Crowding of the nation's emergency departments (EDs) has become a major health care problem and public issue throughout the past decade.1 In part, this problem has resulted from greatly increased patient demand, but it has also been associated with decreased hospital capacity, and both of these factors have complex causes.2, 3 Regardless of the causes, the effects are increasingly troublesome, including diversion of ambulances, long patient waits, frustration for patients and ED personnel, greater risks for poor outcomes, and unnecessarily high costs.1, 2, 4 A recent survey in California found that all ED directors at university or county hospitals and 96% of those at private or community hospitals reported crowding as a problem, and 28% said it was a daily occurrence.5Capsule Summary
What is already known on this topic
Although emergency department (ED) crowding is a topic of increasing public and professional concern, there is no standardized definition of it and little agreement on what factors may contribute to it.
What question this study addressed
To use a broad-based and thorough expert process to identify all measures of ED and hospital workflow that may be useful in understanding, monitoring, and managing crowding.
What this study adds to our knowledge
A panel of 74 national experts assessed 113 measures, and chose 38 through a discussion and rating process.
How this might change clinical practice
The 38 measures should serve as a resource for research to determine which ones are related to crowding, and eventually to develop tools to predict and modify crowding.
Many factors contribute to ED crowding, but there is relatively little empiric research on this topic. The General Accounting Office recently reported the results of a 2-year nationwide study of the problem.6 They found that the inability to transfer admitted ED patients to inpatient beds was the factor most commonly associated with crowding. Although the contributing reasons for this lack of inpatient beds are complex, the General Accounting Office identified 2 primary causes: (1) hospitals have strong economic incentives to staff only beds that will nearly always be full (which impairs their ability to respond to intermittent surges in demand); and (2) ED patients must compete with other sources of inpatient admissions, many of which generate higher revenue for hospitals (eg, elective surgical procedures, cardiac catheterization). Other suggested causes of crowding include an increase in ED visits and in severity, increased extensive therapy in the ED, difficulty obtaining timely consultations, inefficient surgical scheduling, the nursing shortage, the uninsured, delayed access to ancillary services, reduced availability of subacute and long-term-care beds, increased operational costs, natural fluctuations in demand, reduced hospital and on-call specialist reimbursements, hospital restructuring, and changing patient demographics.1, 5, 7, 8, 9, 10
Schull et al11 assembled an expert panel of 10 front-line key informants from 4 hospitals and an ambulance service in Canada to develop a standard definition of ED crowding and a list of key determinants thought to be most important. They decided on ambulance diversion as an appropriate operational definition and proxy measure of urban ED crowding and identified 25 factors as potentially important determinants of crowding. Whatever the causes, it seems likely that a comprehensive set of measures would help in understanding which factors contribute the most to this situation and to assist with monitoring and managing it. Focusing on some high-priority measures might also stimulate others to create objective data about this problem, which has had much press and public attention but little quantitative information.
Before comprehensive measurement systems for ED crowding could be developed, it was necessary to have a conceptual model for the various factors that may contribute to the problem. Recently, Asplin et al12 have proposed a conceptual model for ED crowding (Figure) that is described in more detail elsewhere. The model is based on engineering principles from queuing theory and compartmental models of flow, dividing ED function into input, throughput, and output stages.13 These concepts have been used extensively in health care to understand and improve hospital bed allocation, operating room staffing, coronary angiography services, primary care access for appointments, and a variety of medical systems, as well as in clinical toxicology, pharmacokinetics, and the like.14, 15, 16, 17 Similar concepts were also suggested specifically for ED patient flow by Coats and Michalis18 and by Litvak et al.9
The input-throughput-output model permits most factors affecting use and crowding to be grouped into 1 of these 3 stages.12 Thus, input or demand for ED services depends on the volume of ill and injured people in the community and the capability of the rest of the health care system to address the needs of individuals not requiring emergency care. Throughput includes factors that affect the efficiency of an ED to cope with its input, ranging from ED beds and staffing to the efficiency of ancillary services and consultant access. Finally, output factors include the ability of the inpatient system to admit patients requiring hospital care and of the ambulatory care system to provide timely postdischarge care (Figure).
With such a model, addressing the measurement issue comprehensively becomes possible. The goal of this project was to develop measures that could be used for monitoring, planning, and research. This article describes the development of these measures, using the input-throughput-output conceptual model as a way of grouping and applying them for various uses.