radiology reports Archives - The Imaging Wire

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.

It’s one of radiology’s great dilemmas – should patients get their own radiology reports? A new review article in JACR examines this question in more detail, documenting shifting attitudes toward data sharing among radiologists, referring physicians, and patients themselves.

In reality, the question of whether patients should get their own reports has been settled by the 2022 implementation of federal information blocking rules that prevent providers from withholding patient data.

But open questions remain, such as the best mechanisms for delivering data to patients and how to ensure they aren’t confused or alarmed by radiology findings.

To that end, researchers conducted a systematic review of studies from 2007 to 2023 on patient access to radiology reports, eventually identifying 33 publications that revealed …

70% of studies found patients expressing positive preference toward accessing their radiology reports, a trend consistent over the entire study period.
42% of studies documented patient difficulties in understanding medical terminology.
33% highlighted concerns about patient anxiety and emotional impact.
Physician opinions on report sharing shifted from 2010 to 2022, from initial dissatisfaction to a gradual appreciation of its benefits.
Most studies focused on patient opinions rather than those of referring physicians and radiologists, whose opinions were found in only 18% and 9% of studies, respectively.

A major problem identified by the researchers is that radiology reports have medical terminology that isn’t easily understood by patients – this can lead to confusion and anxiety.

Communicating findings in plain language could be one solution, but the researchers said little progress has been made due to “resistance from radiologists and entrenched reporting practices.”

Although it wasn’t mentioned by the study authors, generative AI offers one possible solution by using natural language processing algorithms to create patient-friendly versions of clinical reports.

Indeed, patient-facing reports are a major use case for generative AI, with studies already documenting high levels of patient satisfaction.

The Takeaway

Once patients get access to their own reports, it’s impossible to put that genie back in the bottle. Rather than debating whether patients should get radiology reports, the question now should be how radiologists can ensure their reports will be understood without confusion by their ultimate customer – patients.

Tag: radiology reports

RadGPT Simplifies Radiology Reports for Patients

Should Patients Get Their Radiology Reports?

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