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{
    "pk": 48989,
    "title": "Impact of Artificial Intelligence-supported Triage Systems on Emergency Department Management: A Comparison of Infermedica, Emergency Severity Index, and Manchester Triage System",
    "subtitle": null,
    "abstract": "<p><strong>Objective:</strong> The surge in the number of emergency department (ED) visits due to a growing population, aging society, and easier access to healthcare highlights the need for an effective triage process. Our goal in this study was to compare the clinical and operational performance of a triage system supported by artificial intelligence (AI) with two traditional methods—the Emergency Severity Index and the Manchester Triage System—in a high-volume ED.</p>\n<p><strong>Methods: </strong>In this prospective study, 18,000 adult patients were randomized equally to one of the three triage systems. Primary and secondary outcomes included patient wait time, complication and mortality rates, resource utilization, medical errors, legal issues, and patient satisfaction.</p>\n<p><strong>Results:</strong> Compared with the Manchester Triage System, the AI-supported system was associated with significantly lower in-ED mortality (OR 0.39, 95% CI, 0.32–0.47; P &lt; .001) and lower complication rates (4.42% vs 10.25%), as well as higher patient satisfaction scores (9.0 vs 7.0; P &lt; .001). Resource utilization was also more balanced in the AI-supported triage cohort.</p>\n<p><strong>Conclusion:</strong> The AI-assisted triage system showed favorable clinical and operational patterns relative to traditional methods. However, the single-center design and short observation period limit generalizability, and causal inferences could not be firmly established.</p>",
    "language": "eng",
    "license": {
        "name": "Creative Commons Attribution 4.0",
        "short_name": "CC BY 4.0",
        "text": "Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.\r\n\r\nNo additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.",
        "url": "https://creativecommons.org/licenses/by/4.0"
    },
    "keywords": [
        {
            "word": "Infermedica"
        },
        {
            "word": "Emergency Severity Index"
        },
        {
            "word": "Manchester Triage System"
        },
        {
            "word": "Clinical Outcomes"
        },
        {
            "word": "Patient Satisfaction"
        },
        {
            "word": "Risk Management"
        }
    ],
    "section": "Emergency Department Operations",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/1246980t",
    "frozenauthors": [
        {
            "first_name": "Erkan",
            "middle_name": "",
            "last_name": "Boğa",
            "name_suffix": "",
            "institution": "Esenyurt Necmi Kadıoğlu State Hospital, Emergency Medicine Service, Istanbul, Türkiye",
            "department": ""
        }
    ],
    "date_submitted": "2025-07-13T18:20:20.085000Z",
    "date_accepted": "2025-11-21T23:37:21.933000Z",
    "date_published": "2026-02-27T16:15:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/westjem/article/48989/galley/49046/download/"
        }
    ]
}