Search

Background: Implementing evidence-based practices (EBPs) to increase cancer screenings in safety net primary care systems has great potential for reducing cancer disparities. Yet there is a gap in understanding the factors and mechanisms that influence EBP implementation within these high-priority systems. Guided by the Consolidated Framework for Implementation Research (CFIR), our study aims to fill this gap with a multiple case study of health care safety net systems that were funded by an American Cancer Society (ACS) grants program to increase breast and colorectal cancer screening rates. The initiative funded 68 safety net systems to increase cancer screening through implementation of evidence-based provider and client-oriented strategies.Methods: Data are from a mixed-methods evaluation with nine purposively selected safety net systems. Fifty-two interviews were conducted with project leaders, implementers, and ACS staff. Funded safety net systems were categorized into high-, medium-, and low-performing cases based on the level of EBP implementation. Within- and cross-case analyses were performed to identify CFIR constructs that influenced level of EBP implementation.Results: Of 39 CFIR constructs examined, six distinguished levels of implementation. Two constructs were from the intervention characteristics domain: adaptability and trialability. Three were from the inner setting domain: leadership engagement, tension for change, and access to information and knowledge. Engaging formally appointed internal implementation leaders, from the process domain, also distinguished level of implementation. No constructs from the outer setting or individual characteristics domain differentiated systems by level of implementation.Conclusions: Our study identified a number of influential CFIR constructs and illustrated how they impacted EBP implementation across a variety of safety net systems. Findings may inform future dissemination efforts of EBPs for increasing cancer screening in similar settings. Moreover, our analytic approach is similar to previous case studies using CFIR and hence could facilitate comparisons across studies. [ABSTRACT FROM AUTHOR]