The Surgical Learning Curve: Does Robotic Technical Skill Explain Differences in Operative Performance?

Journal: Journal of laparoendoscopic & advanced surgical techniques. Part A
Published Date:

Abstract

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. Sleeve gastrectomy cases ( = 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 test was used to define differences between surgeons with the eta-squared value for effect size. Linear regression was used for temporal changes. A value <.05 was considered significant. 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 ( = 0.0001-0.096). Subcomponent scores showed idiosyncratic temporal changes, although force sensitivity increased among all ( = 0.172-0.243). For a novice surgeon, phase-adjusted operative time ( = 0.24), but not overall GEARS scores ( = 0.04), improved over time. 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.

Authors

  • Daniel P Bitner
    Intraoperative Performance Analytics Laboratory (IPAL), Department of General Surgery, Northwell Health, Lenox Hill Hospital, 186 E. 76th Street, 1st Floor, New York, NY, 10021, USA. DBitner@northwell.edu.
  • Saratu Kutana
    Intraoperative Performance Analytics Laboratory (IPAL), Department of General Surgery, Northwell Health, Lenox Hill Hospital, 186 E. 76th Street, 1st Floor, New York, NY, 10021, USA.
  • Katherine Carsky
    Intraoperative Performance Analytics Laboratory (IPAL), Department of General Surgery, Northwell Health, Lenox Hill Hospital, New York, New York, USA.
  • Poppy Addison
    Intraoperative Performance Analytics Laboratory (IPAL), Department of General Surgery, Northwell Health, Lenox Hill Hospital, 186 E. 76th Street, 1st Floor, New York, NY, 10021, USA.
  • Samuel P DeChario
    Institute for Spine and Scoliosis, Lawrenceville, New Jersey, USA.
  • Anthony Antonacci
    Department of General Surgery, Lenox Hill Hospital, Northwell Health, New York, NY, US.
  • David Mikhail
    Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
  • Edward Yatco
    Intraoperative Performance Analytics Laboratory (IPAL), Department of General Surgery, Northwell Health, Lenox Hill Hospital, New York, New York, USA.
  • Paul J Chung
    Department of Surgery.
  • Filippo Filicori
    Intraoperative Performance Analytics Laboratory (IPAL), Department of General Surgery, Northwell Health, Lenox Hill Hospital, 186 E. 76th Street, 1st Floor, New York, NY, 10021, USA.