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In a lot the identical means folks can “chat” with giant language fashions like GPT-4, Stanford Well being Care clinicians can now work together with a affected person’s medical data via an AI-backed software program referred to as ChatEHR.
The know-how, at present in a pilot stage, allows them to ask questions on a affected person’s medical historical past, mechanically summarize charts and carry out different duties. ChatEHR makes use of data from a person’s well being data to offer its response.
“AI can augment the practice of physicians and other health care providers, but it’s not helpful unless it’s embedded in their workflow and the information the algorithm is using is in a medical context,” mentioned Nigam Shah, MBBS, Ph.D., chief information science officer at Stanford Well being Care, who led the workforce in growing the know-how. “ChatEHR is secure; it’s pulling directly from relevant medical data; and it’s built into the electronic medical record system, making it easy and accurate for clinical use.”
The software program has been in improvement since 2023, when a workforce of Stanford Medication researchers led by Shah; Anurang Revri, vice chairman and chief enterprise architect for Stanford Well being Care’s Know-how and Digital Companies; and others acknowledged the potential of enormous language fashions and had been impressed to create one thing helpful for clinicians.
“ChatEHR opens up a new way for clinicians to interact with electronic health records in a more streamlined and efficient manner, whether that’s asking for a summary of the entire chart or retrieving specific data points relevant to the patient’s care,” mentioned Michael Pfeffer, MD, chief data and digital officer for Stanford Well being Care and the College of Medication, who helped lead the event and integration of the software program.
“This is a unique instance of integrating LLM capabilities directly into clinicians’ practice and workflow. We’re thrilled to bring this to the workforce at Stanford Health Care.”
Quicker search, abstract and knowledge gathering
At present, the software program is accessible solely to a small cohort of people at Stanford Hospital—33 physicians, nurses, doctor’s assistants and nurse practitioners—who’re monitoring its efficiency, refining its accuracy and enhancing its utility.
“Making the electronic medical record more user-friendly means physicians can spend less time scouring every nook and cranny of it for the information they need,” mentioned Sneha Jain, MD, a medical assistant professor of drugs who has been an early person of the know-how. “ChatEHR can help them get that information up front so they can spend time on what matters—talking to patients and figuring out what’s going on.”
When clinicians entry the device, they’re greeted with: “Hi, 
I’m ChatEHR! Here to help you securely chat with the patient’s medical record.”
At that time, they’ll sort in a slew of questions concerning the affected person: Does this particular person have any allergy symptoms? What does their newest ldl cholesterol take a look at present? Have that they had a colonoscopy? Have been the outcomes regular?
ChatEHR will not be meant for medical recommendation, Shah mentioned. The software program is an information-gathering device that may expedite the method and, ideally, save time. All choices keep in well being care consultants’ fingers.
Past a single search, ChatEHR can speed up most of the time-consuming duties which are a part of a health care provider’s on a regular basis workload. Jonathan Chen, MD, Ph.D., a hospital doctor and an assistant professor of drugs and of biomedical information sciences, famous that when a affected person involves the emergency room, the admitting physician has to rapidly determine the way to assist them.
“It’s not just the chest pain they’re having in that moment that matters—it’s their whole story, what led up to this moment. All their prior history is relevant. What medications were they on, what side effects did they have, what surgeries took place and how did that affect them?” he mentioned. “It’s a ton of work to go back and find all of that information during a time-sensitive case, so speeding up that process would be a big help.”
He added that ChatEHR could possibly be useful in some switch instances. Sufferers who’re transferred to Stanford Hospital for extra superior care typically arrive with a big packet of data, typically a whole lot of pages lengthy.
“All of that medical history is crucial, but going in cold and sifting through that is a huge lift,” Chen mentioned. “Having ChatEHR boil that down into a relevant summary would make that process smoother.” And, he mentioned, it is not simply high-level summaries that ChatEHR gives—the doctor can even ask probing follow-up questions to higher perceive the affected person’s historical past.
The workforce can also be constructing out one thing they name “automations,” or evaluative duties primarily based on a affected person’s historical past and file. For instance, the workforce has created an automation that may decide whether or not it is applicable to switch a affected person to the Stanford Medication-affiliated Sequoia Hospital affected person care unit, which gives extra affected person rooms.
“That automated evaluation saves us the administrative burden of sifting through patient information and helps us quickly determine if a patient can be transferred, opening access to care here at Stanford Hospital,” Shah mentioned. He and others are engaged on different automations, which might decide eligibility for hospice care, for instance, or suggest extra consideration post-surgery.
Persevering with the rollout
Shah and the workforce will proceed evaluating ChatEHR’s use instances utilizing MedHELM, an open-source, versatile and cost-effective framework for real-world LLM analysis in medication. There are additionally different accuracy-ensuring options which are in improvement, resembling citations that present clinicians the place bits of data got here from throughout the medical file.
Because the know-how develops, the aim is to open ChatEHR to all clinicians who take a look at affected person charts. “We’re rolling this out in accordance with our responsible AI guidelines, not only ensuring accuracy and performance, but making sure we have the educational resources and technical support available to make ChatEHR usable and useful to our workforce,” Shah mentioned.
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Clinicians can ‘chat’ with medical data via new AI software program, ChatEHR (2025, June 6)
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