Electronic health records contain detailed information about the medical
condition of patients, but they are difficult for patients to understand even
if they have access to them. We explore whether ChatGPT (GPT 4) can help
explain multidisciplinary team (MDT) reports to colorectal and prostate cancer
patients. These reports are written in dense medical language and assume
clinical knowledge, so they are a good test of the ability of ChatGPT to
explain complex medical reports to patients. We asked clinicians and lay people
(not patients) to review explanations and responses of ChatGPT. We also ran
three focus groups (including cancer patients, caregivers, computer scientists,
and clinicians) to discuss output of ChatGPT. Our studies highlighted issues
with inaccurate information, inappropriate language, limited personalization,
AI distrust, and challenges integrating large language models (LLMs) into
clinical workflow. These issues will need to be resolved before LLMs can be
used to explain complex personal medical information to patients.

电子病历、ChatGPT、多学科团队报告、医学语言和大型语言模型是本研究的关键词。研究发现，大型语言模型能帮助解释复杂的医学报告给患者，但存在信息不准确、语言不当、个性化有限、人工智能不信任以及将大型语言模型融入临床工作流程的挑战等问题需要解决。