Evidence map›Paper›PMID 33663603›Full record

ArticleAdvances in simulation (London, England)2021

Translational simulation: from description to action.

Christopher Peter Nickson, Andrew Petrosoniak, Stephanie Barwick, Victoria Brazil

Open access · goldAbstract read
In one paragraph

Article in Advances in simulation (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
17.7field-weighted citation impact, top 1% of its field
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

32 citing papers in PubMed, 88 citations in OpenAlex.

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  4. Connecting data science and translational simulation.Advances in simulation (London, England) · 2026
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  20. Global consensus statement on simulation-based practice in healthcare.Advances in simulation (London, England) · 2024
    Article
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

4 authors at 3 institutions in 2 countries.

Christopher Peter NicksonIntensive Care Unit and Centre for Health Innovation, Alfred Health, Melbourne, Australia. c.nickson@alfred.org.au.ORCID http://orcid.org/0000-0002-6968-3087
Andrew PetrosoniakSt. Michael's Hospital, Toronto, Canada.
Stephanie BarwickMater Education, South Brisbane, Queensland, Australia.
Victoria BrazilFaculty of Health Sciences and Medicine, Bond University, Gold Coast, Australia.
Bond University · AUAlfred Health · AUSt. Michael's Hospital · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article describes an operational framework for implementing translational simulation in everyday practice. The framework, based on an input-process-output model, is developed from a critical review of the existing translational simulation literature and the collective experience of the authors' affiliated translational simulation services. The article describes how translational simulation may be used to explore work environments and/or people in them, improve quality through targeted interventions focused on clinical performance/patient outcomes, and be used to design and test planned infrastructure or interventions. Representative case vignettes are used to show how the framework can be applied to real world healthcare problems, including clinical space testing, process development, and culture. Finally, future directions for translational simulation are discussed. As such, the article provides a road map for practitioners who seek to address health service outcomes using translational simulation.

Indexed as

Healthcare simulationHuman factors/ergonomicsInput-process-output modelIn situ simulationOperational frameworkQuality improvementTranslational simulation

Identifiers

PMID33663603
PMCPMC7930894
OpenAlexW3134832083

What OpenQuestion holds

Textmetadata
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.