Abstract
BACKGROUND: It is challenging to identify and understand the specific mechanisms through which an implementation strategy affects implementation outcomes, as implementation happens in the context of complex, multi-level systems. These systems and the mechanisms within each level have their own dynamic environments that change frequently. For instance, sequencing may matter in that a mechanism may only be activated indirectly by a strategy through another mechanism. The dosage or strength of a mechanism may vary over time or across different health care system levels. To elucidate the mechanisms relevant to successful implementation amidst this complexity, systems analysis methods are needed to model and manage complexity. METHODS: The fields of systems engineering and systems science offer methods-which we refer to as systems analysis methods-to help explain the interdependent relationships between and within systems, as well as dynamic changes to systems over time. When applied to studying implementation mechanisms, systems analysis methods can help (i) better identify and manage unknown conditions that may or may not activate mechanisms (both expected mechanisms targeted by a strategy and unexpected mechanisms that the methods help detect) and (ii) flexibly guide strategy adaptations to address contextual influences that emerge after the strategy is selected and used. RESULTS: In this paper, we delineate a structured approach to applying systems analysis methods for examining implementation mechanisms. The approach includes explicit steps for selecting, tailoring, and evaluating an implementation strategy regarding the mechanisms that the strategy is initially hypothesized to activate, as well as additional mechanisms that are identified through the steps. We illustrate the approach using a case example. We then discuss the strengths and limitations of this approach, as well as when these steps might be most appropriate, and suggest work to further the contributions of systems analysis methods to implementation mechanisms research. CONCLUSIONS: Our approach to applying systems analysis methods can encourage more mechanisms research efforts to consider these methods and in turn fuel both (i) rigorous comparisons of these methods to alternative mechanisms research approaches and (ii) an active discourse across the field to better delineate when these methods are appropriate for advancing mechanisms-related knowledge.