Evidence map›Paper›PMID 34378000›Full record

ArticleJournal of the American College of Emergency Physicians open2021

Call volume, triage outcomes, and protocols during the first wave of the COVID-19 pandemic in the United Kingdom: Results of a national survey.

Helen Snooks, Alan John Watkins, Fiona Bell, Mike Brady, Andy Carson-Stevens, Edward Duncan, Bridie Angela Evans, Louise England, Theresa Foster, John Gallanders and 12 more

Abstract read
In one paragraph

Article in Journal of the American College of Emergency Physicians open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 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

22 authors.

Helen SnooksSwansea University Medical School Swansea UK.
Alan John WatkinsSwansea University Medical School Swansea UK.
Fiona BellYorkshire Ambulance Service NHS Trust Wakefield UK.
Mike BradyWelsh Ambulance Services NHS Trust Trust Headquarters Denbighshire Wales UK.
Andy Carson-StevensDivision of Population Medicine Cardiff University Cardiff UK.
Edward DuncanNursing Midwifery and Allied Health Professions Research Unit University of Stirling Stirling UK.
Bridie Angela EvansSwansea University Medical School Swansea UK.
Louise EnglandEast Midlands Ambulance Service NHS Trust Lincoln UK.
Theresa FosterEast of England Ambulance Service NHS Trust Melbourn Cambridgeshire UK.
John GallandersSwansea University Medical School Swansea UK.
Imogen GunsonWest Midlands Ambulance Service NHS Trust West Midlands UK.
Robert Harris-MayesUnaffiliated - Patient and Public Contributor.
Mark KingstonSwansea University Medical School Swansea UK.
Ronan LyonsSwansea University Medical School Swansea UK.
Elisha MillerYorkshire Ambulance Service NHS Trust Wakefield UK.
Andy NewtonSwansea University Medical School Swansea UK.
Alison PorterSwansea University Medical School Swansea UK.
Tom QuinnKingston University and St George's University of London London UK.
Andy RosserWest Midlands Ambulance Service NHS Trust West Midlands UK.
Aloysius Niroshan SiriwardenaCommunity and Health Research Unit University of Lincoln School of Health & Social Care Lincoln UK.
Robert SpaightEast Midlands Ambulance Service NHS Trust Lincoln UK.
Victoria WilliamsSwansea University Medical School Swansea UK.

Funding

Medical Research Council MC_PC_13043Medical Research Council MR/K006525/1Medical Research Council MR/V027808/1Medical Research Council MR/V028367/1
6 · The paper itself

Abstract

objectivesDuring the first wave of the COVID-19 pandemic in the United Kingdom (UK), to describe volume and pattern of calls to emergency ambulance services, proportion of calls where an ambulance was dispatched, proportion conveyed to hospital, and features of triage used.

methodsSemistructured electronic survey of all UK ambulance services (n = 13) and a request for routine service data on weekly call volumes for 22 weeks (February 1-July 3, 2020). Questionnaires and data request were emailed to chief executives and research leads followed by email and telephone reminders. The routine data were analyzed using descriptive statistics, and questionnaire data using thematic analysis.

resultsCompleted questionnaires were received from 12 services. Call volume varied widely between services, with a UK peak at week 7 at 13.1% above baseline (service range -0.5% to +31.4%). All services ended the study period with a lower call volume than at baseline (service range -3.7% to -25.5%). Suspected COVID-19 calls across the UK totaled 604,146 (13.5% of all calls), with wide variation between services (service range 3.7% to 25.7%), and in service peaks of 11.4% to 44.5%. Ambulances were dispatched to 478,638 (79.2%) of these calls (service range 59.0% to 100.0%), with 262,547 (43.5%) resulting in conveyance to hospital (service range 32.0% to 53.9%). Triage models varied between services and over time. Two primary call triage systems were in use across the UK. There were a large number of products and arrangements used for secondary triage, with services using paramedics, nurses, and doctors to support decision making in the call center and on scene. Frequent changes to triage processes took place.

conclusionsCall volumes were highly variable. Case mix and workload changed significantly as COVID-19 calls displaced other calls. Triage models and prehospital outcomes varied between services. We urgently need to understand safety and effectiveness of triage models to inform care during further waves and pandemics.

Indexed as

ambulancesCOVID‐19pandemicprehospital emergency caretriage

Identifiers

PMID34378000
PMCPMC8328888

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.