Evidence map›Paper›PMID 28789652›Full record

ArticleBMC health services research2017

Exploring the relationship between general practice characteristics and attendance at Walk-in Centres, Minor Injuries Units and Emergency Departments in England 2009/10-2012/2013: a longitudinal study.

Peter Tammes, Richard W Morris, Emer Brangan, Kath Checkland, Helen England, Alyson Huntley, Daniel Lasserson, Fiona MacKichan, Chris Salisbury, Lesley Wye and 1 more

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In one paragraph

Article in BMC health services research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. What do we mean by urgent care? Definitional confusion and its consequences.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026
    Article
  3. Article
  4. Article
  5. Observational
  6. Article
  7. Observational
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

11 authors.

Peter TammesCentre for Academic Primary Care, Bristol Medical School, University of Bristol, Bristol, UK. p.tammes@bristol.ac.uk.ORCID http://orcid.org/0000-0001-7959-745X
Richard W MorrisCentre for Academic Primary Care, Bristol Medical School, University of Bristol, Bristol, UK.
Emer BranganCentre for Academic Primary Care, Bristol Medical School, University of Bristol, Bristol, UK.
Kath ChecklandCentre for Primary Care, Institute of Population Health, University of Manchester, Manchester, UK.
Helen EnglandDevon Partnership NHS Trust, Exeter, UK.
Alyson HuntleyCentre for Academic Primary Care, Bristol Medical School, University of Bristol, Bristol, UK.
Daniel LassersonNuffield Department of Medicine, University of Oxford, Oxford, UK.
Fiona MacKichanCentre for Academic Primary Care, Bristol Medical School, University of Bristol, Bristol, UK.
Chris SalisburyCentre for Academic Primary Care, Bristol Medical School, University of Bristol, Bristol, UK.
Lesley WyeCentre for Academic Primary Care, Bristol Medical School, University of Bristol, Bristol, UK.
Sarah PurdyCentre for Academic Primary Care, Bristol Medical School, University of Bristol, Bristol, UK.

Funding

Department of Health PB-PG-1111-26018
6 · The paper itself

Abstract

backgroundThe UK National Health Service Emergency Departments (ED) have recently faced increasing attendance rates. This study investigated associations of general practice and practice population characteristics with emergency care service attendance rates.

methodsA longitudinal design with practice-level measures of access and continuity of care, patient population demographics and use of emergency care for the financial years 2009/10 to 2012/13. The main outcome measures were self-referred discharged ED attendance rate, and combined self-referred discharged ED, self-referred Walk-in Centre (WiC) and self-referred Minor Injuries Unit (MIU) attendance rate per 1000 patients. Multilevel models estimated adjusted regression coefficients for relationships between patients' emergency attendance rates and patients' reported satisfaction with opening hours and waiting time at the practice, proportion of patients having a preferred GP, and use of WiC and MIU, both between practices, and within practices over time.

resultsPractice characteristics associated with higher ED attendance rates included lower percentage of patients satisfied with waiting time (0.22 per 1% decrease, 95%CI 0.02 to 0.43) and lower percentage having a preferred GP (0.12 per 1% decrease, 95%CI 0.02 to 0.21). Population influences on higher attendance included more elderly, more female and more unemployed patients, and lower male life-expectancy and urban conurbation location. Net reductions in ED attendance were only seen for practices whose WiC or MIU attendance was high, above the 60th centile for MIU and above the 75th centile for WiC. Combined emergency care attendance fell over time if more patients within a practice were satisfied with opening hours (-0.26 per 1% increase, 95%CI -0.45 to -0.08).

conclusionPractices with more patients satisfied with waiting time, having a preferred GP, and using MIU and WIC services, had lower ED attendance. Increases over time in attendance at MIUs, and patient satisfaction with opening hours was associated with reductions in service use.

Indexed as

General PracticePatient SatisfactionAdultAgedAmbulatory Care FacilitiesEmergency Medical ServicesEmergency Service, HospitalEnglandFemaleHumansLongitudinal StudiesMaleMultilevel AnalysisOutcome Assessment, Health CareAlternative health care serviceContinuity of care‘Emergency servicehospital’Longitudinal studyMultilevel modellingPopulation characteristicsPrimary health care

Identifiers

PMID28789652
PMCPMC5549356

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Registered trials

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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.