UChicago Medicine recently created an application in Epic that has been rolled out across the health system's EHR — and could soon become part of Epic EHRs everywhere.
The automated diagnosis, or AutoDx, feature automatically populates patients' conditions and risk factors into the EHR's note template, helping clinicians not overlook important details and reducing coding queries, according to Cheng-Kai Kao, MD, chief medical information officer of UChicago Medicine.
"We strive to leverage technology to improve care quality and reduce clinician burnout," Dr. Kao told Becker's. "It's exciting to see something created at UChicago generating interest from several other institutions. We may even see a similar feature in future versions of Epic. We are happy to see how this work helps other institutions alleviate the documentation burden."
Matthew Cerasale, MD, outcomes quality director at UChicago Medicine, was the physician builder who originally designed AutoDx. The module initially started with three diagnoses and has evolved to comprise 15. Drs. Cerasale, Kao and their colleagues published a paper on the tool in late June in Applied Clinical Informatics. The platform has been adopted by clinicians across the health system, from its pediatric and community hospitals to its hospital-at-home program, Dr. Cerasale said.
Dr. Kao explained how it works: "Instead of the provider needing to remember everything to document in the chart, these patient-specific diagnoses are now automatically populated in the notes. Providers have the option to delete them if they disagree, but the tool has been very accurate in generating appropriate diagnoses based on thoughtfully crafted logic. These risk factors are crucial for coding and billing, external rankings, quality reporting, and other statistics that many institutions, including ours, care about.
"So for example, when our provider opens the note template for a patient, if the patient has obesity, the diagnosis of obesity will show up in the note along with BMI and the severity of the obesity."
After presenting this work at the Epic Users Group Meeting, several health systems reached out to UChicago Medicine, expressing interest in using it themselves. They will soon have the opportunity to do so, Dr. Kao said.