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Using decision analysis to support implementation planning in research and practice

BACKGROUND: The process of implementing evidence-based interventions, programs, and policies is difficult and complex. Planning for implementation is critical and likely plays a key role in the long-term impact and sustainability of interventions in practice. However, implementation planning is also...

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Autores principales: Smith, Natalie Riva, Knocke, Kathleen E., Hassmiller Lich, Kristen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9338582/
https://www.ncbi.nlm.nih.gov/pubmed/35907894
http://dx.doi.org/10.1186/s43058-022-00330-1
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author Smith, Natalie Riva
Knocke, Kathleen E.
Hassmiller Lich, Kristen
author_facet Smith, Natalie Riva
Knocke, Kathleen E.
Hassmiller Lich, Kristen
author_sort Smith, Natalie Riva
collection PubMed
description BACKGROUND: The process of implementing evidence-based interventions, programs, and policies is difficult and complex. Planning for implementation is critical and likely plays a key role in the long-term impact and sustainability of interventions in practice. However, implementation planning is also difficult. Implementors must choose what to implement and how best to implement it, and each choice has costs and consequences to consider. As a step towards supporting structured and organized implementation planning, we advocate for increased use of decision analysis. MAIN TEXT: When applied to implementation planning, decision analysis guides users to explicitly define the problem of interest, outline different plans (e.g., interventions/actions, implementation strategies, timelines), and assess the potential outcomes under each alternative in their context. We ground our discussion of decision analysis in the PROACTIVE framework, which guides teams through key steps in decision analyses. This framework includes three phases: (1) definition of the decision problems and overall objectives with purposeful stakeholder engagement, (2) identification and comparison of different alternatives, and (3) synthesis of information on each alternative, incorporating uncertainty. We present three examples to illustrate the breadth of relevant decision analysis approaches to implementation planning. CONCLUSION: To further the use of decision analysis for implementation planning, we suggest areas for future research and practice: embrace model thinking; build the business case for decision analysis; identify when, how, and for whom decision analysis is more or less useful; improve reporting and transparency of cost data; and increase collaborative opportunities and training.
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spelling pubmed-93385822022-07-31 Using decision analysis to support implementation planning in research and practice Smith, Natalie Riva Knocke, Kathleen E. Hassmiller Lich, Kristen Implement Sci Commun Debate BACKGROUND: The process of implementing evidence-based interventions, programs, and policies is difficult and complex. Planning for implementation is critical and likely plays a key role in the long-term impact and sustainability of interventions in practice. However, implementation planning is also difficult. Implementors must choose what to implement and how best to implement it, and each choice has costs and consequences to consider. As a step towards supporting structured and organized implementation planning, we advocate for increased use of decision analysis. MAIN TEXT: When applied to implementation planning, decision analysis guides users to explicitly define the problem of interest, outline different plans (e.g., interventions/actions, implementation strategies, timelines), and assess the potential outcomes under each alternative in their context. We ground our discussion of decision analysis in the PROACTIVE framework, which guides teams through key steps in decision analyses. This framework includes three phases: (1) definition of the decision problems and overall objectives with purposeful stakeholder engagement, (2) identification and comparison of different alternatives, and (3) synthesis of information on each alternative, incorporating uncertainty. We present three examples to illustrate the breadth of relevant decision analysis approaches to implementation planning. CONCLUSION: To further the use of decision analysis for implementation planning, we suggest areas for future research and practice: embrace model thinking; build the business case for decision analysis; identify when, how, and for whom decision analysis is more or less useful; improve reporting and transparency of cost data; and increase collaborative opportunities and training. BioMed Central 2022-07-30 /pmc/articles/PMC9338582/ /pubmed/35907894 http://dx.doi.org/10.1186/s43058-022-00330-1 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
Smith, Natalie Riva
Knocke, Kathleen E.
Hassmiller Lich, Kristen
Using decision analysis to support implementation planning in research and practice
title Using decision analysis to support implementation planning in research and practice
title_full Using decision analysis to support implementation planning in research and practice
title_fullStr Using decision analysis to support implementation planning in research and practice
title_full_unstemmed Using decision analysis to support implementation planning in research and practice
title_short Using decision analysis to support implementation planning in research and practice
title_sort using decision analysis to support implementation planning in research and practice
topic Debate
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9338582/
https://www.ncbi.nlm.nih.gov/pubmed/35907894
http://dx.doi.org/10.1186/s43058-022-00330-1
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