Leveraging Large Language Models and Other Artificial Intelligence Methods to Advance Patient-Centered Clinical Decision Support

Presentation Time: 10:30 AM - 12:00 PM

Abstract Keywords: Clinical Decision Support, Large Language Models (LLMs), Patient Engagement and Preferences
Primary Track: Applications
Programmatic Theme: Clinical Informatics
Moderator: Prashila Dullabh, MD
NORC at the University of Chicago

Artificial intelligence (AI) holds great potential to improve healthcare delivery. AI can process large amounts of
clinical data and knowledge to provide recommendations quickly and accurately and has been harnessed to support
clinical decision making. However, there is still much to learn about the use of AI technology and its capabilities
within healthcare. The Agency for Healthcare Research and Quality (AHRQ) supports a range of projects to help
understand the role of AI in patient-centered clinical decision support (PC CDS). Featuring findings from AHRQ’s
Clinical Decision Support Innovation Collaborative (CDSiC), this panel discusses the opportunity for utilizing AI,
including large language models (LLMs), to aid patient-centered clinical decision making, and identifies important
knowledge gaps, challenges, and limitations. This panel will include a representative from a patient advocacy
organization (Crohn’s & Colitis Foundation) who will share perspectives on important considerations for leveraging
AI to support patient-centered clinical decision making.

Speaker(s):
Aziz Boxwala, MD, PhD
Elimu Informatics

Jessica Ancker, MPH, PhD, FACMI
Vanderbilt University Medical Center

Kensaku Kawamoto, MD, PhD, MHS
University of Utah

Angela Dobes, MPH
Crohn's & Colitis Foundation

Author(s):
Prashila Dullabh, MD - NORC at the University of Chicago; Jessica Ancker, MPH, PhD, FACMI - Vanderbilt University Medical Center; Kensaku Kawamoto, MD, PhD, MHS - University of Utah; Aziz Boxwala, MD, PhD - Elimu Informatics; Angela Dobes, MPH - Crohn's & Colitis Foundation;