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BID Artifacts: An Artificial Intelligence-powered Briefing-Intraoperative-Debriefing Platform for Competency-based
David Fernando Duque-Ropero1,2, Andres Fernando Gómez-Samper2
1From the Grupo de Investigación Salud de la Mujer, Clínica Universitaria Colombia, Clínica Colsanitas-Organización Sanitas, Bogotá, Colombia.
Plastic and Reconstructive Surgery. Global Open
|August 12, 2026
Summary
An AI platform called BID Artifacts automates surgical education frameworks for plastic surgery training. This innovative tool, developed by a surgeon, offers scalable digital implementation with positive user feedback and low costs.
Area of Science:
- Medical Education
- Artificial Intelligence
- Plastic Surgery
Background:
- The briefing-intraoperative-bebriefing (BID) framework shows potential in surgical education but lacks scalable digital solutions.
- BID Artifacts, an AI-powered web platform, was developed to automate the BID framework for plastic surgery training.
- The platform was created by a single practicing plastic surgeon using AI-assisted coding, eliminating the need for an engineering team.
Purpose of the Study:
- To develop and evaluate an AI-powered digital platform for automating the BID framework in plastic surgery education.
- To assess the usability and educational perception of the BID Artifacts platform among surgical trainees.
- To demonstrate the feasibility of a clinician developing a comprehensive educational tool without engineering support.
Main Methods:
- A progressive web application was designed, integrating large language models (Claude Sonnet and Gemini Flash) for case generation, feedback, and anatomical diagrams.
- Thirteen users across five training levels (postgraduate year-1 to fellow) participated in BID sessions on various surgical topics.
- System usability was measured using the System Usability Scale, and educational perception was evaluated via an 8-item Likert survey.
Main Results:
- The platform achieved a mean System Usability Scale score of 82.9 (Grade B, good), with 84.6% scoring 72 or above.
- Educational perception averaged 4.70/5.0, with procedural preparedness rated highest (4.92/5.0).
- Immediate AI feedback and critical thinking development were highly valued features, with an average cost of $1.05 per session and no infrastructure costs.
Conclusions:
- BID Artifacts effectively automates the BID framework using AI, serving as both a pedagogical engine and a development tool.
- The study highlights the capability of a single clinician to build a sophisticated educational platform with AI assistance.
- Further validation with larger participant groups is recommended to confirm these findings in plastic surgery education.
