Evidence map›Paper›PMID 35907894›Full record

ArticleImplementation science communications2022

Using decision analysis to support implementation planning in research and practice.

Natalie Riva Smith, Kathleen E Knocke, Kristen Hassmiller Lich

Abstract read
In one paragraph

Article in Implementation science communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Natalie Riva SmithDepartment of Social and Behavioral Sciences, Harvard TH Chan School of Public Health, Harvard University, Boston, MA, 02115, USA. nataliesmith@hsph.harvard.edu.ORCID http://orcid.org/0000-0002-2052-9433
Kathleen E KnockeDepartment of Health Policy and Management, Gillings School of Global Public Health, UNC Chapel Hill, Chapel Hill, USA.
Kristen Hassmiller LichDepartment of Health Policy and Management, Gillings School of Global Public Health, UNC Chapel Hill, Chapel Hill, USA.

Funding

Research Services CoreP2CHD050924 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAREN B GUZZO · 2015 to 2026
$9.6M
From Biological to Social Processes: Interdisciplinary Training in Life Course ResearchT32HD091058 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ROBERT A HUMMER, Amanda L Thompson · 2017 to 2026
$4.3M
The Harvard Chan Education Program in Cancer Prevention and ControlT32CA057711 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Karen M. Emmons, ANNE LINDSAY FRAZIER · 2019 to 2026
$3.3M
NCI NIH HHS T32 CA057711NICHD NIH HHS P2C HD050924NICHD NIH HHS T32 HD091058NIH HHS T32CA057711NIH HHS T32HD091058
6 · The paper itself

Abstract

backgroundThe 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.

conclusionTo 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.

Indexed as

Cost and cost analysisDecision-makingDecision support techniquesEconomic evaluationImplementation science

Identifiers

PMID35907894
PMCPMC9338582

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.