Improving patient understanding of radiology reports using generative artificial intelligence: a vignette study of 2000 US adults

Objectives Patients value access to their medical reports on patient portals, but the terminology in those reports can cause confusion and anxiety. Can the artificial intelligence (AI) simplification of radiology reports into plain language improve patient comprehension? Materials and Methods Twenty original radiology reports (breast imaging, chest X-ray) were simplified into plain language using ChatGPT-4 using a customized prompt for each report type. For each report, clinicians created a gold standard of key findings and appropriate follow-up. In August 2024, a national sample of 2000 US adults reviewed 2 randomly assigned reports, 1 original and 1 AI-generated plain language. Participants answered questions focused on comprehension of key findings, follow-up, confidence, anxiety, and preferences. Comprehension and follow-up were compared to the gold standard. We compared patient accuracy for original vs AI-generated plain language reports. Results Participants (mean age 48 years) were 62.3% female. Compared to original reports, participants shown AI-generated plain language reports had higher accuracy in comprehension (68.0% vs 58.0%; marginal difference 10.8% [95% CI, 7.8%-13.8%]) and follow-up (64.5% vs 58.4%; marginal difference 6.8% [95% CI, 4.1%-9.4%]). Improvements were larger among participants aged >44 years and with less than college education. With plain language reports, participants reported higher confidence in their answers and lower anxiety. Despite these improvements, 60.0% of participants preferred the original report over the plain language version. Discussion Integrating AI simplification into patient portals may be helpful, but trust concerns remain. Conclusion AI simplification improved patient comprehension and confidence. Further research is needed to address patient resistance to AI simplification.