Evidence map›Paper›PMID 32546473›Full record

ArticleEmergency medicine journal : EMJ2020

A data linkage study of suspected seizures in the urgent and emergency care system in the UK.

Thomas Hughes-Gooding, Jon M Dickson, Colin O'Keeffe, Suzanne M Mason

Abstract read
In one paragraph

Article in Emergency medicine journal : EMJ, 2020. 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
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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.

Thomas Hughes-GoodingThe University of Sheffield Medical School, Sheffield, UK thomas.hughes-gooding@nhs.net.ORCID http://orcid.org/0000-0001-8483-5686
Jon M DicksonThe Academic Unit of Primary Medical Care, The University of Sheffield, Sheffield, UK.ORCID http://orcid.org/0000-0002-1361-2714
Colin O'KeeffeSchool of Health and Related Research, The University of Sheffield, Sheffield, UK.ORCID http://orcid.org/0000-0002-4484-7401
Suzanne M MasonSchool of Health and Related Research, The University of Sheffield, Sheffield, UK.ORCID http://orcid.org/0000-0002-1701-0577

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe urgent and emergency care (UEC) system is struggling with increased demand, some of which is clinically unnecessary. Patients suffering suspected seizures commonly present to EDs, but most seizures are self-limiting and have low risk of short-term adverse outcomes. We aimed to investigate the flow of suspected seizure patients through the UEC system using data linkage to facilitate the development of new models of care.

methodsWe used a two-stage process of deterministic linking to perform a cross-sectional analysis of data from adults in a large region in England (population 5.4 million) during 2014. The core dataset comprised a total of 739 436 ambulance emergency incidents, 1 033 778 ED attendances and 362 358 admissions.

resultsA high proportion of cases were successfully linked (86.9% ED-inpatient, 77.7% ED-ambulance). Suspected seizures represented 2.8% of all ambulance service incidents. 61.7% of these incidents led to dispatch of a rapid-response ambulance (8 min) and 72.1% were conveyed to hospital. 37 patients died before being conveyed to hospital and 24 died in the ED (total 61; 0.3%). The inpatient death rate was 0.4%. Suspected seizures represented 0.71% of ED attendances, 89.8% of these arrived by emergency ambulance, 45.4% were admitted and 44.5% of these admissions lasted under 48 hours.

conclusionsThis study confirms previously published data from smaller unlinked datasets, validating the linkage method, and provides new data for suspected seizures. There are significant barriers to realising the full potential of data linkage. Collaborative action is needed to create facilitative governance frameworks and improve data quality and analytical capacity.

Indexed as

Ambulatory CareEmergency Service, HospitalAdultAmbulancesCross-Sectional StudiesFemaleHumansIncidenceInformation Storage and RetrievalMaleSeizuresUnited KingdomEDsemergency care systemsneurology, epilepsyprehospitalresearch, methods

Identifiers

PMID32546473
PMCPMC7525779

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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.