Quantitative Assessment of the Learning Curve for Robotic Thyroid Surgery

With the increased utilization of robot thyroidectomy in recent years, surgical proficiency is the paramount consideration. However, there is no single perfect or ideal method for measuring surgical proficiency. In this study, we evaluated the learning curve of robotic thyroidectomy using various pa...

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Main Authors: HyunGoo Kim, Hyungju Kwon, Woosung Lim, Byung-In Moon, Nam Sun Paik
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Journal of Clinical Medicine
Subjects:
Online Access:https://www.mdpi.com/2077-0383/8/3/402
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spelling doaj-6d7eb7fd937444d19a27b105d4dbb03f2020-11-24T21:44:27ZengMDPI AGJournal of Clinical Medicine2077-03832019-03-018340210.3390/jcm8030402jcm8030402Quantitative Assessment of the Learning Curve for Robotic Thyroid SurgeryHyunGoo Kim0Hyungju Kwon1Woosung Lim2Byung-In Moon3Nam Sun Paik4Department of Surgery, Ewha Womans University Medical Center, 1071 Anyangcheon-ro, Yangcheon-Gu, Seoul 07985, KoreaDepartment of Surgery, Ewha Womans University Medical Center, 1071 Anyangcheon-ro, Yangcheon-Gu, Seoul 07985, KoreaDepartment of Surgery, Ewha Womans University Medical Center, 1071 Anyangcheon-ro, Yangcheon-Gu, Seoul 07985, KoreaDepartment of Surgery, Ewha Womans University Medical Center, 1071 Anyangcheon-ro, Yangcheon-Gu, Seoul 07985, KoreaDepartment of Surgery, Ewha Womans University Medical Center, 1071 Anyangcheon-ro, Yangcheon-Gu, Seoul 07985, KoreaWith the increased utilization of robot thyroidectomy in recent years, surgical proficiency is the paramount consideration. However, there is no single perfect or ideal method for measuring surgical proficiency. In this study, we evaluated the learning curve of robotic thyroidectomy using various parameters. A total of 172 robotic total thyroidectomies were performed by a single surgeon between March 2014 and February 2018. Cumulative summation analysis revealed that it took 50 cases for the surgeon to significantly improve the operation time. Mean operation time was significantly shorter in the group that included the 51st to the 172nd case, than in the group that included only the first 50 cases (132.8 &#177; 27.7 min vs. 166.9 &#177; 29.5 min; <i>p</i> &lt; 0.001). On the other hand, the surgeon was competent after the 75th case when postoperative transient hypoparathyroidism was used as the outcome measure. The incidence of hypoparathyroidism gradually decreased from 52.0%, for the first 75 cases, to 40.2% after the 76th case. These results indicated that the criteria used to assess proficiency greatly influenced the interpretation of the learning curve. Incorporation of the operation time, complications, and oncologic outcomes should be considered in learning curve assessment.https://www.mdpi.com/2077-0383/8/3/402learning curveCUSUMroboticthyroid
collection DOAJ
language English
format Article
sources DOAJ
author HyunGoo Kim
Hyungju Kwon
Woosung Lim
Byung-In Moon
Nam Sun Paik
spellingShingle HyunGoo Kim
Hyungju Kwon
Woosung Lim
Byung-In Moon
Nam Sun Paik
Quantitative Assessment of the Learning Curve for Robotic Thyroid Surgery
Journal of Clinical Medicine
learning curve
CUSUM
robotic
thyroid
author_facet HyunGoo Kim
Hyungju Kwon
Woosung Lim
Byung-In Moon
Nam Sun Paik
author_sort HyunGoo Kim
title Quantitative Assessment of the Learning Curve for Robotic Thyroid Surgery
title_short Quantitative Assessment of the Learning Curve for Robotic Thyroid Surgery
title_full Quantitative Assessment of the Learning Curve for Robotic Thyroid Surgery
title_fullStr Quantitative Assessment of the Learning Curve for Robotic Thyroid Surgery
title_full_unstemmed Quantitative Assessment of the Learning Curve for Robotic Thyroid Surgery
title_sort quantitative assessment of the learning curve for robotic thyroid surgery
publisher MDPI AG
series Journal of Clinical Medicine
issn 2077-0383
publishDate 2019-03-01
description With the increased utilization of robot thyroidectomy in recent years, surgical proficiency is the paramount consideration. However, there is no single perfect or ideal method for measuring surgical proficiency. In this study, we evaluated the learning curve of robotic thyroidectomy using various parameters. A total of 172 robotic total thyroidectomies were performed by a single surgeon between March 2014 and February 2018. Cumulative summation analysis revealed that it took 50 cases for the surgeon to significantly improve the operation time. Mean operation time was significantly shorter in the group that included the 51st to the 172nd case, than in the group that included only the first 50 cases (132.8 &#177; 27.7 min vs. 166.9 &#177; 29.5 min; <i>p</i> &lt; 0.001). On the other hand, the surgeon was competent after the 75th case when postoperative transient hypoparathyroidism was used as the outcome measure. The incidence of hypoparathyroidism gradually decreased from 52.0%, for the first 75 cases, to 40.2% after the 76th case. These results indicated that the criteria used to assess proficiency greatly influenced the interpretation of the learning curve. Incorporation of the operation time, complications, and oncologic outcomes should be considered in learning curve assessment.
topic learning curve
CUSUM
robotic
thyroid
url https://www.mdpi.com/2077-0383/8/3/402
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