The application of implementation science theories for population health: A critical interpretive synthesis.

background and purposeOver the last decade, the field of implementation science (IS) has yielded an array of theoretical approaches to clarify and understand how factors influence the application and scaling-up of evidence-based practice in health care. These developments have led to questions about whether IS theories and frameworks might be of value to population health researchers and decision makers. The purpose of this research was to conduct a critical interpretive synthesis to explore, if, and how, key IS theories and frameworks might inform population health interventions aimed at reducing the burden of illness across populations.

methodsAn initial list of theories and frameworks was developed based on previous published research and narrowed to focus on theories considered as formative for the field of IS. A standardized data extraction form was used to gather key features of the theories and critically appraise their relevance to population health interventions.

resultsTen theories were included in the review and six deemed most applicable to population health based on their consideration of broader contextual and system-level factors. The remaining four were determined to have less relevant components for population health due to their limited consideration of macro-level factors, often focusing on micro (individual) and meso (organizational) level factors.

conclusionsTheories and frameworks are important to guide the implementation and sustainability of population health interventions. The articulation of meso level factors common in IS theories may be of value to interventions targeted at the population level. However, some of the reviewed theories were limited in their consideration of broader contextual factors at the macro level (community, policy or societal). This critical interpretive synthesis also found that some theories lacked provision of practical guidance to address interventions targeting structural factors such as key social determinants of health (e.g., housing, income).