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 potential of LLM agents to improve patient engagement and health education.

翻译：由于临床医生工作负荷繁重，癌症患者常常无法获得及时的教育和个性化支持。这项质量改进研究开发并评估了一个名为MedEduChat的大型语言模型代理，该代理与诊所的电子健康记录系统集成，旨在加强前列腺癌患者教育。2024年5月至2025年4月期间，从梅奥诊所招募的15名非转移性前列腺癌患者和3名临床医生与该代理进行了交互。研究结果显示，MedEduChat具有较高的可用性评分（UMUX得分为83.7/100），并能提升患者的健康信心（健康信心评分从9.9上升至13.9）。临床医生评估了患者与聊天交互的历史记录，认为MedEduChat在准确性（2.9/3）、完整性（2.7/3）和安全性（2.7/3）方面表现优异，个性化程度适中（2.3/3）。本研究突显了大型语言模型代理在改善患者参与度和健康教育方面的潜力。