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

Overview of attention for article published in BMC Medicine, June 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

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201 X users
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Title
Simple rules for evidence translation in complex systems: A qualitative study
Published in
BMC Medicine, June 2018
DOI 10.1186/s12916-018-1076-9
Pubmed ID
Authors

Julie E. Reed, Cathy Howe, Cathal Doyle, Derek Bell

Abstract

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. 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. 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. 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.

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X Demographics

The data shown below were collected from the profiles of 201 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 281 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 281 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 42 15%
Researcher 41 15%
Student > Master 28 10%
Student > Doctoral Student 25 9%
Other 18 6%
Other 58 21%
Unknown 69 25%
Readers by discipline Count As %
Medicine and Dentistry 64 23%
Nursing and Health Professions 35 12%
Social Sciences 34 12%
Business, Management and Accounting 12 4%
Psychology 12 4%
Other 44 16%
Unknown 80 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 129. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 November 2023.
All research outputs
#327,187
of 25,639,676 outputs
Outputs from BMC Medicine
#270
of 4,066 outputs
Outputs of similar age
#7,058
of 342,252 outputs
Outputs of similar age from BMC Medicine
#8
of 59 outputs
Altmetric has tracked 25,639,676 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,066 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 45.1. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 342,252 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.