A streamlined approach to classifying and tailoring implementation strategies: recommendations to speed the...

Implementation science emerged from the recognized need to speed the translation of effective interventions into practice. In the US, the science has evolved to place an ever-increasing focus on implementation strategies. The long list of implementation strategies, terminology used to name strategies, and time required to tailor strategies all may contribute to delays in translating evidence-based interventions (EBIs) into practice. To speed EBI translation, we propose a streamlined approach to classifying and tailoring implementation strategies.

A multidisciplinary team of eight scholars conducted an exercise to sort the Expert Recommendations for Implementing Change (ERIC) strategies into three classes: implementation processes (n = 25), capacity-building strategies (n = 20), and integration strategies (n = 28). Implementation processes comprise best practices that apply across EBIs and throughout the phases of implementation from exploration through sustainment (e.g., conduct local needs assessment). Capacity-building strategies target either general or EBI-specific knowledge and skills (e.g., conduct educational meetings). Integration strategies include "methods and techniques" that target barriers or facilitators to implementation of a specific EBI beyond those targeted by capacity building. Building on these three classes, the team collaboratively developed recommendations for a pragmatic, five-step approach that begins with the implementation processes and capacity-building strategies practice-settings are already using prior to tailoring integration strategies. A case study is provided to illustrate use of the five-step approach to tailor the strategies needed to implement a transitional care intervention in skilled nursing facilities.

Our proposed approach streamlines the formative work required prior to implementing an EBI by building on practice partner preferences, expertise, and infrastructure while also making the most of prior research findings.