Using Large Language Models to Improve Patient-Provider Communications

Poster Number: P40
Presentation Time: 05:00 PM - 06:30 PM

Abstract Keywords: Large Language Models (LLMs), Clinical Decision Support, Documentation Burden
Primary Track: Applications
Programmatic Theme: Clinical Informatics

Patient messages often lack important details, resulting in multiple rounds of messages for clinicians to gather the necessary information. We used a fine-tuned large language model (LLM) and ChatGPT to draft follow-up questions for patients. Five physicians rated them for utility, completeness, conciseness, and clarity. ChatGPT and the fine-tuned LLM could generate more useful and complete questions than those from healthcare providers. Overall, LLM shows great potential for improving patient-provider communication through patient portals.

Speaker(s):
Siru Liu, PhD
Vanderbilt University Medical Center

Author(s):
Siru Liu, PhD - Vanderbilt University Medical Center; Aileen Wright, MD - Vanderbilt; Allison McCoy, PhD, ACHIP, FACMI, FAMIA - Vanderbilt University Medical Center; Sean Huang, MD - Vanderbilt University; Julian Genkins - Stanford Health Care; Josh Peterson, MD, MPH - Vanderbilt University Medical Center; Yaa Kumah-Crystal - Vanderbilt Univeristy Medical Center; William Martinez, MD, MS - Vanderbilt University Medical Center; Babatunde Carew, MD - Vanderbilt University Medical Center; Dara Mize, MD, MS - Vanderbilt University Medical Center; Bryan Steitz, PhD - Vanderbilt University Medical Center; Adam Wright, PhD - Vanderbilt University Medical Center;