Effectiveness of ChatGPT in explaining complex medical reports to patients
June 23, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Mengxuan Sun, Ehud Reiter, Anne E Kiltie, George Ramsay, Lisa Duncan, Peter Murchie, Rosalind Adam
arXiv ID
2406.15963
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CL,
q-bio.OT
Citations
4
Venue
arXiv.org
Last Checked
4 months ago
Abstract
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.
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