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.
Citations
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A Global and Local SHAP-Driven Interpretable Framework for Early Hospital Admission Prediction With Machine Learning at Emergency Department Triage Adam E Brown, Chance W Marostica, Nicole R Hodgson, Wayne A Martini Cureus.2026;[Epub] CrossRef
Crowding in real-time: an artificial intelligence-based model to manage crowding in the emergency department (CRAMMED Study) E. E. Schippers, S. P. Willemsen, L. A. M. Collée, K. L. M. Koenraadt, S. Schol-Gelok BMC Emergency Medicine.2026;[Epub] CrossRef
Objective Cardiogenic syncope can present as a seizure. The distinction between seizure disorder and cardiogenic syncope can only be made if one considers the diagnosis. Our main objective was to identify whether patients presenting with a chief complaint (reason for visit) as seizure or syncope received an electrocardiogram in the emergency department across all age groups.
Methods We conducted a secondary analysis of data collected in the 2010 to 2014 National Hospital Ambulatory Medical Care Survey comparing patients presenting with a chief complaint of syncope versus seizure to determine likelihood of getting an evaluation for possible life threatening cardiovascular disease. The primary endpoint was receiving an electrocardiogram in the emergency department; secondary endpoint was receiving cardiac biomarkers.
Results There was a total of 144,094 patient encounters. Of these visits, 1,553 had syncope and 1,470 had seizure (60.3% vs. 44.2% female, 19.9% vs. 29.0% non-white). After adjusting for age, sex, mode of arrival and insurance, patients with syncope were more likely to receive an electrocardiogram compared to patients with seizure (odds ratio, 10.86; 95% confidence interval [CI], 8.52 to 13.84). This was true across all age groups (0 to 18 years, 56% vs. 7.5%; 18 to 44 years, 60% vs. 27%; 45 to 64 years, 82% vs. 41%; ≥65 years, 85% vs. 68%; P<0.01 for all). Car- diac biomarkers were also obtained more frequently in adult patients with syncope patients (18 to 44 years, 17.5% vs. 10.5%; 45 to 64 years, 33.8% vs. 21.4%; ≥65 years, 47.1% vs. 32.3%; P<0.01 for all).
Conclusion Patients evaluated in the emergency department for syncope received an electrocar- diogram and cardiac biomarkers more frequently than those that had seizure.
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Classification Model for Epileptic Seizure Using Simple Postictal Laboratory Indices Sun Jin Jin, Taesic Lee, Hyun Eui Moon, Eun Seok Park, Sue Hyun Lee, Young Il Roh, Dong Min Seo, Won-Joo Kim, Heewon Hwang Journal of Clinical Medicine.2023; 12(12): 4031. CrossRef
Application of a Head-Up Tilt Table Test in Differentiation Between Epilepsy and Syncope in Children Meisam Babaei, Mohammad Mehdi Nasehi, Mohammad Reza Khalilian, Maryam Rasoulinezhad, Hossein Tavallai, Fargol Farahmandi Journal of Comprehensive Pediatrics.2022;[Epub] CrossRef
Commentary on “Syncope in the Emergency Department: A Guide for Clinicians” Jennifer L. White Journal of Emergency Nursing.2021; 47(2): 208. CrossRef
Retrospective Diagnosis of Congenital Long QT Syndrome in a Patient With Febrile Syncope Kory S. London, Jessica Zegre-Hemsey, Melanie Root, Alex Kleinmann, Jennifer L. White Journal of Emergency Nursing.2020; 46(2): 214. CrossRef