Digital and artificial intelligence-supported triage system in emergency department

Selim Adiyaman () and Fatma Azizoglu ()
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Selim Adiyaman: Halic University / Turkiye
Fatma Azizoglu: Halic University / Turkiye

Journal of Original Studies, 2025, vol. 6, issue ongoing, e2587-e2587

Abstract: Aim: This study aims to evaluate the potential, feasibility, and current limitations of artificial intelligence (AI)-supported triage systems in emergency departments by examining their impact on healthcare services. Traditional triage systems rely on subjective assessments, which contribute to increased issues such as patient overcrowding and resource insufficiencies. In this context, AI-based systems enable faster, more objective, and consistent prioritization. Materials and Methods: Original research and review articles published between 2020 and 2025 were searched in relevant databases. Results: According to the literature review, AI-supported triage systems accelerate patient prioritization, reduce the cognitive load of healthcare workers, and offer advantages such as improving patient outcomes and decreasing waiting times. However, significant challenges remain regarding data security, lack of algorithmic transparency, ethical concerns, and system integration. Discussion and Conclusion: AI-supported digital triage systems have the potential to enhance efficiency and the quality of patient care in emergency departments. For their safe and effective widespread adoption, multicenter prospective clinical studies are necessary, alongside strengthening digital infrastructure and implementing comprehensive training programs for healthcare professionals.

Keywords: Artificial Intelligence; Triage; Emergency Department; Digital Health; Decision Support Systems (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:jle:joujos:jos2857

DOI: 10.47243/jos.2857

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