{
  "abstract": "Background Frequent users (FUs) of emergency departments (EDs) attend repeatedly, placing a disproportionate burden on healthcare systems. Although known to be heterogeneous, there is limited international evidence characterising FU subpopulations or examining how healthcare costs and outcomes differ across groups. Advancing this understanding is important for developing tailored interventions to meet diverse care needs.Methods FUs were defined as individuals with ≥5 ED attendances/year. We used two large UK datasets: Hospital Episode Statistics (HES, 2016–2019) and the Centre for Urgent and Emergency Care database (CUREd, 2017–2020). Together, these included over 148 000 FUs from 5 million ED users. Latent class analysis (LCA) was used to identify FU subgroups based on attendance patterns, healthcare use and diagnostic characteristics.Results We identified three consistent subgroups (HES and CUREd): (1) low-severity FUs (n=23 034, 43.2%; n=7081, 32.7%); (2) high-intensity FUs with mental health and neurological needs (n=6288, 11.8%; n=3456, 15.9%); (3) older FUs with chronic illness and high inpatient use (n=24 028, 45.0%; n=11 139, 51.4%). Subgroups differed substantially in healthcare utilisation, costs and mortality. A fourth class varied across datasets: in HES, it showed moderate morbidity and complex needs; in CUREd, high morbidity and high-intensity ED use.Discussion This is the first FU study to apply LCA across large-scale, multiyear ED datasets, identifying a potentially universal subgroup structure. Current services focus on a narrow subset of high-intensity users. Additional tailored strategies are needed to address the full spectrum of FU needs.",
  "authors": [
    {
      "affiliations": [
        "Leeds Institute of Health Science, University of Leeds, Leeds, UK"
      ],
      "name": "Richard Mattock"
    },
    {
      "affiliations": [
        "Leeds Institute of Health Science, University of Leeds, Leeds, UK",
        "Lumanity, Sheffield, England, UK"
      ],
      "name": "Chris Bojke"
    },
    {
      "affiliations": [
        "Leeds Institute of Health Science, University of Leeds, Leeds, UK"
      ],
      "name": "Samuel D Relton"
    },
    {
      "affiliations": [
        "Leeds Institute of Health Science, University of Leeds, Leeds, UK"
      ],
      "name": "Akshay Kumar"
    },
    {
      "affiliations": [
        "School of Medicine and Population Health, The University of Sheffield, Sheffield, UK"
      ],
      "name": "Chris Burton"
    },
    {
      "affiliations": [
        "School of Medicine and Population Health, The University of Sheffield, Sheffield, UK"
      ],
      "name": "Suzanne Mason"
    },
    {
      "affiliations": [
        "Leeds Institute of Health Science, University of Leeds, Leeds, UK"
      ],
      "name": "Sonia Saraiva"
    },
    {
      "affiliations": [
        "Leeds Institute of Health Science, University of Leeds, Leeds, UK"
      ],
      "name": "Robert West"
    },
    {
      "affiliations": [
        "Cornwall Partnership NHS Foundation Trust, Bodmin, UK"
      ],
      "name": "William Lee"
    },
    {
      "affiliations": [
        "Department of Health Sciences, University of York, York, UK",
        "University College London Institute of Health Informatics, London, UK"
      ],
      "name": "Christina van der Feltz-Cornelis"
    },
    {
      "affiliations": [
        "Leeds Institute of Health Science, University of Leeds, Leeds, UK"
      ],
      "name": "Catriona Marshall"
    },
    {
      "affiliations": [
        "School of Medicine and Population Health, The University of Sheffield, Sheffield, UK"
      ],
      "name": "Gerlinde Pilkington"
    },
    {
      "affiliations": [
        "School of Medicine and Population Health, The University of Sheffield, Sheffield, UK"
      ],
      "name": "Steven Ariss"
    },
    {
      "affiliations": [
        "Yorkshire Ambulance Service NHS Trust, Wakefield, UK"
      ],
      "name": "Steven Dykes"
    },
    {
      "affiliations": [
        "Leeds Institute of Health Science, University of Leeds, Leeds, UK"
      ],
      "name": "Elspeth Guthrie"
    }
  ],
  "title": "Identifying subgroups of frequent emergency department users: a latent class analysis with linked healthcare utilisation, cost and mortality outcomes in the UK",
  "uid": "245145c0-0f52-503c-a419-a38407bbae42"
}