ArticleImplementation science : IS2024
How does the external context affect an implementation processes? A qualitative study investigating the impact of macro-level variables on the implementation of goal-oriented primary care.
Article in Implementation science : IS, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Investigating the implementation of infection prevention and control practices in neonatal care across country income levels: a systematic review.Antimicrobial resistance and infection control · 2025Pooled it
- Rethinking qualitative inquiry in implementation science: clarifying purpose, design, and rigor.Implementation science : IS · 2026Article
- Sustaining values-driven innovation in primary healthcare: a protocol for identifying implementation strategies for long-term impact (longitudinal participatory study).Implementation science communications · 2026Article
- Dimensions of Health System Performance Assessment: A Scoping Review.Iranian journal of public health · 2025Review
- Article
- Primary Care Academy: lessons learned from a large-scale innovative primary care project.Frontiers in public health · 2024Article
- Organization Theory for Implementation Science (OTIS): reflections and recommendations.Frontiers in health services · 2024Article
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Authors and funding
6 authors.
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Abstract
backgroundAlthough the importance of context in implementation science is not disputed, knowledge about the actual impact of external context variables on implementation processes remains rather fragmented. Current frameworks, models, and studies merely describe macro-level barriers and facilitators, without acknowledging their dynamic character and how they impact and steer implementation. Including organizational theories in implementation frameworks could be a way of tackling this problem. In this study, we therefore investigate how organizational theories can contribute to our understanding of the ways in which external context variables shape implementation processes. We use the implementation process of goal-oriented primary care in Belgium as a case.
methodsA qualitative study using in-depth semi-structured interviews was conducted with actors from a variety of primary care organizations. Data was collected and analyzed with an iterative approach. We assessed the potential of four organizational theories to enrich our understanding of the impact of external context variables on implementation processes. The organizational theories assessed are as follows: institutional theory, resource dependency theory, network theory, and contingency theory. Data analysis was based on a combination of inductive and deductive thematic analysis techniques using NVivo 12.
resultsInstitutional theory helps to understand mechanisms that steer and facilitate the implementation of goal-oriented care through regulatory and policy measures. For example, the Flemish government issued policy for facilitating more integrated, person-centered care by means of newly created institutions, incentives, expectations, and other regulatory factors. The three other organizational theories describe both counteracting or reinforcing mechanisms. The financial system hampers interprofessional collaboration, which is key for GOC. Networks between primary care providers and health and/or social care organizations on the one hand facilitate GOC, while on the other hand, technology to support interprofessional collaboration is lacking. Contingent variables such as the aging population and increasing workload and complexity within primary care create circumstances in which GOC is presented as a possible answer.
conclusionsInsights and propositions that derive from organizational theories can be utilized to expand our knowledge on how external context variables affect implementation processes. These insights can be combined with or integrated into existing implementation frameworks and models to increase their explanatory power.
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