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AI Matches Physicians in Identifying Urgent Cases in the Emergency Department

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UCSF-led study finds artificial intelligence is as good as a physician at prioritizing which patients need to be seen first. 

Emergency departments nationwide are overcrowded and overtaxed, but a new study suggests artificial intelligence (AI) could one day help prioritize which patients need treatment most urgently. 

Using anonymized records of 251,000 adult emergency department (ED) visits, researchers at UC San Francisco evaluated how well an AI model was able to extract symptoms from patients’ clinical notes to determine their need to be treated immediately. They then compared the AI analysis with the patients’ scores on the Emergency Severity Index, a 1-5 scale that ED nurses use when patients arrive to allocate care and resources by highest need, a process known as triage.

The patients’ data were separated from their actual identities (de-identified) for the study, which publishes May 7, 2024, in JAMA Network Open. The researchers evaluated the data using the ChatGPT-4 large language model (LLM), accessing it via UCSF’s secure generative AI platform, which has broad privacy protections. 

The researchers tested the LLM’s performance with a sample of 10,000 matched pairs – 20,000 patients in total – that included one patient with a serious condition, such as stroke, and another with a less urgent condition, such as a broken wrist. Given only the patients’ symptoms, the AI was able to identify which ED patient in the pair had a more serious condition 89% of the time.

In a sub-sample of 500 pairs that were evaluated by a physician as well as the LLM, the AI was correct 88% of the time, compared to 86% for the physician.

Having AI assist in the triage process could free up critical physician time to treat patients with the most serious conditions, while offering backup decision-making tools for clinicians who are juggling multiple urgent requests.