Explore Large Language Models (LLMs) and their transformative impact across various medical specialties within the Electronic Health Record (EHR) landscape. Attendees will uncover the multifaceted applications of LLMs, ranging from clinical documentation and coding to decision support systems and predictive analytics. By navigating real-world examples, participants will gain insights into how LLMs enhance efficiency, accuracy, and patient outcomes in diverse medical settings, while also addressing pertinent considerations surrounding data privacy, bias mitigation, and ethical implications. This session promises to empower healthcare professionals with the knowledge and tools needed to harness the full potential of LLMs within the complex tapestry of modern healthcare delivery.

Objectives

• Understand the diverse applications of Large Language Models (LLMs) within Electronic Health Records (EHRs) across various medical specialties, including clinical documentation, coding, decision support systems, and predictive analytics.
• Analyze real-world case studies and examples to identify how LLMs enhance efficiency, accuracy, and patient outcomes in healthcare settings, while also critically evaluating considerations such as data privacy, bias mitigation, and ethical implications.
• Develop practical strategies for leveraging LLMs effectively within the EHR landscape, including best practices for implementation, integration, and optimization to improve clinical workflows, enhance diagnostic capabilities, and advance healthcare delivery.