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This talk shares insights from real-world use of text-based AI at the bedside—from opioid misuse screening via EHR notes to Ambient AI for automating documentation—highlighting both opportunities and risks, as well as approaches for evaluation and improvement.

Large language models (LLMs) have shown remarkable potential in the medical domain, with specialized medical LLMs developed and applied across a variety of tasks. However, their effectiveness in medicine remains uncertain, and practical guidance for their deployment in specific applications is still limited.

The deployment of text-based AI models at the point of care introduces new opportunities—and risks—for improving clinical documentation, communication, and decision support. In this talk, I will share lessons learned from the real-world bedside implementation of AI systems that use the EHR notes for screening opioid misuse to Ambient AI for automating clinical documentation, as well as methods for monitoring, evaluation, and continuous improvement.

This month features Dr. Romero-Brufau, Director of AI for the Department of ENT at Mayo Clinic, where he is also Assistant Professor of ENT and Healthcare Systems Engineering. He will share AI and clinical informatics research information and career insights.

Accessing laboratory test results is the most common activity on patient portals, yet many patients—especially older adults with multiple chronic conditions—struggle to interpret their meaning. In this webinar, we will present a series of studies conducted as part of LabGenie.