Key points are not available for this paper at this time.
BACKGROUND: Incomplete prehospital documentation remains a major challenge, compromising continuity of care and data quality. Manual documentation is time-consuming and cognitively demanding, particularly under operational stress. Speech-based artificial intelligence (AI) systems may enable real-time documentation without interrupting clinical workflow. METHODS: We conducted a feasibility study comparing AI-assisted speech-based documentation with conventional manual documentation during simulated prehospital trauma care. Eight teams completed trauma scenarios using both documentation methods in randomized order. AI outputs were structured into 40 predefined documentation fields derived from the standard combat casualty card. Documentation completeness and user-reported usability were compared between methods. Analyses were performed on paired team-scenario observations. RESULTS: Forty-four simulations were completed (22 per method), with successful AI output in 91% of cases. Overall documentation completeness was similar between AI-assisted and manual documentation 73.9% (interquartile range, 64.1–83.7) vs. 64.8% (interquartile range, 58.7–79.2); p =0.31, with no differences across scenarios or documentation categories (all p >0.05). Usability ratings favored the AI-assisted approach for overall ease of use ( p =0.024) and data entry ( p =0.015). CONCLUSIONS: In this simulated prehospital battlefield setting, AI-assisted speech-based documentation was feasible and achieved documentation completeness comparable to manual documentation while improving perceived usability. Further development and real-world evaluation are needed for operational implementation. ( J Trauma Acute Care Surg 2026;00:000–000 Copyright © 2026 Wolters Kluwer Health, Inc. All rights reserved.) LEVEL OF EVIDENCE: Level III.
Gelman et al. (Mon,) studied this question.