AI-Based Decision Support Systems for Emergency Medical Services Triage

AI-based decision support systems (DSS) have the potential to significantly enhance Emergency Medical Services (EMS) triage by providing rapid, accurate, and consistent patient prioritization in high-pressure situations. Leveraging advanced machine learning, natural language processing, and real-time data integration, these systems assist EMS personnel in making informed decisions, reducing cognitive burden, and optimizing resource allocation. Despite challenges such as data quality, interoperability, user acceptance, and ethical concerns including privacy and algorithmic bias, AI-driven triage tools have demonstrated improved accuracy and efficiency in real-world applications. Future advancements promise greater personalization, transparency, and integration with telemedicine and wearable technologies, reshaping emergency care delivery. Multidisciplinary collaboration and ethical governance are essential to realizing AI’s full potential in EMS triage, ultimately improving patient outcomes and emergency response effectiveness globally.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-05
DOI
https://doi.org/10.5281/zenodo.15598370
Primary Topic
Emergency and Acute Care Studies
Type
article
Field-Weighted Citation Impact
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article

AI-Based Decision Support Systems for Emergency Medical Services Triage

Zenodo (CERN European Organization for Nuclear Research)
Emergency and Acute Care Studies
article

AI-Based Decision Support Systems for Emergency Medical Services Triage

article en

Abstract

AI-based decision support systems (DSS) have the potential to significantly enhance Emergency Medical Services (EMS) triage by providing rapid, accurate, and consistent patient prioritization in high-pressure situations. Leveraging advanced machine learning, natural language processing, and real-time data integration, these systems assist EMS personnel in making informed decisions, reducing cognitive burden, and optimizing resource allocation. Despite challenges such as data quality, interoperability, user acceptance, and ethical concerns including privacy and algorithmic bias, AI-driven triage tools have demonstrated improved accuracy and efficiency in real-world applications. Future advancements promise greater personalization, transparency, and integration with telemedicine and wearable technologies, reshaping emergency care delivery. Multidisciplinary collaboration and ethical governance are essential to realizing AI’s full potential in EMS triage, ultimately improving patient outcomes and emergency response effectiveness globally.

Zenodo (CERN European Organization for Nuclear Research)
Krishna University (IN)
Openalex Percentile: Top 42%
Emergency and Acute Care Studies
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AI-Based Decision Support Systems for Emergency Medical Services Triage · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS