HEALTH POLICY AND CLINICAL PRACTICE/REVIEW ARTICLE

Systematic Review of Emergency Department Crowding:

Causes, Effects, and Solutions
Nathan R. Hoot, PhD From the Department of Biomedical Informatics (Hoot, Aronsky) and the Department of Emergency
Dominik Aronsky, MD, PhD Medicine (Aronsky), Vanderbilt University Medical Center, Nashville, TN.

Emergency department (ED) crowding represents an international crisis that may affect the quality and
access of health care. We conducted a comprehensive PubMed search to identify articles that (1)
studied causes, effects, or solutions of ED crowding; (2) described data collection and analysis
methodology; (3) occurred in a general ED setting; and (4) focused on everyday crowding. Two
independent reviewers identified the relevant articles by consensus. We applied a 5-level quality
assessment tool to grade the methodology of each study. From 4,271 abstracts and 188 full-text
articles, the reviewers identified 93 articles meeting the inclusion criteria. A total of 33 articles studied
causes, 27 articles studied effects, and 40 articles studied solutions of ED crowding. Commonly
studied causes of crowding included nonurgent visits, “frequent-flyer” patients, influenza season,
inadequate staffing, inpatient boarding, and hospital bed shortages. Commonly studied effects of
crowding included patient mortality, transport delays, treatment delays, ambulance diversion, patient
elopement, and financial effect. Commonly studied solutions of crowding included additional
personnel, observation units, hospital bed access, nonurgent referrals, ambulance diversion,
destination control, crowding measures, and queuing theory. The results illustrated the complex,
multifaceted characteristics of the ED crowding problem. Additional high-quality studies may provide
valuable contributions toward better understanding and alleviating the daily crisis. This structured
overview of the literature may help to identify future directions for the crowding research agenda. [Ann
Emerg Med. 2008;52:126-136.]

0196-0644/$-see front matter

Copyright © 2008 by the American College of Emergency Physicians.
doi:10.1016/j.annemergmed.2008.03.014

INTRODUCTION whereby an ED advises ambulances to transport patients to

The international crisis of emergency department (ED) other nearby hospitals when possible.13 The authors found that
crowding has received considerable attention, both in political1,2 ambulance diversion is a frequent reaction to ED crowding,
and lay3-7 venues. In 1986 the Emergency Medical Treatment which may carry consequences including delayed patient
and Labor Act mandated that all patients who present to an ED transport and lost hospital revenue.
in the United States must receive a medical screening As noted by the Institute of Medicine, understanding the
examination, regardless of their ability to pay.8 The unique role causes, effects, and solutions of the ED crowding problem is
of the ED has prompted some to call it the safety net of the important.2 However, to the best of our knowledge, no previous
systematic literature review has summarized this research. The
health care system.9,10 Unfortunately, the increasing problem of
objective of this review was to describe the scientific literature
crowding has strained this safety net to the “breaking point,”
on ED crowding from the perspective of causes, effects, and
according to a recent report by the Institute of Medicine.2,11
solutions.
Escalation of the ED crowding problem has prompted
researchers to investigate a number of scientific questions, some MATERIALS AND METHODS
of which have been summarized by systematic literature reviews. Search Strategy
One review characterized the diverse ways in which researchers We adopted the definition of the word “crowding” proposed
have defined “overcrowding.”12 The authors found that the by the American College of Emergency Physicians14:
term has been frequently defined with various factors inside and “Crowding occurs when the identified need for emergency
outside of the ED and hospital. They concluded that the services exceeds available resources for patient care in the
crowding research agenda would benefit from a consistent emergency department, hospital, or both.” From this definition,
definition. Another review characterized ambulance diversion, we interpreted crowding to be a phenomenon that involves the

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Hoot & Aronsky Systematic Review of Emergency Department Crowding

interaction of supply and demand. We defined the scope of this the patient load. Within the groups representing causes, effects,
review to include articles that met 4 criteria: (1) they studied and solutions of ED crowding, we further categorized articles
causes, effects, or solutions of crowding as a primary objective; according to common themes that emerged among the primary
(2) they studied crowding on an empirical basis, with a findings during the data abstraction phase.
description of the data collection and analysis methodology; (3)
they studied crowding in the context of general emergency Assessment of Study Quality
medicine, rather than a specialty service such as psychiatric To assess the methodological quality of the studies, we
emergency medicine; and (4) they studied everyday crowding, applied a previously described 5-level instrument.15,16 Although
reflecting a focus on daily surge rather than exceptional it was originally developed to judge clinical trials, we applied the
circumstances; in other words, they did not study crowding instrument consistently to clinical trials, descriptive studies, and
associated with disaster events. surveys by using the following adaptation: Quality level 1
We identified a broad set of PubMed (MEDLINE) search included prospective studies that studied a clearly defined
terms to encompass each facet of the inclusion criteria. The outcome measure with a random or consecutive sample that was
search involved free text and Medical Subject Headings (MeSH) large enough to achieve narrow confidence intervals and diverse
terms. We described the concept of “ED” by the following enough to suggest generalizability of the findings. Quality level
search terms: Emergency Medical Services[MeSH] OR 2 included prospective studies that were more limited in terms
Emergency Medicine[MeSH] OR “emergency.” We described of sample size or generalizability. Quality level 3 included
the concept of “crowding” by the following search terms: retrospective studies that otherwise would have satisfied the
Crowding[MeSH] OR “crowding” OR “crowded” OR criteria for quality level 1 or 2. Quality level 4 included studies
“overcrowding” OR “overcrowded” OR “diversion” OR that sampled by convenience or other techniques that were
“divert” OR “congestion” OR “surge” OR “capacity” OR prone to introduce bias. Quality level 5 included studies that
“crisis” OR “crises” OR “occupancy.” We queried MEDLINE lacked a clearly defined or validated outcome measure. We did
on June 6, 2006, with the Boolean union of the above queries, not score articles that lacked necessary methodological details
restricting the search to English-language publications. for the quality instrument.

