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

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

doi:10.1186/s12916-018-1076-9

Abstract

BackgroundEnsuring 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.MethodsUsing 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.ResultsThe 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.ConclusionBy 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.

Highlights

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
The results demonstrate how the theory and rules emerged from the empirical data and how understanding is enhanced by application of a complex systems lens
The presentation of the rules and substantive theory is accompanied by two illustrative case examples from CLAHRC North West London (NWL) projects to bring to life the practical reality of evidence translation

Summary

Introduction

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. There is an urgent need to improve the delivery of high quality healthcare, including the need to improve patient safety and reduce harm [1,2,3], to ensure care is patient centred and compassionate [4, 5], to improve health and wellbeing [6], and to reduce inequalities at the local, regional, national and global scale [7,8,9], all within an increasingly constrained financial environment [10, 11] To address these challenges, there is a need to bridge the gap between the production of research evidence and the consistent delivery of evidence-based care in routine practice [12,13,14,15]. Studies tend to be conducted in controlled environments, where interference from context variables is considered problematic and controlled for by randomisation and protocol design [17]

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