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      A systems approach to scale-up for population health improvement

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      1 , , 2
      Health Research Policy and Systems
      BioMed Central
      Systems, Scale-up, Public health, Global health, Implementation

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          Abstract

          Despite a number of important global public health successes, for many health behaviours there is a continued lack of interventions that have been sufficiently scaled up to achieve system-wide integration. This has limited sustainable and equitable population health improvement. Systems change plays a major role in the relation between implementation processes and at-scale institutionalisation of public health interventions. However, in research, systems approaches remain underutilised in scaling up. Public health scale-up models have typically centred on intervention replication through linear expansion. In this paper, we discuss current conceptualisations and approaches used when scaling up in public health, and propose a new perspective on scaling that shifts attention away from the intervention to focus instead on achieving the desired population-level health outcomes. In our view, ‘scaling up’ exists on a continuum. At one end, effective scaling can involve a linear, intervention-orientated expansive approach that prioritises the spread of evidence-based interventions into existing systems in order to drive expansion in the application of that intervention. At the other end, we contend that scale-up can sit within a complex systems paradigm in which interventions are conceptualised as events in systems. In this case, implementation and scale-up activities should focus on generating changes within the system itself to achieve the desired outcome. This we refer to as ‘systems-orientated scale-up’ to achieving population health improvement, which can complement traditional approaches in relevant situations. We argue that for some health behaviours, our proposed approach towards scaling up could enhance intervention implementation, sustainability and population health impact.

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          Most cited references20

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          Diffusion of innovations in service organizations: systematic review and recommendations.

          This article summarizes an extensive literature review addressing the question, How can we spread and sustain innovations in health service delivery and organization? It considers both content (defining and measuring the diffusion of innovation in organizations) and process (reviewing the literature in a systematic and reproducible way). This article discusses (1) a parsimonious and evidence-based model for considering the diffusion of innovations in health service organizations, (2) clear knowledge gaps where further research should be focused, and (3) a robust and transferable methodology for systematically reviewing health service policy and management. Both the model and the method should be tested more widely in a range of contexts.
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            The pandemic of physical inactivity: global action for public health.

            Physical inactivity is the fourth leading cause of death worldwide. We summarise present global efforts to counteract this problem and point the way forward to address the pandemic of physical inactivity. Although evidence for the benefits of physical activity for health has been available since the 1950s, promotion to improve the health of populations has lagged in relation to the available evidence and has only recently developed an identifiable infrastructure, including efforts in planning, policy, leadership and advocacy, workforce training and development, and monitoring and surveillance. The reasons for this late start are myriad, multifactorial, and complex. This infrastructure should continue to be formed, intersectoral approaches are essential to advance, and advocacy remains a key pillar. Although there is a need to build global capacity based on the present foundations, a systems approach that focuses on populations and the complex interactions among the correlates of physical inactivity, rather than solely a behavioural science approach focusing on individuals, is the way forward to increase physical activity worldwide.
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              When complexity science meets implementation science: a theoretical and empirical analysis of systems change

              Background Implementation science has a core aim – to get evidence into practice. Early in the evidence-based medicine movement, this task was construed in linear terms, wherein the knowledge pipeline moved from evidence created in the laboratory through to clinical trials and, finally, via new tests, drugs, equipment, or procedures, into clinical practice. We now know that this straight-line thinking was naïve at best, and little more than an idealization, with multiple fractures appearing in the pipeline. Discussion The knowledge pipeline derives from a mechanistic and linear approach to science, which, while delivering huge advances in medicine over the last two centuries, is limited in its application to complex social systems such as healthcare. Instead, complexity science, a theoretical approach to understanding interconnections among agents and how they give rise to emergent, dynamic, systems-level behaviors, represents an increasingly useful conceptual framework for change. Herein, we discuss what implementation science can learn from complexity science, and tease out some of the properties of healthcare systems that enable or constrain the goals we have for better, more effective, more evidence-based care. Two Australian examples, one largely top-down, predicated on applying new standards across the country, and the other largely bottom-up, adopting medical emergency teams in over 200 hospitals, provide empirical support for a complexity-informed approach to implementation. The key lessons are that change can be stimulated in many ways, but a triggering mechanism is needed, such as legislation or widespread stakeholder agreement; that feedback loops are crucial to continue change momentum; that extended sweeps of time are involved, typically much longer than believed at the outset; and that taking a systems-informed, complexity approach, having regard for existing networks and socio-technical characteristics, is beneficial. Conclusion Construing healthcare as a complex adaptive system implies that getting evidence into routine practice through a step-by-step model is not feasible. Complexity science forces us to consider the dynamic properties of systems and the varying characteristics that are deeply enmeshed in social practices, whilst indicating that multiple forces, variables, and influences must be factored into any change process, and that unpredictability and uncertainty are normal properties of multi-part, intricate systems.
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                Author and article information

                Contributors
                h.koorts@deakin.edu.au
                Journal
                Health Res Policy Syst
                Health Res Policy Syst
                Health Research Policy and Systems
                BioMed Central (London )
                1478-4505
                1 March 2021
                1 March 2021
                2021
                : 19
                : 27
                Affiliations
                [1 ]GRID grid.1021.2, ISNI 0000 0001 0526 7079, School of Exercise and Nutrition Sciences, Institute for Physical Activity and Nutrition (IPAN), , Deakin University, ; 221 Burwood Highway, Burwood, VIC 3125 Australia
                [2 ]GRID grid.7340.0, ISNI 0000 0001 2162 1699, Department of Social and Policy Sciences, , University of Bath, ; Claverton Down, Bath, United Kingdom
                Author information
                http://orcid.org/0000-0003-1303-6064
                Article
                679
                10.1186/s12961-021-00679-0
                7919988
                33648525
                a1fca6dc-b83f-4f0e-98c6-27619164d272
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 4 August 2020
                : 18 January 2021
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                © The Author(s) 2021

                Health & Social care
                systems,scale-up,public health,global health,implementation
                Health & Social care
                systems, scale-up, public health, global health, implementation

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