What we know: 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 we will do: In
this optimization trial, we will test the effectiveness of intervention components, alone and in combination, on
new PrEP prescriptions in primary care at HFH. First, we will generate feedback 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, we will test the four intervention components in an optimization trial,
with 16 conditions being implemented at 32 clinics. Finally, we will generate feedback 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. In sum, our team brings a novel, innovative approach,
robust interdisciplinary experience, strong preliminary work in HIV, PrEP, MOST, and primary care, and
scientific rigor to make a significant impact on the field.