SynthesisClinical and experimental emergency medicine2026
Emergency department crowding in the modern era: a systematic review (2018-2025).
Synthesis in Clinical and experimental emergency medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Crowding in real-time: an artificial intelligence-based model to manage crowding in the emergency department (CRAMMED Study).BMC emergency medicine · 2026Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study systematically reviews the causes, effects, and potential solutions to emergency department (ED) crowding, with emphasis on challenges amplified by the COVID-19 pandemic. Methods: Following PRISMA guidelines, we searched MEDLINE, CINAHL, and the Web of Science for peer reviewed studies published from January 1, 2018, to January 31, 2025, that investigated ED crowding. Studies were included if they evaluated crowding causes, consequences, or interventions, using metrics such as ED length of stay, boarding, or left without being seen. Four reviewers independently screened titles, abstracts, and full texts. Study quality was assessed using the SIGN critical appraisal tools. This review was registered in PROSPERO (No. CRD420251117676). Results: Of 23,408 studies identified, 226 met inclusion criteria. Most studies were retrospective (83%) and of low (62%) or acceptable (35%) quality. Crowding was primarily driven by input (high patient volumes, limited primary care access), throughput (staffing shortages, laboratory and imaging delays), and output (boarding, late discharges) factors. Adverse effects included increased mortality, treatment delays, prolonged inpatient stays, higher rates of patients leaving without being seen, and reduced patient satisfaction. Effective strategies included provider-in-triage, nurse-initiated orders, and split-flow models. Output-focused interventions, such as active bed management and early discharge protocols, required system-wide coordination. The COVID-19 pandemic shifted patient volumes and led to innovative solutions such as drivethrough clinics and repurposed spaces to alleviate surges. Conclusion: ED crowding is a persistent global issue with significant clinical and operational consequences. While promising interventions exist, high-quality evidence remains limited, underscoring the need for system-level and multifaceted solutions.
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Registered trials
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.