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The Surgical Learning Curve: Does Robotic Technical Skill Explain Differences in Operative Performance?
Bitner, Daniel P; Kutana, Saratu; Carsky, Katherine; Addison, Poppy; DeChario, Samuel P; Antonacci, Anthony; Mikhail, David; Yatco, Edward; Chung, Paul J; Filicori, Filippo.
Afiliação
  • Bitner DP; Intraoperative Performance Analytics Laboratory (IPAL), Department of General Surgery, Northwell Health, Lenox Hill Hospital, New York, New York, USA.
  • Kutana S; Intraoperative Performance Analytics Laboratory (IPAL), Department of General Surgery, Northwell Health, Lenox Hill Hospital, New York, New York, USA.
  • Carsky K; Intraoperative Performance Analytics Laboratory (IPAL), Department of General Surgery, Northwell Health, Lenox Hill Hospital, New York, New York, USA.
  • Addison P; Intraoperative Performance Analytics Laboratory (IPAL), Department of General Surgery, Northwell Health, Lenox Hill Hospital, New York, New York, USA.
  • DeChario SP; Institute for Spine and Scoliosis, Lawrenceville, New Jersey, USA.
  • Antonacci A; Intraoperative Performance Analytics Laboratory (IPAL), Department of General Surgery, Northwell Health, Lenox Hill Hospital, New York, New York, USA.
  • Mikhail D; Department of General Surgery, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, USA.
  • Yatco E; Intraoperative Performance Analytics Laboratory (IPAL), Department of General Surgery, Northwell Health, Lenox Hill Hospital, New York, New York, USA.
  • Chung PJ; Department of Urology, Northwell Health, Lenox Hill Hospital, New York, New York, USA.
  • Filicori F; Intraoperative Performance Analytics Laboratory (IPAL), Department of General Surgery, Northwell Health, Lenox Hill Hospital, New York, New York, USA.
J Laparoendosc Adv Surg Tech A ; 33(5): 471-479, 2023 May.
Article em En | MEDLINE | ID: mdl-36668994
ABSTRACT

Background:

Prior studies on technical skills use small collections of videos for assessment. However, there is likely heterogeneity of performance among surgeons and likely improvement after training. If technical skill explains these differences, then it should vary among practicing surgeons and improve over time. Materials and

Methods:

Sleeve gastrectomy cases (n = 162) between July 2018 and January 2021 at one health system were included. Global evaluative assessment of robotic skills (GEARS) scores were assigned by crowdsourced evaluators. Videos were manually annotated. Analysis of variance was used to compare continuous variables between surgeons. Tamhane's post hoc test was used to define differences between surgeons with the eta-squared value for effect size. Linear regression was used for temporal changes. A P value <.05 was considered significant.

Results:

Variations in operative time discriminated between individuals (e.g., between 2 surgeons, means were 91 and 112 minutes, Tamhane's = 0.001). Overall, GEARS scores did not vary significantly (e.g., between those 2 surgeons, means were 20.32 and 20.6, Tamhane's = 0.151). Operative time and total GEARS score did not change over time (R2 = 0.0001-0.096). Subcomponent scores showed idiosyncratic temporal changes, although force sensitivity increased among all (R2 = 0.172-0.243). For a novice surgeon, phase-adjusted operative time (R2 = 0.24), but not overall GEARS scores (R2 = 0.04), improved over time.

Conclusions:

GEARS scores showed less variability and did not improve with time for a novice surgeon. Improved technical skill does not explain the learning curve of a novice surgeon or variation among surgeons. More work could define valid surrogate metrics for performance analysis.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Robótica / Procedimentos Cirúrgicos Robóticos / Cirurgiões Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Robótica / Procedimentos Cirúrgicos Robóticos / Cirurgiões Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article