More than 37 million in the U.S have diabetes but many don’t receive timely care which can lead to costly, even deadly complications. While effective treatments are available in primary care settings, clinicians lack the tools necessary to identify those patients at the highest risk.
To prevent poor health outcomes, researchers at the University of Houston https://www.uh.edu are developing Primary Care Forecast, a clinical decision support system that uses deep learning to predict which patients are more likely to experience complications.
The first tool to be developed within the AI system is the Diabetes Complication Severity Index (DCSI) Progression Tool, which in addition to a patient’s health history, considers how their social and environment circumstances, employment status, living arrangement, education level, and food security could increase their risk for complications,-
Funded by the American Board of Family Medicine https://www.theabfm.org, the DCSI Progression tool will provide clinicians with timely, actionable insights so they can intervene early, reduce the percentage of individuals with diabetes who have complications, and lower the number of complications affecting each patient.
“Our long time goal is to help clinicians become more proactive and less reactive when treating diabetes. By leveraging the capabilities of AI and ML, we can more effectively connect at risk individuals with interventions before they become sicker,” said Dr. Winston Liaw, PI of the Project, and Chair, Department of Health Systems and Population Health Sciences at the Tilman J. Fertitta Family College of Medicine.
The DCSI Progression Tool will be developed in collaboration with the Humana Integrated Health System Sciences Institute at the University of Houston and leverage unique data sets from Humana Inc. to include claims, health records, along with individual and community social risk factors. The tool will be tested within the PRIME Registry, a national platform that includes millions of primary care patients nationwide.