In the second episode our three part series, we dive deeper into the practical impact of artificial intelligence on emergency medicine with expert, Dr. Gabriel Wardi. Building on our previous discussion about AI’s role in healthcare, we explore clinical decision support systems (CDS)—how they aim to improve diagnostic accuracy but can sometimes miss the mark. Dr. Wardi shares insights from his own experience implementing AI-driven CDS, highlighting both its successes and challenges, including bias, reliability, and the importance of high-quality data. We discuss how AI can address traditional pitfalls of CDS, improve outcomes like sepsis care, and offer a glimpse into the future of AI in emergency settings. Plus, we look ahead to the critical conversation of AI governance and regulation in EM. Tune in as we break down what’s working, what’s next, and how frontline EM physicians can stay ahead of the curve.

How are you using AI in your ED? What are your concerns and hopes for the future of AI in medicine? Keep the discussion going on social media @empulsepodcast or at ucdavisem.com

Hosts:

Dr. Julia Magaña, Professor of Pediatric Emergency Medicine at UC Davis

Dr. Sarah Medeiros, Associate Professor of Emergency Medicine at UC Davis

Guest:

Dr. Gabriel Wardi, Associate Professor & Chief of the Division of Critical Care in the Department of Emergency Medicine at UC San Diego

Resources:

Boussina A, Shashikumar SP, Malhotra A, Owens RL, El-Kareh R, Longhurst CA, Quintero K, Donahue A, Chan TC, Nemati S, Wardi G. Impact of a deep learning sepsis prediction model on quality of care and survival. NPJ Digit Med. 2024 Jan 23;7(1):14. doi: 10.1038/s41746-023-00986-6. Erratum in: NPJ Digit Med. 2024 Jun 12;7(1):153. doi: 10.1038/s41746-024-01149-x. PMID: 38263386; PMCID: PMC10805720.

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Thank you to the UC Davis Department of Emergency Medicine for supporting this podcast and to Orlando Magaña at OM Productions for audio production services.