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Applying implementation frameworks to the clinical trial context

BACKGROUND: Clinical trials advance science, benefit society, and provide optimal care to individuals with some conditions, such as cancer. However, clinical trials often fail to reach their endpoints, and low participant enrollment remains a critical problem with trial conduct. In these ways, clini...

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Autores principales: Stensland, Kristian D., Sales, Anne E., Damschroder, Laura J., Skolarus, Ted A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9552519/
https://www.ncbi.nlm.nih.gov/pubmed/36217172
http://dx.doi.org/10.1186/s43058-022-00355-6
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author Stensland, Kristian D.
Sales, Anne E.
Damschroder, Laura J.
Skolarus, Ted A.
author_facet Stensland, Kristian D.
Sales, Anne E.
Damschroder, Laura J.
Skolarus, Ted A.
author_sort Stensland, Kristian D.
collection PubMed
description BACKGROUND: Clinical trials advance science, benefit society, and provide optimal care to individuals with some conditions, such as cancer. However, clinical trials often fail to reach their endpoints, and low participant enrollment remains a critical problem with trial conduct. In these ways, clinical trials can be considered beneficial evidence-based practices suffering from poor implementation. Prior approaches to improving trials have had difficulties with reproducibility and limited impact, perhaps due to the lack of an underlying trial improvement framework. For these reasons, we propose adapting implementation science frameworks to the clinical trial context to improve the implementation of clinical trials. MAIN TEXT: We adapted an outcomes framework (Proctor’s Implementation Outcomes Framework) and a determinants framework (the Consolidated Framework for Implementation Research) to the trial context. We linked these frameworks to ERIC-based improvement strategies and present an inferential process model for identifying and selecting trial improvement strategies based on the Implementation Research Logic Model. We describe example applications of the framework components to the trial context and present a worked example of our model applied to a trial with poor enrollment. We then consider the implications of this approach on improving existing trials, the design of future trials, and assessing trial improvement interventions. Additionally, we consider the use of implementation science in the clinical trial context, and how clinical trials can be “test cases” for implementation research. CONCLUSIONS: Clinical trials can be considered beneficial evidence-based interventions suffering from poor implementation. Adapting implementation science approaches to the clinical trial context can provide frameworks for contextual assessment, outcome measurement, targeted interventions, and a shared vocabulary for clinical trial improvement. Additionally, exploring implementation frameworks in the trial context can advance the science of implementation through both “test cases” and providing fertile ground for implementation intervention design and testing.
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spelling pubmed-95525192022-10-12 Applying implementation frameworks to the clinical trial context Stensland, Kristian D. Sales, Anne E. Damschroder, Laura J. Skolarus, Ted A. Implement Sci Commun Debate BACKGROUND: Clinical trials advance science, benefit society, and provide optimal care to individuals with some conditions, such as cancer. However, clinical trials often fail to reach their endpoints, and low participant enrollment remains a critical problem with trial conduct. In these ways, clinical trials can be considered beneficial evidence-based practices suffering from poor implementation. Prior approaches to improving trials have had difficulties with reproducibility and limited impact, perhaps due to the lack of an underlying trial improvement framework. For these reasons, we propose adapting implementation science frameworks to the clinical trial context to improve the implementation of clinical trials. MAIN TEXT: We adapted an outcomes framework (Proctor’s Implementation Outcomes Framework) and a determinants framework (the Consolidated Framework for Implementation Research) to the trial context. We linked these frameworks to ERIC-based improvement strategies and present an inferential process model for identifying and selecting trial improvement strategies based on the Implementation Research Logic Model. We describe example applications of the framework components to the trial context and present a worked example of our model applied to a trial with poor enrollment. We then consider the implications of this approach on improving existing trials, the design of future trials, and assessing trial improvement interventions. Additionally, we consider the use of implementation science in the clinical trial context, and how clinical trials can be “test cases” for implementation research. CONCLUSIONS: Clinical trials can be considered beneficial evidence-based interventions suffering from poor implementation. Adapting implementation science approaches to the clinical trial context can provide frameworks for contextual assessment, outcome measurement, targeted interventions, and a shared vocabulary for clinical trial improvement. Additionally, exploring implementation frameworks in the trial context can advance the science of implementation through both “test cases” and providing fertile ground for implementation intervention design and testing. BioMed Central 2022-10-10 /pmc/articles/PMC9552519/ /pubmed/36217172 http://dx.doi.org/10.1186/s43058-022-00355-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Debate
Stensland, Kristian D.
Sales, Anne E.
Damschroder, Laura J.
Skolarus, Ted A.
Applying implementation frameworks to the clinical trial context
title Applying implementation frameworks to the clinical trial context
title_full Applying implementation frameworks to the clinical trial context
title_fullStr Applying implementation frameworks to the clinical trial context
title_full_unstemmed Applying implementation frameworks to the clinical trial context
title_short Applying implementation frameworks to the clinical trial context
title_sort applying implementation frameworks to the clinical trial context
topic Debate
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9552519/
https://www.ncbi.nlm.nih.gov/pubmed/36217172
http://dx.doi.org/10.1186/s43058-022-00355-6
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