When it comes to informing patients of their imaging results, radiologists are caught between a rock and hard place. A new study in JACR shows how generative AI can help by drafting patient-friendly reports that are simple but accurate.
Patients must be informed immediately of their medical results according to a 2021 final rule under the 21st Century Cures Act that prevents medical information blocking.
- And while the technology exists to do that through tools like email and electronic patient portals, rapid notification can create confusion because the language physicians use to communicate with each other isn’t easily understood by anyone outside medicine.
Sure, radiology reports could be rewritten manually for patients, who typically read at about the eighth-grade level.
- But given today’s workforce shortages, who’s going to do that?
Generative AI and large language models offer a solution. In the new JACR paper, researchers from Stanford University led by senior author Curtis Langlotz, MD, PhD, described their development of RadGPT, an LLM designed to improve patient communication.
- To develop RadGPT, researchers started with OpenAI’s GPT-4 model and the RadGraph concept extraction tool to create an LLM that analyzes patient radiology reports and generates concept explanations and question-and-answer pairs.
How well did RadGPT work? The researchers tested it on 30 radiology reports generated at Stanford from 2012 to 2020, including different modalities and clinical applications.
- The LLM was asked to generate reports at a fifth-grade reading level (the level recommended by the Joint Commission for patient-facing healthcare materials).
Five radiology-trained physicians then rated the quality of RadGPT’s responses, finding …
- The average rating of RadGPT-generated concept explanations was 4.8 out of 5.
- 95% of concept explanations had an average rating of 4 or higher.
- 50% of concept explanations were rated 5, the highest possible rating.
- Questions and answers generated by RadGPT were also rated highly, with an average rating of 3.0 on a three-point scale..
The Stanford researchers told The Imaging Wire that their goal is to make RadGPT more widely available as part of a prospective evaluation with real patients.
- They are also developing a user-friendly interface in which patients can receive hyperlinked radiology reports.
The Takeaway
RadGPT and solutions like it fill a desperate need for tools that can save time for radiologists while helping patients better understand their reports and get more engaged in their care. The next step is to get technology like this into the hands of practicing radiologists.
