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Competency in Robotic Surgery: Standard Setting for Robotic Suturing Using Objective Assessment and Expert

Taseen F Haque1, J Everett Knudsen1, Jonathan You2

  • 1Catherine & Joseph Aresty Department of Urology, USC Institute of Urology, University of Southern California, Los Angeles, California.

Journal of Surgical Education
|January 30, 2024
PubMed
Summary
This summary is machine-generated.

This study established a benchmark for robotic suturing competency using the End-to-End Assessment of Suturing Expertise (EASE) tool. The developed standard accurately assessed surgical trainees, ensuring readiness for independent practice.

Keywords:
benchmarkingclinical competenceeducationrobotic surgical procedures

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Area of Science:

  • Surgical Education
  • Robotic Surgery
  • Medical Simulation

Background:

  • Surgical skill assessment tools are crucial for differentiating surgeon experience levels.
  • The End-to-End Assessment of Suturing Expertise (EASE) is a validated measure for suturing performance.
  • Defining competency benchmarks is essential for surgical training and independent practice readiness.

Purpose of the Study:

  • To define a competency benchmark for intraoperative robotic suturing.
  • To utilize the EASE tool as a validated measure of performance in a simulation-based study.
  • To establish a standard for assessing technical readiness in surgical trainees.

Main Methods:

  • Participants performed a dry-lab vesicourethral anastomosis (VUA) robotic suturing exercise.
  • Videos were scored by blinded reviewers using EASE, with inter-rater reliability assessed via PABAK.
  • The Contrasting Group (CG) method was employed to set a pass/fail benchmark score based on expert evaluation.

Main Results:

  • High inter-rater reliability (average PABAK 0.90) was achieved for EASE subskills.
  • A competency benchmark EASE score of >35/39 was established, with a 38% pass rate.
  • The benchmark demonstrated no false positives or negatives, accurately differentiating trainee competency levels.

Conclusions:

  • An absolute standard setting method established competency scores for robotic suturing.
  • The defined benchmark can inform high-stakes decisions regarding trainee technical readiness.
  • Future research will validate this standard in the clinical environment by correlating it with patient outcomes.