Navigating GenAI in Healthcare: Why Clinical Guidelines Matter More Than Ever, sponsored by MCG Health
As generative AI (GenAI) technology advances, its use in healthcare is becoming more prevalent. However, large language models (LLMs) still present significant risks, even when they are applied to direct source material. This session will explore the known pitfalls of LLMs in medicine, presenting evidence of ongoing errors and challenges, as well as potential solutions to address these problems.
Learning Objectives:
- Identify the key risks and challenges associated with using large language models (LLMs) in clinical decision-making processes
- Describe MCG Health's approach to AI-assisted clinical review, including methods to maintain broad clinical context
- Demonstrate the role of clinician involvement at each stage of the AI development process, from data preparation to user acceptance testing (UAT)
Your presenter:
Daniel Cawood, Senior Product Manager, Interoperability Solutions, MCG Health
Daniel Cawood oversees the product development for MCG Health’s interoperability solutions and connects payers and providers for authorization processes. Mr. Cawood began his time at MCG, focusing on the Indicia suite of solutions (provider market clinical decision support) and value-based care solutions. Before joining MCG, he was a Product Owner for Research & Development solutions at Optum Technology, where he focused on using advanced technologies to solve operational, clinical, and business problems.
