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How to optimise public health interventions: a scoping review of guidance from optimisation process frameworks
BACKGROUND: Optimisation processes have the potential to rapidly improve the impact of health interventions. Optimisation can be defined as a deliberate, iterative and data-driven process to improve a health intervention and/or its implementation to meet stakeholder-defined public health impacts wit...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7709329/ https://www.ncbi.nlm.nih.gov/pubmed/33267844 http://dx.doi.org/10.1186/s12889-020-09950-5 |
Sumario: | BACKGROUND: Optimisation processes have the potential to rapidly improve the impact of health interventions. Optimisation can be defined as a deliberate, iterative and data-driven process to improve a health intervention and/or its implementation to meet stakeholder-defined public health impacts within resource constraints. This study aimed to identify frameworks used to optimise the impact of health interventions and/or their implementation, and characterise the key concepts, steps or processes of identified frameworks. METHODS: A scoping review of MEDLINE, CINAL, PsycINFO, and ProQuest Nursing & Allied Health Source databases was undertaken. Two reviewers independently coded the key concepts, steps or processes involved in each frameworks, and identified if it was a framework aimed to optimise interventions or their implementation. Two review authors then identified the common steps across included frameworks. RESULTS: Twenty optimisation frameworks were identified. Eight frameworks were for optimising interventions, 11 for optimising implementation and one covered both intervention and implementation optimisation. The mean number of steps within the frameworks was six (range 3–9). Almost half (n = 8) could be classified as both linear and cyclic frameworks, indicating that some steps may occur multiple times in a single framework. Two meta-frameworks are proposed, one for intervention optimisation and one for implementation strategy optimisation. Steps for intervention optimisation are: Problem identification; Preparation; Theoretical/Literature base; Pilot/Feasibility testing; Optimisation; Evaluation; and Long-term implementation. Steps for implementation strategy optimisation are: Problem identification; Collaborate; Plan/design; Pilot; Do/change; Study/evaluate/check; Act; Sustain/endure; and Disseminate/extend. CONCLUSIONS: This review provides a useful summary of the common steps followed to optimise a public health intervention or its implementation according to established frameworks. Further opportunities to study and/or validate such frameworks and their impact on improving outcomes exist. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-020-09950-5. |
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