Predictive Analytics and Clinical Decision Support to Improve PrEP Prescribing

Scale-up of HIV preexposure prophylaxis (PrEP) is a key strategy of the U.S. initiative to end the HIV epidemic, but healthcare providers lack tools to support PrEP discussions and prescribing for patients likely to benefit. This research will evaluate whether integrating automated tools into electronic health records to help providers efficiently and equitably identify potential candidates for PrEP, discuss PrEP, and prescribe PrEP can improve PrEP initiation and persistence in safety-net community health centers. It will achieve this by conducting a stepped-wedge trial of a decision support tool with an embedded HIV prediction model to identify patients likely to benefit from PrEP. The intervention will be delivered to healthcare providers in 16 community health centers within the national OCHIN network.

Inclusion Criteria: * Delivery site saw at least 500 distinct patients in 2024 during in-person or telehealth visits * Delivery site had at least 10 new HIV diagnoses or positive HIV screening tests in 2023 * Delivery site provides primary care other than pediatrics, and the primary care department(s) were active on OCHIN Epic as of 1/1/2023 Exclusion Criteria: * Delivery site specializing in HIV or STI care * Correctional facilities * Mobile sites * School-based health center sites