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      Simple rules for evidence translation in complex systems: A qualitative study

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          Abstract

          Background

          Ensuring patients benefit from the latest medical and technical advances remains a major challenge, with rational-linear and reductionist approaches to translating evidence into practice proving inefficient and ineffective. Complexity thinking, which emphasises interconnectedness and unpredictability, offers insights to inform evidence translation theories and strategies. Drawing on detailed insights into complex micro-systems, this research aimed to advance empirical and theoretical understanding of the reality of making and sustaining improvements in complex healthcare systems.

          Methods

          Using analytical auto-ethnography, including documentary analysis and literature review, we assimilated learning from 5 years of observation of 22 evidence translation projects (UK). We used a grounded theory approach to develop substantive theory and a conceptual framework. Results were interpreted using complexity theory and ‘simple rules’ were identified reflecting the practical strategies that enhanced project progress.

          Results

          The framework for Successful Healthcare Improvement From Translating Evidence in complex systems (SHIFT-Evidence) positions the challenge of evidence translation within the dynamic context of the health system. SHIFT-Evidence is summarised by three strategic principles, namely (1) ‘act scientifically and pragmatically’ – knowledge of existing evidence needs to be combined with knowledge of the unique initial conditions of a system, and interventions need to adapt as the complex system responds and learning emerges about unpredictable effects; (2) ‘embrace complexity’ – evidence-based interventions only work if related practices and processes of care within the complex system are functional, and evidence-translation efforts need to identify and address any problems with usual care, recognising that this typically includes a range of interdependent parts of the system; and (3) ‘engage and empower’ – evidence translation and system navigation requires commitment and insights from staff and patients with experience of the local system, and changes need to align with their motivations and concerns. Twelve associated ‘simple rules’ are presented to provide actionable guidance to support evidence translation and improvement in complex systems.

          Conclusion

          By recognising how agency, interconnectedness and unpredictability influences evidence translation in complex systems, SHIFT-Evidence provides a tool to guide practice and research. The ‘simple rules’ have potential to provide a common platform for academics, practitioners, patients and policymakers to collaborate when intervening to achieve improvements in healthcare.

          Electronic supplementary material

          The online version of this article (10.1186/s12916-018-1076-9) contains supplementary material, which is available to authorized users.

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          Developing and evaluating complex interventions: the new Medical Research Council guidance

          Evaluating complex interventions is complicated. The Medical Research Council's evaluation framework (2000) brought welcome clarity to the task. Now the council has updated its guidance
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                Author and article information

                Contributors
                Julie.reed@imperial.ac.uk
                c.howe@imperial.ac.uk
                c.doyle@imperial.ac.uk
                d.bell@imperial.ac.uk
                Journal
                BMC Med
                BMC Med
                BMC Medicine
                BioMed Central (London )
                1741-7015
                20 June 2018
                20 June 2018
                2018
                : 16
                : 92
                Affiliations
                [1 ]ISNI 0000 0001 2116 3923, GRID grid.451056.3, National Institute of Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) Northwest London, ; Chelsea, London, UK
                [2 ]ISNI 0000 0001 2113 8111, GRID grid.7445.2, Westminster Hospital, Imperial College, ; London, SW10 9NH UK
                Article
                1076
                10.1186/s12916-018-1076-9
                6009041
                29921274
                c59d31b4-12bb-4476-beaa-31d1257eac15
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.

                History
                : 5 February 2018
                : 14 May 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000272, National Institute for Health Research;
                Award ID: CLAHRC NWL
                Award ID: CLAHRC NWL
                Award ID: CLAHRC NWL
                Award ID: CLAHRC NWL
                Award Recipient :
                Funded by: Health Foundation
                Award ID: Improvement Science Fellowship
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2018

                Medicine
                complex systems,complexity theory,complex adaptive systems,framework,evidence translation,implementation,quality improvement

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