Evidence map›Paper›PMID 29247093›Full record

ArticleBMJ open2017

Feasibility of a hyper-acute stroke unit model of care across England: a modelling analysis.

Michael Allen, Kerry Pearn, Emma Villeneuve, Thomas Monks, Ken Stein, Martin James

Abstract read
In one paragraph

Article in BMJ open, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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.

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Observational
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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

6 authors.

Michael AllenInstitute of Health Research, University of Exeter Medical School, St Luke's Campus, Exeter, UK.
Kerry PearnInstitute of Health Research, University of Exeter Medical School, St Luke's Campus, Exeter, UK.
Emma VilleneuveInstitute of Health Research, University of Exeter Medical School, St Luke's Campus, Exeter, UK.
Thomas MonksNIHR CLAHRC Wessex Data Science Hub, Southampton General Hospital, Southampton, UK.
Ken SteinInstitute of Health Research, University of Exeter Medical School, St Luke's Campus, Exeter, UK.
Martin JamesStroke Services, Royal Devon & Exeter NHS trust, Exeter, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe policy of centralising hyperacute stroke units (HASUs) in England aims to provide stroke care in units that are both large enough to sustain expertise (>600 admissions/year) and dispersed enough to rapidly deliver time-critical treatments (<30 min maximum travel time). Currently, just over half (56%) of patients with stroke access care in such a unit. We sought to model national configurations of HASUs that would optimise both institutional size and geographical access to stroke care, to maximise the population benefit from the centralisation of stroke care.

designModelling of the effect of the national reconfiguration of stroke services. Optimal solutions were identified using a heuristic genetic algorithm.

setting127 acute stroke services in England, serving a population of 54 million people.

participants238 887 emergency admissions with acute stroke over a 3-year period (2013-2015).

interventionModelled reconfigurations of HASUs optimised for institutional size and geographical access.

main outcome measureTravel distances and times to HASUs, proportion of patients attending a HASU with at least 600 admissions per year, and minimum and maximum HASU admissions.

resultsSolutions were identified with 75-85 HASUs with annual stroke admissions in the range of 600-2000, which achieve up to 82% of patients attending a stroke unit within 30 min estimated travel time (with at least 95% and 98% of the patients being within 45 and 60 min travel time, respectively).

conclusionsThe reconfiguration of hyperacute stroke services in England could lead to all patients being treated in a HASU with between 600 and 2000 admissions per year. However, the proportion of patients within 30 min of a HASU would fall from over 90% to 80%-82%.

Indexed as

TravelAlgorithmsCritical PathwaysEnglandFeasibility StudiesHospital UnitsHumansPatient AdmissionStrokeTime Factorsorganisation of health servicesquality in health carestroke

Identifiers

PMID29247093
PMCPMC5736033

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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.