Pre-exposure prophylaxis, or PrEP, is a highly effective biomedical intervention to prevent HIV acquisition among at risk populations. PrEP offers an individual-controlled prevention method that is effective and safe. From 2014 to 2016, only 2% of women who have indication for PrEP received a prescription. Known individual level barriers to PrEP uptake among women include low rates of PrEP knowledge, low perceived risk of HIV acquisition, and barriers around how and where to access PrEP. Identification of women who may be at increased risk for HIV by healthcare systems is a key public health intervention that has potential to reduce new HIV infections. This study seeks to refine the automation of identification of PrEP-eligible cis-gender women using the electronic medical record system and other electronic open source and geospatial data through identifying commonalities among women newly diagnosed with HIV. As current quantitative indicators perform suboptimally, we will seek to establish commonalities among women with recent HIV infection to refine performance of the model. Using the Consolidated Framework for Implementation Research (CFIR), we will develop an implementation plan for utilization of the refined automated identification of HIV-negative, PrEP- eligible women in the emergency department. Improving identification of PrEP-eligible HIV-negative women in an emergency medical setting will likely influence uptake and is a low-cost, innovative solution to identification of potential PrEP-users. As strategies to increase PrEP uptake among women are under-studied, it is important to refine approaches for optimal performance.
Cis-gender women at risk for HIV are disproportionately under-represented among PrEP users. Current automated methods for identifying PrEP candidates perform suboptimally among women. This study seeks to refine the automation of identification of PrEP-eligible cis-gender women using electronic medical records and other electronic social and structural data by identifying commonalities among women newly diagnosed with HIV.