Study Selection
Two reviewers (N.R.H. and D.A.) independently examined RESULTS
the results returned by the MEDLINE search to identify The MEDLINE query returned 4,271 abstracts. The
potentially relevant abstracts. Articles that clearly did not meet reviewers identified 188 abstracts for full-text retrieval, of which
one or more of the review criteria according to the title and 93 articles satisfied the criteria for inclusion in the review. A
abstract were not considered further. When the 2 reviewers flow diagram of the selection process is presented in the Figure
disagreed, a consensus was reached through discussion. We 1. The rate of reviewer agreement during the abstract screening
retrieved full-text articles for the potentially relevant abstracts. phase, before consensus discussion, was 93% overall, 76%
The same 2 reviewers independently examined the full-text among included articles, and 94% among excluded articles. The
articles to determine which studies met all 4 of the inclusion ␬ statistic for chance-corrected agreement between the 2
criteria. Disagreements were again resolved through discussion reviewers was 0.47 (95% confidence interval: 0.42 to 0.52),
to reach a final consensus set of articles that met the review denoting moderate agreement.17
criteria. We found that quality level 1 contained 14 articles, quality
level 2 contained 12 articles, quality level 3 contained 47
Data Collection and Processing articles, quality level 4 contained 10 articles, and quality level 5
We used a data extraction form (Appendix E1, available contained 6 articles. Four articles were not scored because of
online at http://www.annemergmed.com) to record information inadequate reporting of methodology. The primary findings of
about the methods and results of each relevant article, including all articles are summarized briefly in the following sections. The
study design, study setting, study population, sample size, methods and results of each high-quality prospective study are
independent variables, dependent variables, and primary described in Table 1. A total of 33 articles studied causes, 27
findings. We assigned the articles to nonexclusive groups articles studied effects, and 40 articles studied solutions of ED
according to whether they investigated causes, effects, or crowding. This sum exceeds 93 because some articles were
solutions of ED crowding. We attempted to represent the assigned to multiple categories as necessary.
intentions of the original authors when assigning each article to
a group. For example, an issue such as ambulance diversion may Causes
be considered a cause, effect, or solution of ED crowding, Three general themes existed among the causes of ED
depending on the perspective of each study: it might be a cause crowding: input factors, throughput factors, and output factors.
of crowding at nearby institutions to which patients are These themes correspond to a conceptual framework for
diverted, it might be an effect of crowding at a single institution studying ED crowding.18 Input factors reflected sources and
of interest, or it might be a solution of crowding by reducing aspects of patient inflow. Throughput factors reflected

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Systematic Review of Emergency Department Crowding Hoot & Aronsky

Stockholm experienced a 21% increase in ED visits during a

4-year span, far exceeding the population growth of 4.5%
during the same period; the authors attributed this to 2 hospital
closures that caused the ED to become more responsible for
primary care delivery.29 One study estimated that excess patient
volume prompted 71% of ambulance diversion episodes, and
excess patient acuity prompted 15% of ambulance diversion
episodes.30 Although recently discharged inpatients accounted
for just 3% of total visits to one ED, they had longer lengths of
stay and more frequent hospital admissions than other
patients.31 California EDs that were located in neighborhoods
of lower socioeconomic status had increased waiting times,
estimated to be 10 minutes longer per $10,000 reduction in per
capita income.32
Throughput factors. We identified inadequate staffing to be
a commonly studied throughput factor that may cause
Figure 1. Study selection process. Articles were defined to crowding.
be relevant if they (1) studied causes, effects, or solutions Three articles discussed inadequate staffing: A point
of ED crowding as a primary objective; (2) provided a
prevalence study of crowding found that the average nurse was
description of the data collection and analysis; (3) took
place in a general adult or pediatric ED setting; and (4)
caring for 4 patients simultaneously, and the average physician
focused on everyday crowding instead of disaster-related was caring for 10 patients simultaneously.33 A study in
crowding. Both phases of study selection involved a California showed that lower staffing levels of physicians and
consensus between 2 independent reviewers. triage nurses predisposed patients to wait longer for care.32 By
contrast, a time series analysis indicated that, after controlling
for other factors, ambulance diversion was not associated with
bottlenecks within the ED. Output factors reflected bottlenecks
physician and nurse staffing levels.34
in other parts of the health care system that might affect the
Three articles discussed other aspects of throughput factors:
ED. The commonly studied causes of crowding are summarized
During a 9-year period, the number of California EDs
in Table 2.
decreased by 12%, whereas the number of ED beds increased by
Input factors. We identified nonurgent visits, so-called
frequent-flyer patients, and the influenza season to be 16%.35 This increase may not have been sufficient, considering
commonly studied input factors that may cause crowding. that the number of visits and critical visits per ED increased by
Four articles considered nonurgent visits: Three studies found 27% and 59%, respectively, during the same period. The
that low-acuity ED patients frequently sought nonurgent care in training background of the attending physician in charge of an
the ED, and their reasons for doing so included insufficient or ED has been independently associated with patients leaving
untimely access to primary care.19-21 However, one analysis without being seen.36 The use of ancillary services, including
suggested that visits by patients with nonurgent complaints were computed tomographic (CT) scanning and other procedures,
not associated with the most severe crowding at large hospitals.22 prolonged the ED length of stay among surgical critical care
Two articles studied frequent-flyer patients: One report patients.37
found that frequent visitors, defined by 4 or more annual visits, Output factors. We identified inpatient boarding and
accounted for 14% of the total ED visits.23 Moreover, these hospital bed shortages to be commonly studied output factors
patients generally did not have urgent complaints and exhibited that may cause crowding.
Andersen’s24 “need factors” for health care. A similar report Five articles studied inpatient boarding: One study found that
found that the 500 most frequent users of one ED accounted half of EDs in the United States reported extended boarding times
for 8% of total visits, and 29% of these visits might have been for patients in the ED.38 A point prevalence study found that 22%
appropriate for primary care.25 of all ED patients were boarding at one time.33 One academic ED
Three articles investigated the influenza season: Los Angeles delivered 154 patient-days of care to critically ill patients during a
County hospitals recorded a 4- to 7-fold increase in ambulance 1-year period.39 Patients experiencing access block, defined by
diversion during the peak 4 weeks of flu season compared with boarding time exceeding 8 hours, was associated with increased
other times of the year.26 In Toronto, every 10 local cases of flu diversion, waiting times, and occupancy level in an Australian
resulted in a 1.5% increase in the fraction of ED visitors who were ED.40 A time series analysis showed that the number of boarding
elderly flu patients.27 The same group in Toronto calculated that patients was independently associated with the frequency of
every 100 local cases of flu resulted in an increase of 2.5 hours per ambulance diversion.34
week of ambulance diversion.28 Six articles examined hospital bed shortages: A study of
Four articles examined other aspects of input factors: English accident and emergency trusts found a strong

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Table 1. Methods and results of each high-quality prospective study.

