Exploring the heterogeneity of factors that may influence implementation of PrEP in family planning clinics: a latent profile analysis

BACKGROUND: Title X-funded family planning clinics have been identified as optimal sites for delivery of pre-exposure prophylaxis (PrEP) for HIV prevention. However, PrEP has not been widely integrated into family planning services, especially in the Southern US, and data suggest there may be significant implementation challenges in this setting. Because Title X clinics vary greatly in provider-, organizational-, and systems-level characteristics, there is likely variation in capacity to implement PrEP across clinics. METHODS: We conducted a survey from February to June 2018 among providers and administrators of non-PrEP-providing Title X-funded clinics across 18 southern states. Survey items were designed using the Consolidated Framework for Implementation Research (CFIR) to assess constructs relevant to PrEP implementation. To explore the heterogeneity of CFIR-related implementation determinants and identify distinct sub-groups of Title X clinics, a latent profile analysis was conducted using nine CFIR constructs: complexity, relative advantage, cost, attitudes, implementation climate, compatibility, leadership engagement, available resources, and cosmopolitanism. We then conducted a multi-level analysis (accounting for nesting of participants within clinics) to test whether group membership was associated with readiness for implementation of PrEP, controlling for key sociodemographic characteristics. RESULTS: Four hundred and fourteen healthcare providers/administrators from 227 non-PrEP-providing Title X clinics participated in the study. We identified six sub-groups of clinics that each had distinct patterns of PrEP implementation determinants. Clinic sub-groups included “Highest Capacity for Implementation”, “Favorable Conditions for Implementation”, “Mixed Implementation Context”, “Neutral Implementation Context”, “Incompatible Setting for Implementation”, and “Resource-Strained Setting”. Group membership was related to numerous provider-level (i.e., ability to prescribe medication) and clinic-level (i.e., provision of primary care) characteristics. In comparison to the “Neutral” group (which held neutral perceptions across the implementation determinants), the “Highest Capacity” and “Favorable Conditions” groups had significantly higher levels of implementation readiness, and the “Resource-Strained” group had a significantly lower level of implementation readiness. CONCLUSIONS: Latent profile analyses can help researchers understand how implementation readiness varies across healthcare settings, promoting tailoring of implementation strategies to unique contexts. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s43058-021-00148-3.