A Method for Tracking Implementation Strategies: An Exemplar Implementing Measurement-Based Care in Community Behavioral Health Clinics

Implementation experts suggest tailoring strategies to the intended context may enhance outcomes. However, it remains unclear which strategies are best suited to address specific barriers to implementation, in part because few measurement methods exist that adhere to recommendations for reporting. In the context of a dynamic cluster randomized trial comparing a standardized to tailored approach to implementing measurement-based care (MBC), this study aimed to (a) describe a method for tracking implementation strategies, (b) demonstrate the method by tracking strategies generated by teams tasked with implementing MBC at their clinics in the tailored condition, and (c) conduct preliminary examinations of the relation between strategy use and implementation outcomes (i.e., self-reported fidelity to MBC). The method consisted of a coding form based on Proctor, Powell, and McMillen (2013) implementation strategy reporting guidelines and Powell et al.'s (2012) taxonomy to facilitate specification of the strategies. A trained research specialist coded digitally recorded implementation team meetings. The method allowed for the following characterization of strategy use. Each site generated 39 unique strategies across an average of six meetings in five months. There was little variability in the use of types of implementation strategies across sites with the following order of prevalence: quality management (50.00%), restructuring (16.53%), communication (15.68%), education (8.90%), planning (7.20%), and financing (1.69%). We identified a new category of strategies not captured by the existing taxonomy, labeled communication. There was no evidence that number of implementation strategies enacted was statistically significantly associated with changes in self-reported fidelity to MBC however, financing strategies were associated with increased fidelity. This method has the capacity to yield rich data that will inform investigations into tailored implementation approaches.