Application status of the CFIR-ERIC matching tool in healthcare context: a scoping review

The CFIR-ERIC matching tool, developed by Waltz et al. in 2019 to integrate implementation strategies with theoretical frameworks, enables rapid and targeted generation of implementation strategies in healthcare. However, no comprehensive synthesis of its application exists. This scoping review addresses this gap to inform tool optimization and implementation science advancement.

Following the Joanna Briggs Institute scoping review methodology and PRISMA-ScR guidelines, we searched eight databases (PubMed, Embase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP, and SinoMed) for studies applying the CFIR-ERIC matching tool in healthcare (April 29, 2019, to February 8, 2025). Data on application purpose, process, advantages, and limitations were extracted and analyzed via descriptive and content analysis.

A total of 53 studies were included. The tool was mainly used to efficiently formulate targeted implementation strategies (51/53, 96.23%) and primarily applied in clinical intervention improvement (25/53, 47.17%). Regarding the tool's five-step application process, all 51 strategy-generating studies completed the first two steps (barrier identification and strategy generation), while only 50.98% (26/51) further adjusted, 15.69% (8/51) validated, and 7.84% (4/51) evaluated the generated strategies. Commonly reported advantages included providing a structured process for strategy matching (14/53, 26.42%) and references for generating targeted strategies (13/53, 24.53%). Key challenges were the need for context-specific adaptation (13/53, 24.53%) and inherent subjective bias from expert consensus reliance (9/53, 16.98%). Additionally, four studies (7.55%) proposed suggestions for tool refinements.

This review is the first to map the CFIR-ERIC matching tool's application in healthcare, confirming its significant potential and notable strengths in implementation research. Although efforts to update and revise the tool remain limited, there are some approaches offer promising directions for optimization. Future research should focus on leveraging the tool's strengths while addressing its limitations to advance implementation science and improve global healthcare delivery efficiency and quality.

Open Science Framework, https://doi.org/10.17605/OSF.IO/PE2QD .