Evidence map›Paper›PMID 42336780›Full record

ArticleBMJ open2026

Variation in emergency department attendances and acute hospital admissions for ambulatory emergency care: a retrospective analysis of routinely collected NHS data across England.

Richard M Jacques, Rebecca M Simpson, Madina Hasan, Ric Campbell, Simone Croft, Susan Croft, Sophie Williams, Suzy Gallier, Felicity Evison, Amy Dillon and 13 more

Abstract read
In one paragraph

Article in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

23 authors.

Richard M JacquesSchool of Medicine and Population Health, The University of Sheffield, Sheffield, UK r.jacques@sheffield.ac.uk.ORCID http://orcid.org/0000-0001-6710-5403
Rebecca M SimpsonSchool of Medicine and Population Health, The University of Sheffield, Sheffield, UK.ORCID http://orcid.org/0000-0003-1677-5938
Madina HasanData Connect, The University of Sheffield, Sheffield, UK.
Ric CampbellSchool of Medicine and Population Health, The University of Sheffield, Sheffield, UK.
Simone CroftData Connect, The University of Sheffield, Sheffield, UK.
Susan CroftSchool of Medicine and Population Health, The University of Sheffield, Sheffield, UK.
Sophie WilliamsBarts Life Sciences, Barts Health NHS Trust, London, UK.
Suzy GallierPIONEER Data Hub in Acute Care, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.ORCID http://orcid.org/0000-0003-1026-4125
Felicity EvisonPIONEER Data Hub in Acute Care, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.ORCID http://orcid.org/0000-0002-9378-7548
Amy DillonPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Ben GlampsonFaculty of Medicine, Department of Surgery and Cancer, Imperial College London, London, UK.
Quinta DaviesDepartment of Data Science, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK.
Jo KnightLancaster Medical School, Lancaster University, Lancaster, UK.ORCID http://orcid.org/0000-0002-7148-1660
Cai DavisSouthampton Emerging Therapies and Technologies (SETT) Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK.
Michael GeorgeSouthampton Emerging Therapies and Technologies (SETT) Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK.
Charles GutteridgeClinical Informatics, Barts Health NHS Trust, London, UK.
Elizabeth SapeyPIONEER Data Hub in Acute Care, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.ORCID http://orcid.org/0000-0003-3454-5482
Rachel DenholmPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Erik MayerFaculty of Medicine, Department of Surgery and Cancer, Imperial College London, London, UK.
Vishnu ChandrabalanDepartment of Data Science, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK.
Matt StammersSouthampton Emerging Therapies and Technologies (SETT) Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK.ORCID http://orcid.org/0000-0003-3850-3116
Suzanne MasonSchool of Medicine and Population Health, The University of Sheffield, Sheffield, UK.ORCID http://orcid.org/0000-0002-1701-0577
HDRUK UK Regional Linked Data Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesRising demand for emergency care in England is a continuing challenge driven by population ageing and increasing multimorbidity. Ambulatory emergency care (AEC) refers to the provision of same-day acute care for patients who might otherwise require admission. However, the contribution of AEC conditions to demand remains unclear. This study aimed to examine the proportion and nature of patients attending emergency departments (ED) with AEC-related conditions and to describe variation between hospitals in attendances and emergency admissions for AEC conditions. DESIGN AND

settingA retrospective study of routine data from 21 acute hospitals in England, including adult ED attendances and emergency admissions between 1 November 2021 and 31 October 2022. We used a federated approach to ensure data security, applying established AEC definitions to explore variation by age, socioeconomic status and length of stay. OUTCOME MEASURES: Primary: Proportion of (i) ED attendances and (ii) emergency admissions for AEC conditions. Secondary: (i) Proportion of patients presenting at ED with an AEC condition who were admitted; (ii) proportion of emergency admissions with an AEC condition with a length of stay <2 days.

resultsWe analysed 1 513 480 attendances (median per hospital: 73 125) and 660 105 admissions (median per hospital: 30 425). AEC accounted for 29.6% of attendances and 40.8% of admissions, with substantial inter-hospital variability. Patients aged ≥65 were more likely to present with an AEC, while patients from deprived areas had lower rates. Among AEC-related admissions, 49.3% had a stay of less than 2 days.

conclusionsNearly one-third of attendances and two-fifths of admissions were for conditions potentially manageable in AEC or community settings. Variation between hospitals suggests local factors, including service configuration and primary care access, may influence avoidable acute care use. These findings suggest a need for a more nuanced understanding of the drivers behind AEC, or SDEC Services, to better understand their impact on reducing hospital admissions. Analysing these patterns may inform interventions to reduce avoidable hospital utilisation. Further research is needed to identify drivers of variation and to develop scalable strategies for prevention.

Indexed as

Ambulatory CareEmergency Room VisitsEmergency Service, HospitalHospitalizationPatient AdmissionAdolescentAdultAgedAged, 80 and overEnglandFemaleHumansLength of StayMaleMiddle AgedRetrospective StudiesACCIDENT & EMERGENCY MEDICINEEmergency DepartmentsObservational Study

Identifiers

PMID42336780
PMCPMC13296041

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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.