Ramirez, Pedro T.
Soliman, Pamela T.
author_sort Dioun, Shayan M.
collection PubMed
description BACKGROUND AND OBJECTIVES: Data showing the impact of the robotic simulator on fellowship training are limited. This study was conducted to determine whether simulator scores reflect the experience of the robotic gynecologic surgeon and to develop a simulator curriculum for trainees in gynecologic oncology. METHODS: All faculty and fellows in the Department of Gynecologic Oncology and Reproductive Medicine were asked to participate. For phase 1, all participants were divided into 2 groups based on robotic surgical experience: beginner (0–50 cases) and experienced (>50 cases). Each participant completed 9 modules 3 times each to establish baseline data. Median module scores for the experienced group defined the benchmarks scores. In phase 2, all trainees who did not meet the benchmark score on a module were asked to repeat the module until they reached the score twice. RESULTS: Twenty-four participants were included: 18 beginners and 6 experienced surgeons. For all modules, experienced surgeons received higher median scores than beginners. There was a significant difference between the scores of the 2 groups in the Energy Switching 1 (87.5 vs 92.5; P = .002) and Suture Sponge 2 (75.0 vs 87.3; P = .011) modules. Thirteen trainees participated in phase 2. For 8 of 9 of the modules, >75% of trainees met proficiency, with a median of 3 to 6 attempts (range, 2–24). CONCLUSION: Based on the findings, scores reflected each surgeon's experience. With repetition, most of the trainees were able to reach the benchmark scores. Further study is needed to determine the impact of surgical simulation on true intraoperative performance.
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spelling pubmed-57372392017-12-26 Setting Benchmarks for the New User: Training on the Robotic Simulator Dioun, Shayan M. Fleming, Nicole D. Munsell, Mark F. Lee, Joseph Ramirez, Pedro T. Soliman, Pamela T. JSLS Scientific Paper BACKGROUND AND OBJECTIVES: Data showing the impact of the robotic simulator on fellowship training are limited. This study was conducted to determine whether simulator scores reflect the experience of the robotic gynecologic surgeon and to develop a simulator curriculum for trainees in gynecologic oncology. METHODS: All faculty and fellows in the Department of Gynecologic Oncology and Reproductive Medicine were asked to participate. For phase 1, all participants were divided into 2 groups based on robotic surgical experience: beginner (0–50 cases) and experienced (>50 cases). Each participant completed 9 modules 3 times each to establish baseline data. Median module scores for the experienced group defined the benchmarks scores. In phase 2, all trainees who did not meet the benchmark score on a module were asked to repeat the module until they reached the score twice. RESULTS: Twenty-four participants were included: 18 beginners and 6 experienced surgeons. For all modules, experienced surgeons received higher median scores than beginners. There was a significant difference between the scores of the 2 groups in the Energy Switching 1 (87.5 vs 92.5; P = .002) and Suture Sponge 2 (75.0 vs 87.3; P = .011) modules. Thirteen trainees participated in phase 2. For 8 of 9 of the modules, >75% of trainees met proficiency, with a median of 3 to 6 attempts (range, 2–24). CONCLUSION: Based on the findings, scores reflected each surgeon's experience. With repetition, most of the trainees were able to reach the benchmark scores. Further study is needed to determine the impact of surgical simulation on true intraoperative performance. Society of Laparoendoscopic Surgeons 2017 /pmc/articles/PMC5737239/ /pubmed/29279661 http://dx.doi.org/10.4293/JSLS.2017.00059 Text en © 2017 by JSLS, Journal of the Society of Laparoendoscopic Surgeons. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License (http://creativecommons.org/licenses/by-nc-nd/3.0/us/), which permits for noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited and is not altered in any way.
spellingShingle Scientific Paper
Dioun, Shayan M.
Fleming, Nicole D.
Munsell, Mark F.
Lee, Joseph
Ramirez, Pedro T.
Soliman, Pamela T.
Setting Benchmarks for the New User: Training on the Robotic Simulator
title Setting Benchmarks for the New User: Training on the Robotic Simulator
title_full Setting Benchmarks for the New User: Training on the Robotic Simulator
title_fullStr Setting Benchmarks for the New User: Training on the Robotic Simulator
title_full_unstemmed Setting Benchmarks for the New User: Training on the Robotic Simulator
title_short Setting Benchmarks for the New User: Training on the Robotic Simulator
title_sort setting benchmarks for the new user: training on the robotic simulator
topic Scientific Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5737239/
https://www.ncbi.nlm.nih.gov/pubmed/29279661
http://dx.doi.org/10.4293/JSLS.2017.00059
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