Mayo Clinic AI Agent Delivers Personalized Prostate Cancer Education Through Electronic Health Records

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Mayo Clinic researchers developed MedEduChat, an EHR-integrated AI agent that provides accurate, patient-specific prostate cancer education. The tool increased Health Confidence Scores from 9.9 to 13.9 and achieved 83.7 out of 100 usability scores. Clinicians rated its responses as highly correct, complete and safe, marking a significant step toward AI-assisted cancer care.

Mayo Clinic Develops EHR-Integrated AI Agent for Prostate Cancer Patients

Mayo Clinic researchers have created MedEduChat, an innovative AI agent that integrates with electronic health records to deliver personalized prostate cancer education tailored to each patient's medical history. Published in npj Digital Medicine, the study demonstrates how an AI-powered large language model can bridge critical gaps in patient understanding during a time when cancer patients face overwhelming uncertainty about their diagnosis and treatment options

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Source: News-Medical

Source: News-Medical

The tool addresses a persistent challenge in cancer care: limited time with clinicians often leaves patients without the detailed answers they need to make informed decisions. By grounding advanced AI in Mayo-validated clinical data, MedEduChat provides clear, conversational explanations drawn directly from each patient's own health record, helping them navigate complex medical information with greater confidence

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Increased Patient Confidence and High Usability Scores

Fifteen prostate cancer patients participated in a usability study conducted at Mayo Clinic campuses in Arizona and Minnesota, interacting with MedEduChat for 20 to 30 minutes. The results showed remarkable improvements in patient experience: Health Confidence Scores increased from 9.9 to 13.9 on a 16-point scale, demonstrating the tool's effectiveness in building patient understanding and reducing anxiety

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High usability scores further validated the system's design, with average survey responses ranking MedEduChat at 83.7 out of 100. Patients reported that the conversational format helped them understand their diagnosis in a more accessible way, providing relief by explaining unfamiliar medical terminology in clear, concise language. The tool proved particularly effective at replacing incorrect assumptions with medically accurate information derived from their own electronic health records

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Clinician Validated Accuracy and Safety Standards

Wei Liu, Ph.D., a radiation oncology medical physicist, led a rigorous evaluation alongside three Mayo Clinic clinicians who independently reviewed 85 anonymized question-and-response pairs. The accurate guidance for cancer patients was evident in the ratings: clinicians scored MedEduChat's answers as highly correct (2.9 out of 3), complete (2.7 out of 3), and safe (2.7 out of 3)

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Clinicians noted strong patient-readiness and moderate personalization, reflecting the system's ability to tailor explanations based on each person's age, treatment history, and cancer stage. However, they emphasized the importance of ongoing monitoring to prevent errors that could arise from incomplete or inconsistently documented EHR data. The research team incorporated a multilayer approach to address these concerns and guide future system enhancements

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Understanding Diagnosis and Treatment Options Through Structured Education

MedEduChat was designed with a structured educational model that combines closed-domain clinical data, semi-structured guidance, and personalized interaction. Patients can explore diagnosis details, learn about treatment options and side effects, and review lifestyle considerations and follow-up expectations. The tool draws exclusively from validated sources, including Mayo Clinic materials and National Comprehensive Cancer Network guidelines, ensuring reliability and clinical alignment

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"This research demonstrates how large language models can be safely and effectively integrated into real clinical systems to improve cancer education," according to Dr. Liu. "By combining advanced AI with Mayo Clinic's electronic health records, MedEduChat delivers personalized, accurate and easy-to-understand explanations tailored to each patient's medical history"

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Expanding Cancer Research and Clinical Implementation

The study team plans to translate this work into clinical use across all three Mayo Clinic campuses in Arizona, Florida, and Minnesota. Next steps include expanding MedEduChat beyond radiation oncology to additional cancer specialties, aiming to make personalized AI-assisted education a routine part of cancer care. This expansion could transform how patients across multiple cancer types receive information and support during their treatment journey

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The research was funded by the National Cancer Institute, the Eric and Wendy Schmidt Fund for AI Research and Innovation, the Fred C. and Katherine B. Andersen Foundation, and the Kemper Marley Foundation. As healthcare systems explore AI integration, this study offers a blueprint for safely deploying large language models in clinical settings while maintaining accuracy, personalization, and patient safety standards

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