Evidence map›Paper›PMID 35551537›Full record

ArticlePloS one2022

Implementation of prediction models in the emergency department from an implementation science perspective-Determinants, outcomes and real-world impact: A scoping review protocol.

Sze Ling Chan, Jin Wee Lee, Marcus Eng Hock Ong, Fahad Javaid Siddiqui, Nicholas Graves, Andrew Fu Wah Ho, Nan Liu

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

7 authors.

Sze Ling ChanHealth Services Research Centre, Singapore Health Services, Singapore, Singapore.
Jin Wee LeeCentre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore.ORCID 0000-0003-4084-0904
Marcus Eng Hock OngHealth Services Research Centre, Singapore Health Services, Singapore, Singapore.
Fahad Javaid SiddiquiPrehospital Emergency Research Centre, Duke-NUS Medical School, Singapore, Singapore.ORCID 0000-0002-9046-5105
Nicholas GravesProgramme in Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore.
Andrew Fu Wah HoDepartment of Emergency Medicine, Singapore General Hospital, Singapore, Singapore.
Nan LiuHealth Services Research Centre, Singapore Health Services, Singapore, Singapore.ORCID 0000-0003-3610-4883

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The number of prediction models developed for use in emergency departments (EDs) have been increasing in recent years to complement traditional triage systems. However, most of these models have only reached the development or validation phase, and few have been implemented in clinical practice. There is a gap in knowledge on the real-world performance of prediction models in the ED and how they can be implemented successfully into routine practice. Existing reviews of prediction models in the ED have also mainly focused on model development and validation. The aim of this scoping review is to summarize the current landscape and understanding of implementation of predictions models in the ED. This scoping review follows the Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. We will include studies that report implementation outcomes and/or contextual determinants according to the RE-AIM/PRISM framework for prediction models used in EDs. We will include outcomes or contextual determinants studied at any point of time in the implementation process except for effectiveness, where only post-implementation results will be included. Conference abstracts, theses and dissertations, letters to editors, commentaries, non-research documents and non-English full-text articles will be excluded. Four databases (MEDLINE (through PubMed), Embase, Scopus and CINAHL) will be searched from their inception using a combination of search terms related to the population, intervention and outcomes. Two reviewers will independently screen articles for inclusion and any discrepancy resolved with a third reviewer. Results from included studies will be summarized narratively according to the RE-AIM/PRISM outcomes and domains. Where appropriate, a simple descriptive summary of quantitative outcomes may be performed.

Indexed as

Emergency Service, HospitalImplementation ScienceDelivery of Health CareScoping Reviews as Topic

Identifiers

PMID35551537
PMCPMC9097992

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.