A Multilevel, Multiphase Optimization Strategy for PrEP (MOST:PrEP)

Overview

What is known: There are 1.2 million people in the US who meet the indications for PrEP; yet, disparities exist in uptake. For example, only 9% of Black and 16% of Latino individuals, compared to 65% of White individuals, have been prescribed PrEP. At Henry Ford Health (HFH) system, only 10% of eligible patients have been prescribed PrEP. Primary care is an ideal setting for PrEP to be offered as an HIV prevention method since providers see large numbers of patients who are HIV negative, with some who are at increased risk for HIV, and the primary care setting is often the point of entry to the healthcare system. The multiphase optimization strategy (MOST) framework is a novel, innovative way to identify an efficient intervention. What will be done: In this optimization trial, the investigators will test the effectiveness of intervention components, alone and in combination, on new PrEP prescriptions in primary care at HFH. First, feedback will be generated on context-specific (system and individual level) factors for intervention component delivery via focus groups with providers (n=15) and patients eligible for PrEP (n=30). Then, four intervention components will be tested in an optimization trial, with 16 conditions being implemented at 32 clinics. Finally, feedback will be generated on the factors that affected implementation via semi-structured interviews with providers (n=30) and patients (n=30). Participants will be primary care providers (PCPs) and patients eligible for PrEP in Henry Ford Health System. Clinics will be randomized (yes/no) to receive any combination of provider and patient intervention components. Provider intervention components include computer-based simulation training and/or best practice alerts delivered via the electronic health record (EHR). Patient intervention components include HIV risk assessment and/or PrEP informational video - both delivered via the EHR. Primary outcome is the rate of new PrEP prescriptions at the clinic level. Secondary outcomes will include PrEP maintenance, number of HIV tests ordered by a PCP, and number of PCPs trained. Sub analyses will test which factors moderate (e.g., patient sex, race, age, gender, sexual orientation) or mediate (e.g., perceived HIV risk, provider and patient PrEP knowledge) PrEP uptake, focusing on priority populations and disparities in rates of PrEP prescription. Implications: 1) Understanding which intervention components lead to increased PrEP prescriptions will represent an important advance in HIV prevention efforts. 2) Optimizing a multi-level intervention for providers and patients to increase PrEP prescriptions would lead to a new, efficient, evidence-based option. 3) Determining what factors are related to PrEP uptake will help reduce disparities in PrEP initiation among those most in need. 4) Understanding the context specific factors related to intervention component implementation will help identify best methods for replication/adaptation in other healthcare systems.