Article Focus Design Sample Outcome Measures Primary Findings
Quality level 1
Andersson, Cause Prospective 16,246 patients Waiting time, ED length ED visits increased from 247.8 to 287.7 per 1,000
200129 observational during 3 y of stay population, waiting time increased by 8.2 min for
nonreferred patients
Bayley, Effect Prospective 904 patients Marginal cost 825 patients boarded more than 3 h, opportunity cost of
200570 cohort $204 per boarding patient, annual total of $168,300
for hospital
Burt, 200664 Effect Survey 405 EDs Ambulance diversion 16.2 million ambulance transports in United States,
501,000 diversion events annually, 70% from large
EDs, 85% response rate
Eckstein, Effect Prospective 21,240 incidents Time to unload patient 1 in 8 transports took at least 15 min to unload patient,
200472 observational of out of increasing over time, more frequent from January to
service March
Fromm, Cause Prospective 17,900 visits ED length of stay 8.5% of ED patients were critically ill, remained in ED for
199339 cohort 145.3 min; 154 patient-days of critical care were
administered
Haines, Solution Prospective 704 incidents of Hospital admission rate, Paramedic decision to not transport pediatric patients led
200695 case series non-transport patient satisfaction to a 2.4% admission rate, no deaths, good patient
satisfaction
Lambe, Cause Prospective 1,798 patients Waiting time Waiting times averaged 56 min, each $10,000 decrease
200332 observational in local per-capita income increased waiting times by
10.1 min
Neely, 199456 Effect Prospective 481 patients Transport distance, time Diverted patients traveled 5.0 to 11.6 min longer and 1.3
observational to 4.6 miles further than nondiverted patients
Patel, 200691 Solution Before-after 3y Ambulance diversion Community-wide diversion policy decreased diversion
intervention hours by 74%, despite increases of 6.5% in census and
8.8% in admissions
Shah, 200694 Solution Before-after 2 mo Ambulance diversion Destination-control program reduced diversion hours by
intervention 41% at a university hospital and 61% at a community
hospital
Shaw, 199876 Solution Before-after 48,669 children Elopement, waiting time Additional personnel called on 32% of days, waiting time
intervention decreased by 15 min, elopement rate decreased by
37%
Solberg, Solution Delphi method 74 experts Magnitude estimation 38 consensus measures of patient demand and
2003105 complexity; ED capacity, efficiency, and workload;
hospital efficiency and capacity
Vilke, 200492 Solution Before-after 2y Ambulance diversion Standardized diversion guidelines reduced diversion hours
intervention from 4,007 to 1,079 and diverted patients from 1,320
to 322
Weiss, 200499 Solution Prospective 336 observations Staff assessments of NEDOCS predicted crowding assessments with R2 of
observational crowding 0.49, reduced model retained 88% of accuracy
Quality level 2
Baker, 199167 Effect Prospective 397 patients Triage assessment, self- 46% of patients who left without being seen needed
cohort reported health immediate medical attention, 11% were hospitalized in
status, hospitalization the next week
Bindman, Effect Prospective 700 patients Waiting time, self- 15% of patients left without being seen, 86% because of
199169 cohort reported health status waiting time, doubled risk of worse pain or disease
severity
Bucheli, Solution Before-after 360 patients ED length of stay Additional physician during evening shift decreased length
200474 intervention of stay from 176⫾137 to 141⫾86 min for outpatients
Fatovich, Cause Prospective 141 incidents of Reason for ambulance 30.4% of ambulance diversion incidents caused by entry
200330 observational diversion diversion block, 13.6% by access block, 27.2% by both, 15.2%
by high acuity
Grumbach, Cause, Survey 700 patients Reason for visit, 45% of patients cited barriers to primary care, 13% had
199319 solution willingness to seek urgent complaints, 38% would trade visit for primary
alternate care care appointment
Kelen, 200178 Solution Before-after 1,589 patients Elopement, ambulance Acute care unit decreased patient elopement from 10.1%
intervention diversion to 5.0% and ambulance diversion from 6.7 to 2.8 h per
100 patients
Michelen, Solution Before-after 711 patients ED utilization Frequent-flyer patients decreased ED usage after primary
200696 intervention care referral, health education, and counseling, P⬍.01
for each

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Table 1. (Continued) Methods and results of each high-quality prospective study.

Article Focus Design Sample Outcome Measures Primary Findings
103
Raj, 2006 Solution Prospective 128 observations Staff assessments of Mean difference of 3.47 NEDOCS units between NEDOCS
observational crowding and staff assessments, 95% agreement limits of
–46.52 to 53.43
Reeder, Solution Prospective 221 observations Staff assessments of READI bed ratio differed by 0.245, acuity ratio by 0.131
2003100 observational crowding between periods of normal and excess demand
Schneider, Cause, Survey 250 EDs Operating status at 4.2 patients per nurse, 9.7 patients per physician, 11%
200333 effect index time of EDs diverting, and 22% of patients boarding, 36%
response rate
Vilke, 200490 Solution Before-after 3 wk Ambulance diversion Frequency of ambulance diversion decreased from 27.7
intervention to 0 h when nearby hospital stopped diverting
ambulances
Washington, Solution Randomized 156 patients Self-reported health Patients with 3 symptom complexes deferred to next-day
200285 controlled status, care utilization care had similar health status and care utilization at
trial follow-up
READI, Real-time Emergency Analysis of Demand Indicators; NEDOCS, National Emergency Department Overcrowding Scale.

