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Author Spotlight: Segmentation and VR for Advanced Neurovascular Interventions
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Shared Learning Utilizing Digital Methods in Surgery to Enhance Transparency in Surgical Innovation: Protocol for a

Christin Hoffmann1, Matthew Kobetic1, Natasha Alford1

  • 1National Institute for Health and Care Research, Bristol Biomedical Research Centre, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.

JMIR Research Protocols
|September 8, 2022
PubMed
Summary

This scoping review examines digital methods for surgical training and feedback. It aims to improve knowledge sharing for surgical innovation, reducing errors and accelerating the adoption of new techniques.

Keywords:
digitaldigital healthdigital methoddigital tooleHealtheducationfeedbackinnovationlearningmedical educationoperativeproceduresreviewreview methodologyscoping reviewshared learningsurgeonsurgerysurgicaltraining

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Area of Science:

  • Medical Education
  • Surgical Innovation
  • Digital Health

Background:

  • Surgical innovation offers improved patient outcomes but lacks standardized knowledge dissemination.
  • Informal dissemination (e.g., social media) leads to inefficient learning, repeated errors, and delayed adoption of new techniques.
  • There is a need for real-time, standardized methods for sharing surgical innovation knowledge.

Purpose of the Study:

  • To conduct a scoping review of digital methods for surgical training, education, and feedback.
  • To summarize existing shared learning methods in surgery, their application, impact, benefits, and barriers.
  • To inform the development of novel, real-time methods for optimizing shared learning in surgical innovation.

Main Methods:

  • Adherence to scoping review guidelines with 6 comprehensive searches across multiple sources.
  • Inclusion of articles in English from the last 5 years, focusing on theater staff, digital shared learning methods, and evaluations.
  • Two-stage study selection and 10% double data extraction, analyzed using descriptive statistics, narrative summaries, and thematic analysis.

Main Results:

  • Systematic searches of 2 electronic databases yielded 10,093 records.
  • The study commenced in October 2021 and is planned for completion in 2023.
  • Results will be published open access in a peer-reviewed journal.

Conclusions:

  • This is a comprehensive review of current methods for shared learning in surgery.
  • Efficient knowledge sharing can optimize surgical research evaluation and reduce harmful innovation.
  • Findings will guide the development of improved real-time learning methods for surgical innovation.