The review, led by Jingxiang Pan, Chenxinan Ma, Sibo Liu, Marcus Eng Hock Ong, and Fahad Javaid Siddiqui, followed the Arksey and O’Malley scoping review framework and adhered to the PRISMA-ScR reporting checklist, the accepted standard for transparent reporting of scoping reviews. The researchers systematically searched five major bibliographic databases: PubMed, Embase, Web of Science, Scopus, and CINAHL. Their search strategy combined Boolean operators with terms covering emergency departments, overcrowding, and measurement tools, a deliberately broad approach designed to capture every instrument that has ever been proposed or tested for quantifying crowding. After removing duplicates, the team screened 1,974 papers. From that pool, 87 studies met the inclusion criteria, spanning the years 2003 to 2025, with the majority conducted in the United States, a geographic skew that itself says something important about where crowding research has been concentrated and where the evidence gaps remain.

The headline finding is that twelve distinct multidimensional measurement tools have been developed and studied over the past two decades. The list reads like an alphabet soup of emergency medicine acronyms: NEDOCS, the National Emergency Department Overcrowding Scale; PEDOCS, its pediatric counterpart; CEDOCS, designed for community hospitals; EDWIN, the Emergency Department Work Index; the occupancy rate; SONET, the Severely Overcrowded, Overcrowded, and Not Overcrowded Estimation Tool; ICMED, the International Crowding Measure in Emergency Departments; READI, the Real-time Emergency Analysis of Demand Indicators; mSEAL, a modified version of the Skåne Emergency Department Assessment of patient Load; and three further instruments, the ED workload rate, the ED work score, and the Emergency Department Crowding Scale. Each of these tools attempts to compress a chaotic, multidimensional operational reality into a number that administrators and clinicians can act upon.

The technical logic behind these instruments varies considerably, and understanding that variation is central to the review’s contribution. NEDOCS, the most widely recognized of the family, computes a composite score from inputs such as the total number of patients in the department, the longest waiting time for a bed, the number of patients waiting to be seen, the longest time since arrival for waiting patients, and the number of admitted patients holding beds in the department. The resulting score places the department on a categorical ladder from not busy to catastrophically overcrowded. EDWIN, by contrast, takes a ratio-based approach, weighing the number of patients being treated and waiting against the number of physicians on duty and the number of treatment beds, effectively capturing the relationship between demand and staffing capacity in real time. The occupancy rate is the simplest of all: the proportion of occupied treatment spaces relative to total capacity. Its elegance lies in its ease of calculation, but that simplicity is also its weakness, because a department can technically have empty beds while still being functionally gridlocked by boarding patients who cannot be moved upstairs.

Why does multidimensionality matter so much? Because crowding is not a single phenomenon but an emergent property of an entire hospital system. Input throughput describes the arrival of patients; throughput describes their movement through triage, assessment, and treatment; and output describes their discharge or admission to inpatient wards. A department can be crushed at any or all of these stages. A tool that only counts patients in the waiting room will miss the boarding crisis downstream; a tool that only tracks bed occupancy will miss the staffing shortfall that slows every consultation. The multidimensional tools reviewed here attempt to capture several of these dimensions simultaneously, which is precisely why they require more data infrastructure and why their validation is harder. The review found that the most frequently used and most extensively validated instruments were NEDOCS, EDWIN, and the occupancy rate, meaning that a substantial share of the twelve tools have been proposed or trialed but never subjected to rigorous, repeated validation across different settings.

That validation gap carries real clinical and operational consequences. If a hospital administrator in Singapore, Lagos, or rural Ohio wants to know whether their department is dangerously crowded, the answer depends heavily on which tool they choose, and the tools were largely developed in specific contexts with specific assumptions. NEDOCS thresholds, for example, were calibrated in large American tertiary centers, and there is no guarantee that a score of 140 means the same thing in a 30-bed community department as it does in a 300-bed urban trauma center. PEDOCS addresses the pediatric population, where acuity mix and flow dynamics differ from adult medicine. CEDOCS attempts to adapt measurement to community hospital realities, where resources and patient volumes differ again. The review’s authors emphasize that no single tool is universally superior; instead, suitability depends on the alignment between a tool’s data requirements, its underlying assumptions, and the operational realities of the institution deploying it.

The methodological rigor of the review itself deserves attention. The team pre-registered the study on the Open Science Framework, a step that guards against selective reporting and outcome switching. Data extraction focused specifically on each tool’s strengths, weaknesses, and contextual applicability rather than simply cataloging their existence. Study selection was documented with a PRISMA flow diagram, and the extracted data were synthesized narratively, with descriptive visualizations generated in the R statistical environment. Preliminary findings were presented at the Society for Emergency Medicine Singapore Annual Scientific Meeting in February 2025, allowing the work to be scrutinized by the emergency medicine community before formal publication. The article is published open access under a Creative Commons license, meaning the full synthesis is freely available to the hospital administrators and policymakers who most need it.

What emerges from the synthesis is a field at an inflection point. The review identifies persistent obstacles: the absence of a standardized, internationally agreed definition of overcrowding; heavy reliance on tools developed and validated in high-income, particularly American, settings; and the practical burden of data collection, since several instruments require real-time feeds from electronic health records that many hospitals, especially in low- and middle-income countries, cannot easily provide. The authors call for standardized definitions and for flexible, adaptable tools capable of addressing the diverse operational landscapes of emergency departments globally. That adaptability requirement is technically demanding: a tool must be simple enough to compute continuously without manual data entry, sensitive enough to detect meaningful changes in crowding state, and calibrated to thresholds that actually predict the adverse outcomes, such as mortality, treatment delay, and ambulance diversion, that make crowding dangerous in the first place.

The stakes of getting this right extend well beyond hospital walls. Overcrowding is frequently described as a symptom of system-wide failure rather than an emergency department problem per se, because its root causes, inpatient bed shortages, limited primary care access, and aging populations with complex needs, lie upstream and downstream of the department itself. But you cannot manage what you cannot measure, and the review makes clear that the measurement science is still maturing. As health systems worldwide grapple with surging emergency demand, the choice of a crowding metric will shape how resources are allocated, how crises are detected, and how interventions are evaluated. This scoping review provides the most comprehensive map yet of that decision space, and its central message is pragmatic: institutions should select tools that match their needs and context, while the research community works toward the standardized, adaptable instruments that global emergency care still lacks.

Subject of Research: Measurement tools for emergency department overcrowding

Article Title: Multidimensional emergency department overcrowding measurement tools: a scoping review

Article References: Pan, J., Ma, C., Liu, S., Ong, M. E. H., & Siddiqui, F. J. (2026). Multidimensional emergency department overcrowding measurement tools: a scoping review. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15707-4

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15707-4

Keywords: emergency department, overcrowding, NEDOCS, EDWIN, occupancy rate, scoping review, patient flow, crowding metrics, health services research, hospital capacity, validation, PRISMA