Abstract
BackgroundImplementation research is increasingly being recognised for optimising the outcomes of clinical practice. Frequently, the benefits of new evidence are not implemented due to the difficulties applying traditional research methodologies to implementation settings. Randomised controlled trials are not always practical for the implementation phase of knowledge transfer, as differences between individual and organisational readiness for change combined with small sample sizes can lead to imbalances in factors that impede or facilitate change between intervention and control groups. Within-cluster repeated measure designs could control for variance between intervention and control groups by allowing the same clusters to receive a sequence of conditions. Although in implementation settings, they can contaminate the intervention and control groups after the initial exposure to interventions. We propose the novel application of counterbalanced design to implementation research where repeated measures are employed through crossover, but contamination is averted by counterbalancing different health contexts in which to test the implementation strategy.MethodsIn a counterbalanced implementation study, the implementation strategy (independent variable) has two or more levels evaluated across an equivalent number of health contexts (e.g. community-acquired pneumonia and nutrition for critically ill patients) using the same outcome (dependent variable). This design limits each cluster to one distinct strategy related to one specific context, and therefore does not overburden any cluster to more than one focussed implementation strategy for a particular outcome, and provides a ready-made control comparison, holding fixed. The different levels of the independent variable can be delivered concurrently because each level uses a different health context within each cluster to avoid the effect of treatment contamination from exposure to the intervention or control condition.ResultsAn example application of the counterbalanced implementation design is presented in a hypothetical study to demonstrate the comparison of ‘video-based’ and ‘written-based’ evidence summary research implementation strategies for changing clinical practice in community-acquired pneumonia and nutrition in critically ill patient health contexts.ConclusionA counterbalanced implementation study design provides a promising model for concurrently investigating the success of research implementation strategies across multiple health context areas such as community-acquired pneumonia and nutrition for critically ill patients.
Highlights
Implementation research is increasingly being recognised for optimising the outcomes of clinical practice
We propose a novel application of counterbalanced design to implementation science, which allows the concurrent comparison of interventions while minimising inter-group differences and the risk of contamination
Common randomised study designs used in implementation research The more traditional cluster randomised study design used in implementation research is a between-cluster parallel design
Summary
Implementation research is increasingly being recognised for optimising the outcomes of clinical practice. We propose the novel application of counterbalanced design to implementation research where repeated measures are employed through crossover, but contamination is averted by counterbalancing different health contexts in which to test the implementation strategy. Implementation research has been promoted as one way to facilitate the translation of research into practice [6] This developing field of research evaluates the success of strategies such as knowledge brokering [7, 8], algorithms [9], and multifaceted approaches [10, 11] for individual and organisational change. Health service researchers have increasingly recognised implementation research as a field of science [12], the benefits of many implementation attempts remain unclear [7, 13]
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