Paramedic Papers

Home Trauma AI trauma triage in LMIC prehospital care

Trauma

AI trauma triage in LMIC prehospital care

Artificial Intelligence in the Golden Hour: A scoping review of prehospital trauma triage and implementation feasibility in LMICs
International Journal of Medical Informatics · Added 10 August 2026

Scoping review mapping AI applications in LMIC prehospital trauma care found ML models achieved AUC 0.91-0.94 for mortality prediction and digital platforms reduced response times from 162 to 13 minutes in Bangladesh.

Study type
Systematic review
Design
Scoping review (PRISMA-ScR) of AI in LMIC prehospital trauma care
Participants
17 primary studies
Main finding
ML models achieved AUC 0.91–0.94 for mortality prediction; digital platforms in Bangladesh reduced average response times from 162 to 13 minutes; edge-AI/NLP achieved 95% accuracy in low-connectivity settings
Caveat
Scoping review of heterogeneous LMIC studies; no appraisal of patient outcomes
Bottom line
Context only

Why it matters in Australia (Medium relevance). AI/ML methods are methodologically relevant, but study focused on LMIC contexts (Indonesia, Kenya, Bangladesh, Tanzania) with very different infrastructure and system constraints than Australia.

Learning goal

Weigh the role of AI-supported trauma triage tools in improving prehospital mortality prediction and resource decisions.

Open in dashboard Read the paper (DOI) PubMed

More

Related papers on Trauma