CFIR simplified: Pragmatic application of and adaptations to the Consolidated Framework for Implementation Research (CFIR) for evaluation of a patient‐centered care transformation within a learning health system

INTRODUCTION: The Consolidated Framework for Implementation Research (CFIR) is a commonly used implementation science framework to facilitate design, evaluation, and implementation of evidence‐based interventions. Its comprehensiveness is an asset for considering facilitators and barriers to implementation and also makes the framework cumbersome to use. We describe adaptations we made to CFIR to simplify its pragmatic application, for use in a learning health system context, in the evaluation of a complex patient‐centered care transformation. METHODS: We conducted a qualitative study and structured our evaluation questions, data collection methods, analysis, and reporting around CFIR. We collected qualitative data via semi‐structured interviews and observations with key stakeholders throughout. We identified and documented adaptations to CFIR throughout the evaluation process. RESULTS: We analyzed semi‐structured interviews with key stakeholders (n = 23) from clinical observations (n = 5). We made three key adaptations to CFIR: (a) promoted “patient needs and resources,” a subconstruct of the outer setting, to its own domain within CFIR during data analysis; (b) divided the “inner setting” domain into three layers that account for the hierarchy of health care systems (i. pilot clinic, ii. peer clinics, and iii. overarching health care system); and (c) tailored several construct definitions to fit a patient‐centered, primary care setting. Analysis yielded qualitative findings concentrated in the CFIR domains “intervention characteristics” and “outer setting,” with a robust number of findings in the new domain “patient needs and resources.” CONCLUSIONS: To make CFIR more accessible and relevant for wider use in the context of patient‐centered care transformations within a learning health system, a few adaptations are key. Specifically, we found success by teasing apart interactions across the inner layers of a health system, tailoring construct definitions, and placing additional focus on patient needs.