Applications of artificial intelligence in nursing triage contexts a systematic review
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Abstract
Background: Triage is a nursing competence aimed at assigning a priority code to patients presenting to the emergency department and assessing their potential risk evolution based on observable and reported symptoms. The triage nurse must be highly skilled and trained according to existing national regulations. Triage is a crucial moment to ensure patient management and define the order of access to treatment. Artificial intelligence (AI) is having an increasing global impact, particularly in supporting healthcare activities. This systematic review aimed to evaluate the effectiveness of AI-based systems in the nursing triage process compared to traditional methods.
Methods: The foreground question was formulated using the PICO method. The research was conducted using three databases (PubMed, Cinahl, Scopus) following PRISMA guidelines. To include as many relevant studies as possible, five different keyword combinations were used (nurs*, triage, artificial intelligence). Studies published between 2019 and 2024, in both Italian and English, were considered for inclusion.
Results: A total of 12 articles were included. More than half of the selected studies present very recent data. The extracted data primarily focused on study objectives, methodologies, measured outputs, and obtained results. In each included study, the findings were derived from a comparison between the performance of the described, proposed, or developed AI technologies and traditional triage procedures. The main limitation of this review is the limited availability of scientific literature on the subject.
Conclusions: The use of artificial intelligence in nursing triage is a rapidly evolving field with evident potential, particularly in optimizing nursing workflow. However, as this area is still expanding, most AI-based applications described and studied require further testing and refinement before being widely implemented. Overall, the findings from the reviewed studies are highly promising.
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