correlation between ED treatment time and hospital patients to receive timely care at their preferred institutions.
occupancy.41 A period of widespread hospital restructuring in Provider losses reflected consequences borne by the health care
Toronto independently increased the rate of severe crowding system itself. The commonly studied effects of crowding are
from 0.5% to 6% of the time.42 Length of stay in one ED summarized in Table 3.
increased substantially when the hospital occupancy levels Adverse outcomes. We identified patient mortality to be a
exceeded 90%.43 A survey of Korean EDs linked high hospital commonly studied adverse outcome of crowding.
occupancy levels to ED crowding.44 A study in Portland found Four articles focused on patient mortality: One study found a
that a decrease in the number of hospital beds was strongly significant increase in mortality associated with weekly ED
associated with an increase in ambulance diversion.45 Another volume.52 High occupancy in one Australian ED was estimated
study estimated that a hospital closure would affect the nearest to cause 13 patient deaths per year.53 Another study associated a
ED by increasing ambulance diversion by 56 hours per month combined measure of hospital and ED crowding with an
for 4 months.46 increased risk of mortality at 2, 7, and 30 days after hospital
Additional themes. Five surveys and interviews identified admission.54 In Houston, a statistically insignificant trend was
factors that health care providers and other stakeholders perceive found for higher mortality among trauma patients who were
to be important causes of ED crowding: increasing patient admitted during ambulance diversion.55
volume and acuity, shortages of treatment areas, shortages of Reduced quality. We identified transport delays and
nursing staff, delays in ancillary services, boarding inpatients, treatment delays to be commonly studied effects of crowding
and hospital bed shortages.47-51 pertaining to reduced quality.
Four articles examined transport delays: Ambulance diversion
Effects was shown to increase transport time and distance in 2
Four general themes existed among the effects of ED studies.56,57 A study focused on cardiac patients found that the
crowding: adverse outcomes, reduced quality, impaired access, 90th percentile of transport time increased when multiple local
and provider losses. Adverse outcomes reflected health-related hospitals were on diversion.58 During 2 years in which
patient endpoints. Reduced quality reflected benchmarks of the crowding was exacerbated in Toronto, the 90th percentile of
care delivery process. Impaired access reflected the ability of

Table 3. Commonly studied effects of ED crowding.

Table 2. Commonly studied causes of ED crowding.
Effect of Crowding References
Cause of Crowding References
Adverse outcomes
Input factors Patient mortality 52-55
Nonurgent visits 19-22 Reduced quality
Frequent-flyer patients 23,25 Transport delays 56-59
Influenza season 26-28 Treatment delays 60-63
Throughput factors Impaired access
Inadequate staffing 32-34 Ambulance diversion 33,64
Output factors Patient elopement 36,65-69
Inpatient boarding 33,34,38-40 Provider losses
Hospital bed shortages 41-46 Financial effect 70,71

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transport time increased by 11%.59 Table 4. Commonly studied solutions of ED crowding.

Four articles investigated treatment delays: Patients who Solution of Crowding References
arrived at one ED during crowded periods waited 30 minutes
Increased resources
longer for an ED bed.60 Crowding was associated with increased Additional personnel 74-76
door-to-needle time for patients with suspected myocardial Observation units 77-80
infarction.61 High ED occupancy levels were associated with Hospital bed access 81,82
delayed pain assessment and lower likelihood of pain Demand management
Nonurgent referrals 19,85-87
documentation among hip fracture patients.62 A trial with
Ambulance diversion 88-92
negative results found no increase in the time to head CT Destination control 93,94
among patients with suspected stroke when a trauma evaluation Operations research
occurred simultaneously.63 Crowding measures 98-105
Impaired access. We identified ambulance diversion and Queuing theory 106,107
patient elopement to be commonly studied effects of crowding
pertaining to impaired access.
Two articles focused on ambulance diversion: A national deployment of additional physical, personnel, and supporting
survey found that approximately 501,000 ambulance diversions resources. Demand management reflected methods to
occurred in the United States during 1 year, and approximately redistribute patients or encourage appropriate utilization.
70% of these were from large EDs.64 A point-prevalence study Operations research reflected crowding measures and offline
of ED crowding found that 11% of US EDs were change management techniques. The commonly studied
simultaneously diverting ambulances.33 solutions of crowding are summarized in Table 4.
Six articles characterized patient elopement: Patients were Increased resources. We identified additional personnel,
more likely to leave without being seen when ED occupancy observation units, and hospital bed access to be commonly
exceeded 100% of the total capacity.36 In one study, the rate of studied solutions of crowding involving increased resources.
patients leaving without being seen closely correlated with Three articles studied additional personnel: One described a
waiting times.65 The rate of patients leaving one ED without permanent increase in the number of physicians during a busy
being seen correlated well with a crowding regression model.66 shift, reducing the outpatient length of stay by 35 minutes.74 A
Among patients who left without being seen, 46% needed rural hospital, which previously did not have an attending
urgent medical attention, and 11% were hospitalized within a physician present during the night shift, found that the presence
week.67 Patients frequently cited long waiting times as a reason of an attending physician improved several throughput measures
for leaving without being seen, and 60% of them sought other of ED crowding.75 One hospital activated reserve personnel as
medical care within a week.68 Patients who left the ED without needed during the viral epidemic season, reducing the waiting
being seen were twice as likely to report worsened health time by 15 minutes and the rate of patients leaving without
problems.69 being seen by 37%.76
Provider losses. We identified financial effect to be a Four articles investigated observation units: One short-stay
commonly studied provider loss of crowding. medical unit reduced the length of stay for outpatients with
Two articles calculated financial effect: One study estimated chest pain and asthma exacerbation.77 Another study found that
that the hospital lost $204 in potential revenue per patient with an ED-managed acute care unit decreased ambulance diversion
an extended boarding time.70 Another study found that patients by 40% and halved the rate of patients leaving without being
who boarded in the ED longer than a day also stayed in the seen.78 A hospital reported that the addition of an acute medical
hospital longer, increasing costs by an estimated $6.8 million unit reduced the median number of boarding patients from 14
during 3 years.71 to 8 during a 2-year period.79 One study proposed a hybrid
Two articles considered other aspects of provider losses: A observation unit, which was designed to use resources effectively
study found that during 1 in 8 patient transports, the and substantially decreased the length of stay for scheduled
ambulance could not unload the patient promptly at the ED, procedure patients.80
putting it out of service for 15 minutes or more.72 A survey of Two articles considered hospital bed access: After increasing
Canadian emergency physicians found that job dissatisfaction the number of critical care beds from 47 to 67, ambulance
was closely related to the perceived scarcity of resources.73 diversion at one hospital decreased by 66%.81 A natural
Additional themes. Three surveys identified outcomes that experiment resulting from a period of industrial action, leading
ED directors perceive to be major effects of crowding: death, to improved hospital bed access for an ED, resulted in
delayed care, unnecessary procedures, and extended pain.47-49 significant decreases in occupancy levels and waiting times.82
Two articles examined other aspects of increased resources:
Solutions One study increased both space and staffing through an ED
Three general themes existed among the solutions of ED reorganization, which resulted in the improvement of several
crowding: increased resources, demand management, and crowding outcomes.83 Another study attempted to reduce the
operations research. Increased resources reflected the potential bottleneck of ancillary services by implementing point-

