Can a Generative Artificial Intelligence Model Be Used to Create Mass Casualty Incident Simulation Scenarios? A Feasibility Study
The feasibility study suggests that a structured, collaborative workflow combining LLM-based generation with expert human review may enable a new approach to mass casualty trauma simulation scenario creation. LLMs hold promise as a scalable tool for the development of MCI training materials. However, consistent human oversight, quality assurance processes, and governance frameworks remain essential to ensure clinical accuracy, safety, and educational value.
Authors
- T. N. Diem Vu (ORCID: https://orcid.org/0000-0003-4405-3190)
- Mariela Rivera (ORCID: https://orcid.org/0000-0003-3085-5619)
- Sergio M. Navarro (ORCID: https://orcid.org/0000-0003-3455-1567)
- John Zietlow
- Maxwell J Jabaay
- Erica Loomis
- Daniel Stephens (ORCID: https://orcid.org/0000-0002-6980-0001)
- Sarah B. Lund (ORCID: https://orcid.org/0000-0003-2214-5916)
- Myung S. Park (ORCID: https://orcid.org/0000-0001-7421-0914)
- A. B. Atkinson
- Ege Donagay
Institutions
- Mayo Clinic (US)
- The University of Texas at San Antonio Health Science Center (US)
- Bilkent University (TR)
- Mayo Clinic in Florida (US)
Publication Details
- Journal
- Healthcare
- Published
- 2025-12-05
- DOI
- https://doi.org/10.3390/healthcare13243184
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00