Optimizing EHR-Based Prediction Models to Improve HIV Preexposure Prophylaxis Use in Community Health Centers

Scale-up of HIV preexposure prophylaxis (PrEP) is a key strategy of the federal initiative to end the HIV epidemic. However, healthcare providers lack tools to identify patients who are at increased risk for HIV infection and thus likely to benefit from PrEP. This pilot study will test the hypothesis that an electronic health record (EHR)-based clinical decision support system that incorporates an HIV risk prediction model can help providers identify patients at increased risk for HIV infection and improve PrEP prescribing in safety-net community health centers. The clinical decision support system will be implemented in the EHR at 2-3intervention clinics, while 2 control clinics will receive standard of care. The primary outcome is PrEP prescriptions. Other key metrics of PrEP-related care to be assessed include medication persistence, adherence to monitoring guidelines for PrEP, and rates of HIV/STI testing and diagnoses. The expected outcome is the foundation for a large-scale cluster randomized trial to test whether EHR-based clinical decision support tools for PrEP can improve PrEP prescribing and prevent new HIV infections in a national network of community health centers.