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Systematic Review of Emergency Department Crowding Hoot & Aronsky

of-care laboratory testing, which decreased the length of stay by Department Overcrowding Scale (NEDOCS) explained 49% of
41 minutes.84 the variation in physician and nurse assessments of crowding.99
Demand management. We identified nonurgent referrals, The Real-time Emergency Analysis of Demand Indicators were
ambulance diversion, and destination control to be commonly designed for real-time monitoring of ED operations, although
studied solutions of crowding involving demand management. they did not correlate with providers’ opinions on crowding.100
Four studies tested nonurgent referrals: A survey of ED The Work Score predicted ambulance diversion at its institution
patients found that 38% would swap their ED visit for a of origin with area under the receiver operating characteristic
primary care appointment within 72 hours.19 A randomized, curve of 0.89.101 A comparative validation, which used staff
controlled trial focused on 3 common symptom complexes and assessments of crowding as the outcome, estimated the area
found that they may be deferred for next-day primary care under the receiver operating characteristic curve of the EDWIN
without worsening self-reported health status on follow-up.85 to be 0.80 and of the NEDOCS to be 0.83.102 However, an
When following up nonurgent patients who were triaged to external validation of the NEDOCS in Australia concluded that
receive care elsewhere, one group found that there were no it was not useful, according to Bland-Altman and ␬ statistics.103
major adverse outcomes, and 42% of the patients received same- A sampling form consisting of 7 operational measures was
day care elsewhere.86 A similar study found that 94% of shown to correlate well with staff assessments of crowding.104 A
nonurgent patients who were referred to community-based care panel of experts described 38 consensus operational measures
reported that their condition was better or unchanged.87 that may be used to assess crowding levels.105
Five studies investigated ambulance diversion: By one Two studies used queuing theory: One group illustrated the
calculation, ambulance diversion decreased the rate of ability of discrete event simulation to model ED operations, and
ambulance arrivals by 30% to 50%.88 A similar calculation they tested its applicability by analyzing a proposed triage
found that “red-alert” ambulance diversion reduced the arrival scheme.106 A similar study described a separate discrete event
rate by 0.4 per hour.89 When one hospital committed to simulation and studied the effects of physician utilization on
avoiding ambulance diversion for 1 week, the need for diversion patient waiting times.107
at a nearby hospital was almost eliminated.90 Standardized Additional themes. Five studies described multifaceted
administrative interventions that could not be classified
diversion criteria in Sacramento, targeted to decrease “round-
separately: A broad intervention consisting of 51 actions
robin” crowding, reduced the rate of ambulance diversion by
reduced ED length of stay and ambulance diversion in
74% despite increased patient volume.91 San Diego
Melbourne.108 One network deployed several interventions,
implemented a standardized policy for initiating ambulance
tuned for the individual needs of 4 hospitals, and reduced the
diversion among all local hospitals and reduced ambulance
amount of ambulance diversion by 25% and 34% in
diversion by 75%.92
consecutive years.109 A group of hospitals in Rochester deployed
Two studies proposed destination control: The use of
several interventions, and they reported that the most effective
Internet-accessible operating information to redistribute
interventions occurred outside the ED.110 Another study
ambulances reduced the need for diversion from 1,788 hours to
reported interventions, including more physicians, improved
1,138 hours in one network.93 Another study described a
ancillary services, and changes in hospital policy, that reduced
physician-directed ambulance destination control initiative that length of stay by half.111 One hospital deployed a multipronged
reduced diversion by 41%.94 intervention, which involved a short-stay unit, additional
Three studies considered other aspects of demand physicians, and an early warning system, to deal with holiday
management: A trial of paramedic-initiated nontransport found demand surges.112
that 2.4% of nontransported pediatric patients were later
admitted to the hospital.95 Three social interventions designed LIMITATIONS
for frequent visitors, which included education and counseling, This study has a number of limitations that merit discussion.
were associated with decreased ED utilization.96 Another study First, we may not have captured every article that studied
targeted frequent users with case management interventions, but causes, effects, and solutions of ED crowding. We limited the
the rate of ED utilization was unchanged.97 search to English-language articles, so any relevant articles
Operations research. The studies within the operations published in foreign languages were not included. We avoided
research theme did not describe direct solutions to ED searching the grey literature with a general purpose internet
crowding; however, they proposed to support solutions through query, and we did not hand-search the references of included
improved business intelligence. We identified crowding articles. If used, these 2 techniques might have impaired the
measures and queuing theory to be commonly studied solutions reproducibility of our review. We searched a single database;
to crowding according to operations research. moreover, it is possible that our search terms did not capture all
Eight studies described crowding measures: The Emergency aspects of the topic. The MeSH vocabulary contains a single
Department Work Index (EDWIN) associated well with term related to crowding, so we supplemented the search with a
ambulance diversion and less well with secondary outcome large set of free-text keywords. We attempted to minimize the
measures at its institution of origin.98 The National Emergency likelihood of missed articles by applying a broad search strategy.

