Study of 950,000 US Clinicians Shows Rapid Uptake of AI in Patient Care – Often Beyond Their Own Specialty
Key Takeaways:
- Monthly active users of the AI-enabled clinical information platform OpenEvidence rose from 355 in January 2024 to 703,265 in June 2026, with clinicians in the study submitting 270 million queries.
- Just over half of queries (51.9 per cent) related to clinical decision making, particularly treatment and management, while diagnosis accounted for 13.9 per cent.
- Clinicians often used AI for questions outside their own specialty, and use varied across clinician types, specialties and career stages.
A first look at how clinicians use AI at scale
The first large-scale study of how often clinicians use artificial intelligence (AI) tools in patient care, who those clinicians are and what they use the tools for has found that a significant number of medical practitioners are using AI in the clinic. They are often using it to explore treatment options for their patients in areas outside their clinical specialty.
The study was led by researchers at Harvard Medical School (HMS) and Brigham and Women’s Hospital. It looked at how 950,000 physicians, physician assistants and nurse practitioners in the United States used OpenEvidence, a popular AI-enabled clinical information platform, over the last two and a half years. The results of the federally funded study were published on 15 October in JAMA.
“Two key takeaways are that an enormous number of physicians are using AI for clinical care and that they are often using it in areas where they don’t have specific expertise,” said corresponding author Anupam Jena, the Joseph P. Newhouse Professor of Health Care Policy in the Blavatnik Institute at HMS and HMS professor of medicine at Massachusetts General Hospital.
“Everyone appreciates the huge potential for AI to change how medicine is practiced, but right now we have limited information on how many doctors are using it, what they are using it for, and how it’s impacting patients,” Jena said. The JAMA study tackles the first two of those questions.
Adoption at speed and scale
The researchers found that the increase in use has been dramatic, in terms of both the speed and the scale of adoption, Jena said. That stands in contrast to what research showed with electronic health records, where the pace of adoption was slow and “only really occurred after government regulation,” Jena said.
From January 2024 to June 2026, the number of monthly active OpenEvidence users increased from 355 to 703,265, the team found. Over that time, practitioners included in the study submitted 270 million queries to the platform.
To understand what those queries were about, Jena and colleagues used a large language model to classify the clinical purpose and topic areas of a random sample of 38.8 million queries.
What clinicians are asking AI
Most queries were related to clinical decision making (51.9 per cent), particularly treatment and management. Diagnosis accounted for 13.9 per cent of queries.
The data showed that queries were frequently aimed at aiding treatment decisions rather than diagnostic tasks, and that questions were often about subjects outside the practitioner’s specialty. For example, surgeons often ask questions that are not about surgery, the team found.
How use varies by specialty and career stage
The level of use varied across clinician types, specialties and career stages.
The researchers compared the number of queries made by a particular specialty with the percentage of the physician workforce that specialty represents. Some specialties used more than their share of queries:
- Oncology and haematology specialists accounted for 3.8 per cent of queries, while they make up just 1.9 per cent of the workforce.
- Internal medicine doctors accounted for 27.3 per cent of physician queries, while they make up 14.5 per cent of the physician workforce.
Other specialties, including radiology, orthopaedics and ophthalmology, used less than their share.
More than half of the users in the sample (556,200) were physicians, who submitted an average of 37 queries per month of use. Early-career physicians and those in oncology, haematology, internal medicine and family medicine submitted a higher-than-average share of queries.
What comes next
The study addresses how many clinicians are using AI and what they are using it for, but not how that use affects patients. The next step will be to examine whether use of these tools improves clinical care, the researchers said.
“AI tools have become integrated into routine in clinical practice faster than almost any technology we’ve seen, but until now we’ve had very little data on how clinicians actually use them,” said first author Vishal Patel, HMS clinical fellow in surgery at Brigham and Women’s. “This research gives us an early picture of where these tools fit into clinical decision-making and where we need to study their accuracy and effects on patient care next.”
With AI tools entering routine practice at this pace, knowing how to evaluate and use them safely is becoming part of everyday clinical work – the focus of professional training such as the College of Contemporary Health’s AI Essentials for Primary Care: Tools, Ethics and Everyday Applications, a CPD-accredited online short course.
Study data and disclosures
Three of the co-authors are employees of OpenEvidence, which did not fund the study but provided the de-identified data that was analysed.
CCH insight
This study suggests AI is already part of routine clinical decision making, often in areas beyond a clinician’s own specialty, while questions about accuracy and the effect on patient care are still to be answered. That makes the ability to assess AI tools critically an increasingly important skill.
CCH’s AI Essentials for Primary Care: Tools, Ethics and Everyday Applications CPD short course (3.5 CPD hours, fully online, CPD-accredited) covers how to evaluate AI systems safely, understand accountability and data protection requirements, and give patients clear answers about AI in their care.
Explore AI Essentials for Primary Care →
Source: JAMA
