ArticleBMC emergency medicine2026
Factors associated with the phenomenon of overcrowding in the emergency department: a retrospective cohort study.
Article in BMC emergency medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- Crowding in real-time: an artificial intelligence-based model to manage crowding in the emergency department (CRAMMED Study).BMC emergency medicine · 2026Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesEmergency departments (EDs) have been confronted with growing demand for several decades. However, the strain on EDs is generally not evenly distributed across the year, as some days are at increased risk of overcrowding compared to others. Identifying the days during which teams are unable to meet actual service demands could be beneficial as a means to avoid, in the most drastic cases, redirecting patients to other care structures (ambulance diversion). The objective of this study was to identify the factors explaining ED overcrowding in a general hospital.
methodsWe conducted a retrospective study at a single emergency department between 1 January 2017 and 31 December 2021. The days with the highest deviation from baseline regarding length of stay were defined as being overcrowded. The factors associated with overcrowding were evaluated using a logistic regression model adjusted for the day’s characteristics.
resultsThe study period comprised 183 overcrowded days and 1643 uncrowded days. The factors associated with the risk of crowding in multivariable analysis were the ED crowding status of the previous day, the number of patients at the beginning of the day, the proportion of patients age 75 or greater, the number of radiological exams per patient, and the number of radiological exams of the skull and brain region. The mitigating factors were the proportion of patients with less urgent needs during triage, an increased proportion of patients needing trauma care, the proportion of patients < 7 years old, weekend days, and the epidemic period following the month of March 2020.
conclusionOur study has highlighted case-mix factors and chronological factors related to the risk of overcrowding. These factors were communicated to hospital management, which allowed the hospital to reassess its operations.
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