Identifying subgroups of frequent emergency department users: a latent class analysis with linked healthcare utilisation, cost and mortality outcomes in the UK.

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 att

SUBMITTER: Mattock R 

PROVIDER: S-EPMC12911696 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature