Personalizing Prostate Cancer Education for Patients Using an EHR-Integrated LLM Agent
Yuexing Hao, Jason Holmes, Mark R. Waddle, Brian J. Davis, Nathan Y. Yu, Kristin Vickers, Heather Preston, Drew Margolin, Corinna E. Lockenhoff, Aditya Vashistha, Saleh Kalantari, Marzyeh Ghassemi, Wei Liu

TL;DR
This study introduces MedEduChat, an EHR-integrated LLM agent that enhances prostate cancer patient education, improves health confidence, and is highly usable, demonstrating potential to support personalized patient engagement.
Contribution
Developed and evaluated MedEduChat, an innovative EHR-integrated LLM agent, to provide personalized prostate cancer education and support patient engagement in a clinical setting.
Findings
High usability score (UMUX 83.7/100)
Improved patient health confidence (score increased from 9.9 to 13.9)
Clinicians rated MedEduChat as highly correct, complete, and safe
Abstract
Cancer patients often lack timely education and personalized support due to clinician workload. This quality improvement study develops and evaluates a Large Language Model (LLM) agent, MedEduChat, which is integrated with the clinic's electronic health records (EHR) and designed to enhance prostate cancer patient education. Fifteen non-metastatic prostate cancer patients and three clinicians recruited from the Mayo Clinic interacted with the agent between May 2024 and April 2025. Findings showed that MedEduChat has a high usability score (UMUX 83.7 out of 100) and improves patients' health confidence (Health Confidence Score rose from 9.9 to 13.9). Clinicians evaluated the patient-chat interaction history and rated MedEduChat as highly correct (2.9 out of 3), complete (2.7 out of 3), and safe (2.7 out of 3), with moderate personalization (2.3 out of 3). This study highlights the…
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Taxonomy
TopicsArtificial Intelligence in Healthcare and Education · AI in Service Interactions · FinTech, Crowdfunding, Digital Finance