132 Annals of Emergency Medicine Volume , .  : August 

Hoot & Aronsky Systematic Review of Emergency Department Crowding

We also used a conservative approach during the abstract operational changes involve the entire department, rather than
screening phase, retrieving the full-text articles for all abstracts individual patients who may be randomized to experimental
that could not be clearly excluded. The moderate ␬ value may and control groups.85 We believe that the crowding literature
be explained because one author was more conservative than the would benefit from more randomized controlled trials
other in marking abstracts for full-text retrieval. This issue was examining patient-focused interventions.
identified and resolved during the consensus discussion. We Although several studies investigated nonurgent and
believe our methodology captured the majority of pertinent frequent-flyer visits, relatively little evidence suggests they
articles. independently cause ED crowding.19-23,25 This notion is
Second, the diversity of methodology, outcome measures, supported by recent literature.113 More evidence is available to
and reporting among the original articles rendered aspects of identify inpatient boarding and other hospital-related factors as
this review difficult. We attempted to describe the primary causes of ED crowding.33,34,38-46 These studies corroborate with
findings of each study as consistently as possible, noting the successful interventions that reduced crowding by altering the
effect sizes of each study when feasible and in other cases operation of hospital and community services other than the
describing the nature of the findings in more qualitative terms. ED.78,79,81,82,90-93 We believe that the crowding literature
In some cases, our descriptions were limited according to the would benefit from more studies that analyze the ED in the
reporting of the original articles. The brief summaries that we context of integrated hospital processes and focus on
provide do not capture the full complexity of each study, so our multicenter community networks rather than single institutions.
review is intended to guide interested readers to the original The results suggest that standard operations management
cited articles. We did not conduct a formal meta-analysis, tools, such as queuing theory, have only recently been applied in
because of the breadth of study designs and endpoints an effort to improve ED patient flow.106,107 We are aware of
considered. We refrain from making strong conclusions about few previous reports describing such applications in the ED
which factors are most important because these would be based setting.114 By contrast, these tools were adopted much earlier by
primarily on judgment rather than numeric inference. industries like airlines and manufacturing. This lag is analogous
Third, the classification of studies into groups and themes to the gap between basic science and clinical science, which
was partly subjective, so objections may be made regarding how translational research aims to address. A result of queuing theory
particular articles were categorized. We acknowledge that there states that a system with varying inputs and fixed capacity will
may be no clearly correct taxonomy for grouping this diverse set
become congested for transient periods.115 By consequence,
of articles. For instance, measurement tools and queuing models
permanent increases in resources may be neither efficient nor
would not reduce ED crowding unless paired with an
adequate to address crowding, given the fluctuating demand.
intervention plan. Regardless, we have classified these articles as
The review includes 1 study demonstrating the feasibility of
solutions, insofar as the original authors intended their research
deploying additional resources on demand to alleviate ED
to support crowding interventions. Our intention in using this
crowding.76 We believe that the crowding literature would
trichotomy of causes, effects, and solutions was to provide a
benefit from studies that apply standard management research
structured overview of the relevant literature, which we hope
techniques to ED operations and investigate ways to alter
benefits the reader.
resource availability dynamically according to demand.
DISCUSSION When considered as a whole, the body of literature
A substantial body of literature exists describing the causes, demonstrates that ED crowding is a local manifestation of a
effects, and solutions of ED crowding. The major themes systemic disease. The causes of ED crowding involve a complex
among the causes of crowding included nonurgent visits, network of interwoven processes ranging from hospital
frequent-flyer patients, influenza season, inadequate staffing, workflow to viral epidemics. The effects of ED crowding are
inpatient boarding, and hospital bed shortages. The major numerous and adverse. Various targeted solutions to crowding
themes among the effects of crowding included patient have been shown to be effective, and further studies may
mortality, transport delays, treatment delays, ambulance demonstrate new innovations. This broad overview of the
diversion, patient elopement, and financial effect. The major current research may help to inform the future research agenda
themes among the solutions of crowding included additional and, subsequently, to protect the fragile safety net of the health
personnel, observation units, hospital bed access, nonurgent care system.
referrals, ambulance diversion, destination control, crowding
measures, and queuing theory. Supervising editor: David J. Magid, MD, MPH
The quality instrument that we used indicated that a large Funding and support: By Annals policy, all authors are required
number of high-quality articles have been published about ED to disclose any and all commercial, financial, and other
crowding.15,16 We identified a total of 26 prospective studies relationships in any way related to the subject of this article,
and 47 retrospective studies that met the criteria for the 3 that might create any potential conflict of interest. See the
highest quality levels. We noted a scarcity of randomized Manuscript Submission Agreement in this issue for examples
controlled trials in this review, perhaps because many ED of specific conflicts covered by this statement. Dr. Hoot was

