Technological Advancements in Triage

Introduction. Artificial intelligence can analyze large-scale datasets to enhance decision-making and efficiency. Artificial intelligence has potential in trauma triage, yet remains underexplored. Effective triage is essential for optimizing patient outcomes and resource allocation, but current systems heavily rely on nurses’ judgment, which is subject to variability. AI-driven models could enhance accuracy, reduce bias, and support clinical decision-making in emergency care.Aim. This literature review explores the role of artificial intelligence in medical triage, assessing its impact on accuracy, efficiency, and decision-making in patient assessment and prioritization.Methods. A systematic search was conducted in March 2025 using PubMed, Web of Science and Hrčak databases to identify studies published between 2022 and 2025. Articles meeting predefined inclusion criteria were selected, resulting in 31 studies being included in the final review. The review followed PRISMA guidelines. Inclusion criteria consisted of systematic reviews, review articles, original research papers, cross-sectional studies, clinical trials, randomized controlled trials, and meta-analyses published in Croatian or English. The search terms included “artificial intelligence”, “triage”, “medical practice” and “nursing practice”.Results. The reviewed studies demonstrate that AI models can enhance triage accuracy and reliability, sometimes outperforming healthcare professionals

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Publication Details

Journal
Croatian Nursing Journal
Published
2025-12-19
DOI
https://doi.org/10.24141/2/9/2/13
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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article

Technological Advancements in Triage

Boris Ilić, Helena Mayerhoffer
Croatian Nursing Journal
Artificial Intelligence in Healthcare and Education
article

Technological Advancements in Triage

Boris Ilić, Helena Mayerhoffer
article en

Abstract

Introduction. Artificial intelligence can analyze large-scale datasets to enhance decision-making and efficiency. Artificial intelligence has potential in trauma triage, yet remains underexplored. Effective triage is essential for optimizing patient outcomes and resource allocation, but current systems heavily rely on nurses’ judgment, which is subject to variability. AI-driven models could enhance accuracy, reduce bias, and support clinical decision-making in emergency care.Aim. This literature review explores the role of artificial intelligence in medical triage, assessing its impact on accuracy, efficiency, and decision-making in patient assessment and prioritization.Methods. A systematic search was conducted in March 2025 using PubMed, Web of Science and Hrčak databases to identify studies published between 2022 and 2025. Articles meeting predefined inclusion criteria were selected, resulting in 31 studies being included in the final review. The review followed PRISMA guidelines. Inclusion criteria consisted of systematic reviews, review articles, original research papers, cross-sectional studies, clinical trials, randomized controlled trials, and meta-analyses published in Croatian or English. The search terms included “artificial intelligence”, “triage”, “medical practice” and “nursing practice”.Results. The reviewed studies demonstrate that AI models can enhance triage accuracy and reliability, sometimes outperforming healthcare professionals

Croatian Nursing JournalVol. 9(2)
University of Applied Health Sciences (HR)
Openalex Percentile: Top 37%
Artificial Intelligence in Healthcare and Education
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