A novel counterbalanced implementation study design

Methodological description and application to implementation research

Mitchell N. Sarkies, Elizabeth H. Skinner, Kelly Ann Bowles, Meg E. Morris, Cylie Williams, Lisa O'Brien, Anne Bardoel, Jenny Martin, Anne E. Holland, Leeanne Carey, Jennifer White, Terry P. Haines

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)

Abstract

Background: Implementation 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. Methods: In 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. Results: An 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. Conclusion: A 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.

Original languageEnglish
Article number45
Number of pages11
JournalImplementation Science
Volume14
Issue number1
DOIs
Publication statusPublished - 2 May 2019

Keywords

  • Context
  • Counterbalanced
  • Crossover
  • Design
  • Implementation
  • Method
  • Randomised controlled trial
  • Research
  • Strategy
  • Study

Cite this

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abstract = "Background: Implementation 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. Methods: In 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. Results: An 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. Conclusion: A 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.",
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A novel counterbalanced implementation study design : Methodological description and application to implementation research. / Sarkies, Mitchell N.; Skinner, Elizabeth H.; Bowles, Kelly Ann; Morris, Meg E.; Williams, Cylie; O'Brien, Lisa; Bardoel, Anne; Martin, Jenny; Holland, Anne E.; Carey, Leeanne; White, Jennifer; Haines, Terry P.

In: Implementation Science, Vol. 14, No. 1, 45, 02.05.2019.

Research output: Contribution to journalArticleResearchpeer-review

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T2 - Methodological description and application to implementation research

AU - Sarkies, Mitchell N.

AU - Skinner, Elizabeth H.

AU - Bowles, Kelly Ann

AU - Morris, Meg E.

AU - Williams, Cylie

AU - O'Brien, Lisa

AU - Bardoel, Anne

AU - Martin, Jenny

AU - Holland, Anne E.

AU - Carey, Leeanne

AU - White, Jennifer

AU - Haines, Terry P.

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AB - Background: Implementation 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. Methods: In 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. Results: An 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. Conclusion: A 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.

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KW - Crossover

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KW - Implementation

KW - Method

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KW - Research

KW - Strategy

KW - Study

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