Can generative AI help improve healthcare data interoperability?
Researchers from Evanston, Ill.-based Northwestern University think so. They authored a new study that found GPT-4, the large language model employed in ChatGPT, to be effective in translating EHR data into standardized form (known as Fast Healthcare Interoperability Resources, or FHIR).
"This is going to greatly accelerate the pace of breaking down the walls between different health systems that hinder the aggregation of health data and the exchange of the data for performing large-scale research," said Yuan Luo, PhD, chief AI officer at Northwestern's Clinical and Translational Sciences Institute and Institute for Artificial Intelligence in Medicine, in an Aug. 7 statement.
The researchers' FHIR-GPT model had a better match rate for EHR data than existing tools for medication statements, medication timing schedules, medical forms, reasons for medication administration, dose quantities, and medication administration routes, according to the study published July 19 in NEJM AI. The authors say they plan to further validate the tool before it can be adopted by health systems across the U.S.