Evidence map›Paper›PMID 32517553›Full record

ReviewJournal of health services research & policy2021

Clarifying the concept of avoidable emergency department attendance.

Beth Parkinson, Rachel Meacock, Katherine Checkland, Matt Sutton

Abstract readReview
In one paragraph

Review in Journal of health services research & policy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

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  19. Young adults' healthcare utilisation and healthcare needs: Perceptions and experiences of healthcare providers.Health expectations : an international journal of public participation in health care and health policy · 2022
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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

4 authors.

Beth ParkinsonPhD student in Health Economics, Health Organisation, Policy and Economics, The University of Manchester, UK.ORCID 0000-0003-4120-0933
Rachel MeacockSenior Lecturer in Health Economics, Health Organisation, Policy and Economics, The University of Manchester, UK.
Katherine ChecklandProfessor of Health Policy and Primary Care, Health Organisation, Policy and Economics, The University of Manchester, UK.
Matt SuttonProfessor of Health Economics, Health Organisation, Policy and Economics, School of Health Sciences, The University of Manchester, UK.

Funding

Wellcome TrustWellcome Trust 208183/Z/17/Z
6 · The paper itself

Abstract

Emergency department attendances are rising in several countries. Many of the policies aimed at reducing emergency department attendances are based on the assumption that a proportion of current utilization is 'avoidable' and therefore could be reduced. In considering how to achieve this aim, it is important to first understand the problem. In this essay, we review the literature on the concept and identification of avoidable emergency department attendances in England. We identified three areas of inconsistency surrounding avoidable emergency department attendances: the terminology, the underlying definition, and the method used to identify avoidable attendances. We offer a more nuanced definition which may better support action to reduce emergency department activity. Recognizing that there are different types of undesirable utilization which vary by underlying causes and potential solutions will aid policy makers in identifying areas where policies targeting reductions in emergency department attendances would best be directed.

Indexed as

Emergency Service, HospitalEnglandHumansavoidableemergency careemergency departmenthealth policypreventable

Identifiers

PMID32517553
PMCPMC7734604

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.