Volume , .  : August  Annals of Emergency Medicine 133

Systematic Review of Emergency Department Crowding Hoot & Aronsky

supported by National Library of Medicine grant LM07450-02 18. Asplin BR, Magid DJ, Rhodes KV, et al. A conceptual model of
and National Institute of General Medical Studies grant T32 emergency department crowding. Ann Emerg Med. 2003;42:
GM07347. The research was also supported by National 173-180.
Library of Medicine grant R21 LM009002-01. The authors 19. Grumbach K, Keane D, Bindman A. Primary care and public
declare no conflicts of interest pertaining to the publication of emergency department overcrowding. Am J Public Health. 1993;
83:372-378.
this work.
20. Afilalo J, Marinovich A, Afilalo M, et al. Nonurgent emergency
Publication dates: Received for publication July 16, 2007. department patient characteristics and barriers to primary care.
Revision received January 26, 2008. Accepted for publication Acad Emerg Med. 2004;11:1302-1310.
March 11, 2008. Available online April 23, 2008. 21. Howard MS, Davis BA, Anderson C, et al. Patients’ perspective
on choosing the emergency department for nonurgent medical
Earn CME Credit: Continuing Medical Education for this article care: a qualitative study exploring one reason for overcrowding.
is available at: www.ACEP-EMedHome.com. J Emerg Nurs. 2005;31:429-435.
22. Sprivulis P, Grainger S, Nagree Y. Ambulance diversion is not
Reprints not available from the authors.
associated with low acuity patients attending Perth metropolitan
Address for correspondence: Nathan R. Hoot, PhD, 400 emergency departments. Emerg Med Australas. 2005;17:11-15.
Eskind Biomedical Library, 2209 Garland Avenue, Nashville, 23. Huang JA, Tsai WC, Chen YC, et al. Factors associated with
TN 37232; 615-936-3720, fax 615-936-1427; E-mail frequent use of emergency services in a medical center. J
Formos Med Assoc. 2003;102:222-228.
nathan.hoot@vanderbilt.edu.
24. Andersen RM. Revisiting the behavioral model and access to
medical care: does it matter? J Health Soc Behav. 1995;36:1-
REFERENCES 10.
1. Yamane K. Hospital Emergency Departments: Crowded 25. Dent AW, Phillips GA, Chenhall AJ, et al. The heaviest repeat
Conditions Vary Among Hospitals and Communities. Washington, users of an inner city emergency department are not general
DC: US General Accounting Office; 2003. GAO-03-460. practice patients. Emerg Med (Fremantle). 2003;15:322-329.
2. Committee on the Future of Emergency Care in the United States 26. Glaser CA, Gilliam S, Thompson WW, et al. Medical care
Health System. Hospital-Based Emergency Care: At the Breaking capacity for influenza outbreaks, Los Angeles. Emerg Infect Dis.
Point. Washington, DC: National Academies Press; 2006. 2002;8:569-574.
3. Gibbs N. Do you want to die? The crisis in emergency care is 27. Schull MJ, Mamdani MM, Fang J. Influenza and emergency
taking its toll on doctors, nurses, and patients. Time. May 28, department utilization by elders. Acad Emerg Med. 2005;12:
1990:58-65. 338-344.
4. Barrero J. Hospitals get orders to reduce crowding in emergency 28. Schull MJ, Mamdani MM, Fang J. Community influenza
rooms. New York Times. January 24, 1989:1-2. outbreaks and emergency department ambulance diversion. Ann
5. Goldberg C. Emergency crews worry as hospitals say, “No Emerg Med. 2004;44:61-67.
vacancy.” New York Times. December 17, 2000:39 29. Andersson G, Karlberg I. Lack of integration, and seasonal
6. Orenstein JB. State of emergency. Washington Post. April 22, variations in demand explained performance problems and
2001:B1 waiting times for patients at emergency departments: a 3 years
7. Jeffrey NA. Who’s crowding emergency rooms? Right now it’s evaluation of the shift of responsibility between primary and
managed-care patients. Wall Street Journal. July 20, 1999:B1 secondary care by closure of two acute hospitals. Health Policy.
8. Emergency Medical Treatment and Active Labor Act, established 2001;55:187-207.
under the Consolidated Omnibus Budget Reconciliation Act of 30. Fatovich DM, Hirsch RL. Entry overload, emergency department
1985. Pub L No. 99-272, 42USC 1395dd (1986). overcrowding, and ambulance bypass. Emerg Med J. 2003;20:
9. Asplin BR. Tying a knot in the unraveling health care safety net. 406-409.
Acad Emerg Med. 2001;8:1075-1079.
31. Baer RB, Pasternack JS, Zwemer FL Jr. Recently discharged
10. American Academy of Pediatrics Committee on Pediatric
inpatients as a source of emergency department overcrowding.
Emergency Medicine.Overcrowding crisis in our nation’s
Acad Emerg Med. 2001;8:1091-1094.
emergency departments: is our safety net unraveling?
32. Lambe S, Washington DL, Fink A, et al. Waiting times in
Pediatrics. 2004;114:878-888.
California’s emergency departments. Ann Emerg Med. 2003;41:
11. Kellermann AL. Crisis in the emergency department. N Engl
35-44.
J Med. 2006;355:1300-1303.
33. Schneider SM, Gallery ME, Schafermeyer R, et al. Emergency
12. Hwang U, Concato J. Care in the emergency department: how
crowded is overcrowded? Acad Emerg Med. 2004;11:1097-1101. department crowding: a point in time. Ann Emerg Med. 2003;42:
13. Pham JC, Patel R, Millin MG, et al. The effects of ambulance 167-172.
diversion: a comprehensive review. Acad Emerg Med. 2006;13: 34. Schull MJ, Lazier K, Vermeulen M, et al. Emergency department
1220-1227. contributors to ambulance diversion: a quantitative analysis. Ann
14. American College of Emergency Physicians. Crowding. Ann Emerg Med. 2003;41:467-476.
Emerg Med. 2006;47:585. 35. Lambe S, Washington DL, Fink A, et al. Trends in the use and
15. Sackett DL, Haynes RB, Guyatt GH, et al. Clinical Epidemiology: capacity of California’s emergency departments, 1990-1999.
A Basic Science for Clinical Medicine. 2nd ed. Boston, MA: Little Ann Emerg Med. 2002;39:389-396.
Brown; 1991. 36. Polevoi SK, Quinn JV, Kramer NR. Factors associated with
16. Wang CS, FitzGerald JM, Schulzer M, et al. Does this dyspneic patients who leave without being seen. Acad Emerg Med. 2005;
patient in the emergency department have congestive heart 12:232-236.
failure? JAMA. 2005;294:1944-1956. 37. Davis B, Sullivan S, Levine A, et al. Factors affecting ED length-
17. Landis JR, Koch GG. The measurement of observer agreement of-stay in surgical critical care patients. Am J Emerg Med. 1995;
for categorical data. Biometrics. 1977;33:159-174. 13:495-500.

