Background: Successful implementation of evidence is challenging and commonly not sustained overtime. RCT methods are often unable to provide conclusive evidence of effective implementation strategies because of individual case context heterogeneity. Complimentary process evaluations provide information to explain trial results. Complexity Theory applied to the social context of healthcare may provide better explanations of the implementation context when viewed as a complex adaptive system. Qualitative Comparative Analysis (QCA) methodology offers a different approach to synthesising process evaluation findings with their trial outcome. This case-based method can evaluate common patterns of implicating implementation factors that arise across individual cases e.g. NHS organisations. Different configurations of factors provide greater explanatory power when assessing complex system behaviour in healthcare contexts. The methodological structure of QCA provides an opportunity to systematically connect theory with data to account for the heterogenous implementation context in individual cases. This is demonstrated by using the output of high-quality trial and process evaluation that evaluated implementation strategies to implement a guideline in NHS organisations.
Aim: To operationalise Complexity Theory concepts using QCA methodology to explain the context of implementation of evidence (fasting before surgery guidance).
Methods: Three empirical studies, included:
I. Building a novel conceptual framework with concepts drawn from social Complexity Theory texts and systematically identified implementation theories and frameworks.
II. Conducting a systematic review of QCA studies in healthcare.
III. Evaluating QCA methods with a complexity lens, first by process tracing outcome and process data from an implementation trial to differentiate the different causal pathways for each NHS organisation.
Findings:
I. Five simplified social Complex Adaptive Systems (CAS) concepts include: ‘Interaction’, ‘Self-organisation’, ‘Emergence’, ‘History’ and ‘Temporality’. The novel conceptual framework for implementation research includes three additional concepts: ‘Individual agent’, ‘Interaction’, ‘Self organisation’, ‘Emergence’, ‘History’, ‘Temporality’, ‘System Organising Principle’, and ‘Innovation’.
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II. Nineteen QCA studies (1987-2015) showed variable quality with authors selecting QCA to explain data complexity. A further 32 QCA studies (2015-2019) indicate increasing use and improvements in application.
III. Final QCA models covering 16 NHS organisations suggest fasting practice improvements were a function of all five of the final social CAS informed conditions. This required engagement of leading individuals, micro-systems, policy dissemination, targeted activities and the ability to override the system imperative to manage the operating list.
Conclusion: QCA methods using a Complexity Theory informed conceptual framework indicates the potential for systematic exploration of trial and process data to explain inconclusive findings and heterogeneity of the individual NHS organisation contexts. QCA can expose condition and outcome patterns that vary across NHS organisations by operationalising social Complex Adaptive Systems concepts. Adopting this systems approach to implementation research aids explanation of the implementation context. This thesis presents a novel conceptual framework for implementation research facilitated by a synthesis method of increasing interest in health, and illustrates an exemplar to systematically assess trial outcome and process findings.
Recommendations
When adopting a complex adaptive systems perspective to understand implementation processes and events within social healthcare systems, Qualitative Comparative Analysis (QCA) methods provide a methodological device to expose causally complex process steps. As an addition, to the healthcare methods toolbox alongside other more typical evidence-based methods QCA counterbalances the over-simplification of trial designs. QCA explanatory models use the logic of sets based on necessity and sufficiency of causal conditions to derive complex causal associations between them. This approach manages factor complexity and case context sensitivity. Direct engagement with theory to provide explanations of what happened and why to inform future implementation projects was enabled by this method. Future development requires standards for both conduct and reporting of QCA. These standards should also focus on application in the health and implementation research context. This is to take account of the demand for rigour and validation in evidence-based research in health sciences.