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Related Experiment Videos

A Comparative Study of Generative Artificial Intelligence Versus Clinical Experts for Evidence-Based Decision-Making

Ross M Scallan¹, Bethany Atwood¹, Chandler H Moser²

¹Center for Nursing Science and Clinical Inquiry, Landstuhl Regional Medical Center, Landstuhl, Rheinland-Pfalz 66849, Germany.

Military Medicine

|July 7, 2026

Summary

Generative AI rapidly synthesizes clinical protocols, but government tools prioritized speed over safety. Human oversight is crucial for ensuring AI supports, not replaces, clinical judgment in healthcare settings.

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Area of Science:

Biomedical informatics
Artificial intelligence in healthcare
Evidence-based practice implementation

Background:

Exponential growth in biomedical data challenges evidence-based practice adoption, especially in resource-limited military settings.
Generative artificial intelligence (AI) presents a potential solution for rapid evidence synthesis.
This study compares generative AI tools with human experts for identifying surgical instrument reprocessing protocols in austere environments.

Purpose of the Study:

To evaluate the utility and feasibility of generative AI tools versus human clinical experts.
To compare AI and expert performance in identifying surgical instrument reprocessing protocols for austere settings.
To assess time-to-completion, accessibility, and clinical validity of AI-generated recommendations.

Main Methods:

A descriptive comparative study queried four AI platforms (NIPRGPT, ChatGPT, Google Gemini, GenAI.mil) and two clinical experts.
Participants were prompted to identify the best recommendation for reprocessing surgical instruments without steam sterilization in austere environments.
Outputs were compared based on time, firewall accessibility (Department of War), and clinical validity against literature.

Main Results:

AI platforms completed tasks in under 10 minutes, while experts took 14 hours.
Commercial AI (ChatGPT, Gemini) faced firewall blocks; GenAI.mil was accessible.
Experts recommended chlorine dioxide (ClO2) for sterility; only ChatGPT matched. Other AIs recommended OPA or glutaraldehyde, prioritizing speed over sterility assurance.

Conclusions:

Generative AI significantly reduces time and cognitive load for clinical protocol synthesis.
Government-hosted AI prioritized logistics over safety, creating an accessibility-accuracy paradox.
AI implementation requires human verification and governance to ensure it complements clinical judgment.