{
  "abstract": "Objectives Rising 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 setting A 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.Results We 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.Conclusions Nearly 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.",
  "authors": [
    {
      "affiliations": [
        "School of Medicine and Population Health, The University of Sheffield, Sheffield, UK"
      ],
      "name": "Richard M Jacques"
    },
    {
      "affiliations": [
        "School of Medicine and Population Health, The University of Sheffield, Sheffield, UK"
      ],
      "name": "Rebecca M Simpson"
    },
    {
      "affiliations": [
        "Data Connect, The University of Sheffield, Sheffield, UK"
      ],
      "name": "Madina Hasan"
    },
    {
      "affiliations": [
        "School of Medicine and Population Health, The University of Sheffield, Sheffield, UK"
      ],
      "name": "Ric Campbell"
    },
    {
      "affiliations": [
        "Data Connect, The University of Sheffield, Sheffield, UK"
      ],
      "name": "Simone Croft"
    },
    {
      "affiliations": [
        "School of Medicine and Population Health, The University of Sheffield, Sheffield, UK",
        "Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK"
      ],
      "name": "Susan Croft"
    },
    {
      "affiliations": [
        "Barts Life Sciences, Barts Health NHS Trust, London, UK"
      ],
      "name": "Sophie Williams"
    },
    {
      "affiliations": [
        "PIONEER Data Hub in Acute Care, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK",
        "NIHR Midlands Patient Safety Research Collaboration and NIHR Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK"
      ],
      "name": "Suzy Gallier"
    },
    {
      "affiliations": [
        "PIONEER Data Hub in Acute Care, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK"
      ],
      "name": "Felicity Evison"
    },
    {
      "affiliations": [
        "Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK",
        "NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol, UK"
      ],
      "name": "Amy Dillon"
    },
    {
      "affiliations": [
        "Faculty of Medicine, Department of Surgery and Cancer, Imperial College London, London, UK",
        "Imperial Clinical Analytics Research & Evaluation (iCARE) Secure Data Environment, NIHR, Imperial BRC, Imperial College Healthcare NHS Trust, London, UK"
      ],
      "name": "Ben Glampson"
    },
    {
      "affiliations": [
        "Department of Data Science, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK"
      ],
      "name": "Quinta Davies"
    },
    {
      "affiliations": [
        "Lancaster Medical School, Lancaster University, Lancaster, UK"
      ],
      "name": "Jo Knight"
    },
    {
      "affiliations": [
        "Southampton Emerging Therapies and Technologies (SETT) Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK",
        "Clinical Informatics Research Unit (CIRU), University of Southampton, Southampton, UK"
      ],
      "name": "Cai Davis"
    },
    {
      "affiliations": [
        "Southampton Emerging Therapies and Technologies (SETT) Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK",
        "Clinical Informatics Research Unit (CIRU), University of Southampton, Southampton, UK"
      ],
      "name": "Michael George"
    },
    {
      "affiliations": [
        "Clinical Informatics, Barts Health NHS Trust, London, UK"
      ],
      "name": "Charles Gutteridge"
    },
    {
      "affiliations": [
        "PIONEER Data Hub in Acute Care, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK",
        "NIHR Midlands Patient Safety Research Collaboration and NIHR Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK"
      ],
      "name": "Elizabeth Sapey"
    },
    {
      "affiliations": [
        "Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK",
        "NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol, UK",
        "Health Data Research UK South-West, Bristol, Bristol, UK"
      ],
      "name": "Rachel Denholm"
    },
    {
      "affiliations": [
        "Faculty of Medicine, Department of Surgery and Cancer, Imperial College London, London, UK",
        "Imperial Clinical Analytics Research & Evaluation (iCARE) Secure Data Environment, NIHR, Imperial BRC, Imperial College Healthcare NHS Trust, London, UK"
      ],
      "name": "Erik Mayer"
    },
    {
      "affiliations": [
        "Department of Data Science, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK"
      ],
      "name": "Vishnu Chandrabalan"
    },
    {
      "affiliations": [
        "Southampton Emerging Therapies and Technologies (SETT) Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK",
        "Clinical Informatics Research Unit (CIRU), University of Southampton, Southampton, UK"
      ],
      "name": "Matt Stammers"
    },
    {
      "affiliations": [
        "School of Medicine and Population Health, The University of Sheffield, Sheffield, UK",
        "Data Connect, The University of Sheffield, Sheffield, UK"
      ],
      "name": "Suzanne Mason"
    },
    {
      "affiliations": [],
      "name": "HDRUK UK Regional Linked Data Consortium"
    }
  ],
  "title": "Variation in emergency department attendances and acute hospital admissions for ambulatory emergency care: a retrospective analysis of routinely collected NHS data across England",
  "uid": "947d33ec-b662-5e5e-91ea-047dbcd07eea"
}