An AI assistant can interpret those lab results for you

When Judith Miller had routine blood work done in July, she got a phone alert the same day that her lab results were posted online. So, when her doctor messaged her the next day that her overall tests were fine, Miller wrote back to ask about the elevated carbon dioxide and low anion gap listed in the report.

While the 76-year-old Milwaukee resident waited to hear back, Miller did something patients increasingly do when they can’t reach their health care team. She put her test results into Claude and asked the AI assistant to evaluate the data.

“Claude helped give me a clear understanding of the abnormalities,” Miller said. The generative AI model didn’t report anything alarming, so she wasn’t anxious while waiting to hear back from her doctor, she said.

Patients have unprecedented access to their medical records, often through online patient portals such as MyChart, because federal law requires health organisations to immediately release electronic health information, such as notes on doctor visits and test results. A study published in 2023 found that 96% of patients surveyed want immediate access to their records, even if their provider hasn’t reviewed them.

And many patients are using large language models, or LLMs, like OpenAI’s ChatGPT, Anthropic’s Claude, and Google’s Gemini, to interpret their records. That help comes with some risk, though. Physicians and patient advocates warn that AI chatbots can produce wrong answers and that sensitive medical information might not remain private.

Yet, most adults are cautious about AI and health. Fifty-six percent of those who use or interact with AI are not confident that information provided by AI chatbots is accurate, according to a 2024 KFF poll. KFF is a health information nonprofit that includes KFF Health News.

“LLMs are theoretically very powerful and they can give great advice, but they can also give truly terrible advice depending on how they’re prompted,” said Adam Rodman, an internist at Beth Israel Deaconess Medical Center in Massachusetts and the chair of a steering group on generative AI at Harvard Medical School.

Justin Honce, a neuroradiologist at UCHealth in Colorado, said it can be very difficult for patients who are not medically trained to know whether AI chatbots make mistakes.

“Ultimately, it’s just the need for caution overall with LLMs. With the latest models, these concerns are continuing to get less and less of an issue but have not been entirely resolved,” Honce said.

Rodman has seen a surge in AI use among his patients in the past six months. In one case, a patient took a screenshot of his hospital lab results on MyChart then uploaded them to ChatGPT to prepare questions ahead of his appointment. Rodman said he welcomes patients’ showing him how they use AI, and that their research creates an opportunity for discussion.

Roughly 1 in 7 adults over 50 use AI to receive health information, according to a recent poll from the University of Michigan, while 1 in 4 adults under age 30 do so, according to the KFF poll.

Using the internet to advocate for better care for oneself isn’t new. Patients have traditionally used websites such as WebMD, PubMed, or Google to search for the latest research and have sought advice from other patients on social media platforms like Facebook or Reddit. But AI chatbots’ ability to generate personalised recommendations or second opinions in seconds is novel.

Liz Salmi, communications and patient initiatives director at OpenNotes, an academic lab at Beth Israel Deaconess that advocates for transparency in health care, had wondered how good AI is at interpretation, specifically for patients.

In a proof-of-concept study published this year, Salmi and colleagues analysed the accuracy of ChatGPT, Claude, and Gemini responses to patients’ questions about a clinical note. All three AI models performed well, but how patients framed their questions mattered, Salmi said. For example, telling the AI chatbot to take on the persona of a clinician and asking it one question at a time improved the accuracy of its responses.

Privacy is a concern, Salmi said, so it’s critical to remove personal information like your name or Social Security number from prompts. Data goes directly to tech companies that have developed AI models, Rodman said, adding that he is not aware of any that comply with federal privacy law or consider patient safety. Sam Altman, CEO of OpenAI, warned on a podcast last month about putting personal information into ChatGPT.