UF College of Nursing faculty member Hwayoung Cho, PhD, along with Yiyang Liu, MPH, PhD, of the College of Public Health and Health Professions, recently received a $683,625 NIH grant for a three-year study into developing an HIV risk prediction model that can detect women with a higher risk of HIV and translating it into a clinical decision support, or CDS, platform integrated into an EHR system.
The study, funded by the National Institute of Mental Health, is titled: “AI-based Clinical decision support to idenTify wOmeN for HIV testing and PrEP in Florida (ACTION-HIV).”
Investigators hope to use artificial intelligence and real-world big data to develop the women-specific HIV risk prediction CDS tool. Once integrated into an EHR system, the HIV risk prediction CDS will produce automated recommendations for HIV screening and HIV prevention medication (pre-exposure prophylaxis: PrEP) based on patient information entered into the system in primary care settings. The innovative EHR-based CDS tool will have a potentially significant impact on increasing HIV testing, reducing sex disparity in PrEP uptake, and decreasing new HIV infections in Florida.
Research reported in this publication was supported by the National Institute of Mental Health of the National Institutes of Health under Award Number R34MH135768. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health
Co-investigators for this three-year study include Mattia Prosperi and Robert Cook, College of Public Health and Health Professions, Ramzi Salloum and Yonghui Wu, College of Medicine, and Khoa Nguyen, College of Pharmacy.