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."
Beyond a single search, ChatEHR can accelerate many of the time-consuming tasks that are part of a doctor's everyday workload. Jonathan Chen, MD, PhD, a hospital physician and an assistant professor of medicine and of biomedical data sciences, noted that when a patient comes to the emergency room, the admitting doctor has to quickly figure out how to help 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 said. "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 be helpful in some transfer cases. Patients who are transferred to Stanford Hospital for more advanced care generally arrive with a large packet of information, sometimes hundreds of pages long. "All of that medical history is crucial, but going in cold and sifting through that is a huge lift," Chen said. "Having ChatEHR boil that down into a relevant summary would make that process smoother." And, he said, it's not just high-level summaries that ChatEHR provides, the physician can also ask probing follow-up questions to better understand the patient's history.
The team is also building out something they call "automations," or evaluative tasks based on a patient's history and record. For example, the team has created an automation that can determine whether it's appropriate to transfer a patient to the Stanford Medicine-affiliated Sequoia Hospital patient care unit, which offers more patient 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 said. He and others are working on other automations, which would determine eligibility for hospice care, for example, or recommend additional attention post-surgery.
Continuing the rollout
Shah and the team will continue evaluating ChatEHR's use cases using MedHELM, an open-source, flexible, and cost-effective framework for real-world LLM evaluation in medicine. There are also other accuracy-ensuring features that are in development, such as citations that show clinicians where bits of information came from within the medical record.
As the technology develops, the goal is to open ChatEHR to all clinicians who look at patient 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 said.
