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RoCS: Robotic Curriculum for young Surgeons.

Jessica Stockheim1, Aristotelis Perrakis2, Bernhard A Sabel3

  • 1Department of General, Visceral, Vascular and Transplant Surgery, University Hospital Magdeburg, Otto-Von-Guericke University Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany. jessica.stockheim@med.ovgu.de.

Journal of Robotic Surgery
|July 9, 2022
PubMed
Summary

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A new training curriculum, "robotic curriculum for young surgeons" (RoCS), provides essential robotic abdominal surgery skills for residents. This multimodal program enhances surgical training and evaluates learning success for early-career surgeons.

Area of Science:

  • Surgical Education
  • Minimally Invasive Surgery
  • Robotic Surgery

Background:

  • Robotic-assisted surgery is increasingly common, but training programs often target experienced surgeons.
  • A need exists for structured curricula to train residents in robotic abdominal surgery.

Approach:

  • Developed the
  • robotic curriculum for young surgeons
  • (RoCS) based on literature review and implemented it in a German university hospital.
  • Utilized the robotic assessment questionnaire (RAQ) for data collection and iterative curriculum improvement.
  • Incorporated multimodal training including operating table assistance, console training, robotic team time-out (rTTO), and standardized perioperative processes.

Key Points:

  • RoCS integrates basic robotic surgical skills training with standardized perioperative protocols.
Keywords:
NASA Task Load IndexResidencyRobotic surgerySurgical curriculumTraining

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  • Key elements include rTTO, personnel scheduling, and procedural clustering by organ system and complexity.
  • The curriculum allows for evaluation of communication, performance, patient factors, and workload using tools like the NASA Task Load Index.
  • Conclusions:

    • RoCS offers a flexible and adaptable training solution for young surgeons in robotic procedures.
    • The program effectively addresses the specific needs of residents and evaluates their learning progress.
    • Further multicenter validation is recommended to confirm the concept's broader applicability and compare different robotic systems.