New research published in JAMA Network Open found agentic AI models to be largely safe and effective when used to generate hospital course summaries.
The AI summarization tool used in the study was also associated with reduced clinician burnout and modest time savings.
The findings were based on a 10-week prospective pilot at a Stanford Health Care inpatient unit in which 11 attending hospitalist physicians used an agentic AI workflow, powered by Gemini 2.5 Pro.
The custom agentic AI workflow developed for the study, known as MedAgentBrief, generated draft hospital course summaries nightly.
The system followed a multi-step process: the AI created an initial draft based on the patient's history, physical and latest note, iterated on that draft with chronological notes and cross-checks and added citations to reduce hallucinations.
It produced a final summary that included a patient one-liner, a problem-based summary and a narrative hospital course overview, the study stated.
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