134 Annals of Emergency Medicine Volume , .  : August 

Hoot & Aronsky Systematic Review of Emergency Department Crowding

38. Andrulis DP, Kellermann A, Hintz EA, et al. Emergency 58. Schull MJ, Morrison LJ, Vermeulen M, et al. Emergency
departments and crowding in United States teaching hospitals. department gridlock and out-of-hospital delays for cardiac
Ann Emerg Med. 1991;20:980-986. patients. Acad Emerg Med. 2003;10:709-716.
39. Fromm RE Jr, Gibbs LR, McCallum WG, et al. Critical care in the 59. Schull MJ, Morrison LJ, Vermeulen M, et al. Emergency
emergency department: a time-based study. Crit Care Med. department overcrowding and ambulance transport delays for
1993;21:970-976. patients with chest pain. CMAJ. 2003;168:277-283.
40. Fatovich DM, Nagree Y, Sprivulis P. Access block causes 60. Liu S, Hobgood C, Brice JH. Impact of critical bed status on
emergency department overcrowding and ambulance diversion in emergency department patient flow and overcrowding. Acad
Perth, Western Australia. Emerg Med J. 2005;22:351-354. Emerg Med. 2003;10:382-385.
41. Cooke MW, Wilson S, Halsall J, et al. Total time in English 61. Schull MJ, Vermeulen M, Slaughter G, et al. Emergency
accident and emergency departments is related to bed department crowding and thrombolysis delays in acute
occupancy. Emerg Med J. 2004;21:575-576. myocardial infarction. Ann Emerg Med. 2004;44:577-585.
42. Schull MJ, Szalai JP, Schwartz B, et al. Emergency department 62. Hwang U, Richardson LD, Sonuyi TO, et al. The effect of
overcrowding following systematic hospital restructuring: trends emergency department crowding on the management of pain in
at twenty hospitals over ten years. Acad Emerg Med. 2001;8: older adults with hip fracture. J Am Geriatr Soc. 2006;54:270-
1037-1043. 275.
43. Forster AJ, Stiell I, Wells G, et al. The effect of hospital 63. Chen EH, Mills AM, Lee BY, et al. The impact of a concurrent
occupancy on emergency department length of stay and patient trauma alert evaluation on time to head computed tomography
disposition. Acad Emerg Med. 2003;10:127-133. in patients with suspected stroke. Acad Emerg Med. 2006;13:
44. Hwang JI. The relationship between hospital capacity 349-352.
characteristics and emergency department volumes in Korea. 64. Burt CW, McCaig LF, Valverde RH. Analysis of ambulance
Health Policy. 2006;79:274-283. transports and diversions among US emergency departments.
45. Warden CR, Bangs C, Norton R, et al. Temporal trends in Ann Emerg Med. 2006;47:317-326.
ambulance diversion in a mid-sized metropolitan area. Prehosp 65. Kyriacou DN, Ricketts V, Dyne PL, et al. A 5-year time study
analysis of emergency department patient care efficiency. Ann
Emerg Care. 2003;7:109-113.
Emerg Med. 1999;34:326-335.
46. Sun BC, Mohanty SA, Weiss R, et al. Effects of hospital
66. Weiss SJ, Ernst AA, Derlet R, et al. Relationship between the
closures and hospital characteristics on emergency department
National ED Overcrowding Scale and the number of patients who
ambulance diversion, Los Angeles County, 1998 to 2004. Ann
leave without being seen in an academic ED. Am J Emerg Med.
Emerg Med. 2006;47:309-316.
2005;23:288-294.
47. Derlet RW, Richards JR. Emergency department overcrowding in
67. Baker DW, Stevens CD, Brook RH. Patients who leave a public
Florida, New York, and Texas. South Med J. 2002;95:846-849.
hospital emergency department without being seen by a
48. Derlet R, Richards J, Kravitz R. Frequent overcrowding in U.S.
physician. Causes and consequences. JAMA. 1991;266:1085-
emergency departments. Acad Emerg Med. 2001;8:151-155.
1090.
49. Richards JR, Navarro ML, Derlet RW. Survey of directors of
68. Rowe BH, Channan P, Bullard M, et al. Characteristics of
emergency departments in California on overcrowding. West
patients who leave emergency departments without being seen.
J Med. 2000;172:385-388.
Acad Emerg Med. 2006;13:848-852.
50. Clark K, Normile LB. Delays in implementing admission orders
69. Bindman AB, Grumbach K, Keane D, et al. Consequences of
for critical care patients associated with length of stay in
queuing for care at a public hospital emergency department.
emergency departments in six mid-Atlantic states. J Emerg Nurs. JAMA. 1991;266:1091-1096.
2002;28:489-495. 70. Bayley MD, Schwartz JS, Shofer FS, et al. The financial burden
51. Bazzoli GJ, Brewster LR, Liu G, et al. Does U.S. hospital of emergency department congestion and hospital crowding for
capacity need to be expanded? Health Aff (Millwood). 2003;22: chest pain patients awaiting admission. Ann Emerg Med. 2005;
40-54. 45:110-117.
52. Miro O, Antonio MT, Jimenez S, et al. Decreased health care 71. Krochmal P, Riley TA. Increased health care costs associated
quality associated with emergency department overcrowding. Eur with ED overcrowding. Am J Emerg Med. 1994;12:265-266.
J Emerg Med. 1999;6:105-107. 72. Eckstein M, Chan LS. The effect of emergency department
53. Richardson DB. Increase in patient mortality at 10 days crowding on paramedic ambulance availability. Ann Emerg Med.
associated with emergency department overcrowding. Med J 2004;43:100-105.
Aust. 2006;184:213-216. 73. Rondeau KV, Francescutti LH. Emergency department
54. Sprivulis PC, Da Silva JA, Jacobs IG, et al. The association overcrowding: the impact of resource scarcity on physician job
between hospital overcrowding and mortality among patients satisfaction. J Healthc Manag. 2005;50:327-340.
admitted via Western Australian emergency departments. Med J 74. Bucheli B, Martina B. Reduced length of stay in medical
Aust. 2006;184:208-212. emergency department patients: a prospective controlled study
55. Begley CE, Chang Y, Wood RC, et al. Emergency department on emergency physician staffing. Eur J Emerg Med. 2004;11:29-
diversion and trauma mortality: evidence from Houston, Texas. 34.
J Trauma. 2004;57:1260-1265. 75. Donald KJ, Smith AN, Doherty S, et al. Effect of an on-site
56. Neely KW, Norton RL, Young GP. The effect of hospital resource emergency physician in a rural emergency department at night.
unavailability and ambulance diversions on the EMS system. Rural Remote Health. 2005;5:380.
Prehosp Disaster Med. 1994;9:172-176. 76. Shaw KN, Lavelle JM. VESAS: a solution to seasonal
57. Redelmeier DA, Blair PJ, Collins WE. No place to unload: a fluctuations in emergency department census. Ann Emerg Med.
preliminary analysis of the prevalence, risk factors, and 1998;32:698-702.
consequences of ambulance diversion. Ann Emerg Med. 1994; 77. Bazarian JJ, Schneider SM, Newman VJ, et al. Do admitted
23:43-47. patients held in the emergency department impact the

Volume , .  : August  Annals of Emergency Medicine 135

Systematic Review of Emergency Department Crowding Hoot & Aronsky

throughput of treat-and-release patients? Acad Emerg Med. 96. Michelen W, Martinez J, Lee A, et al. Reducing frequent flyer
1996;3:1113-1118. emergency department visits. J Health Care Poor Underserved.
78. Kelen GD, Scheulen JJ, Hill PM. Effect of an emergency 2006;17(1 suppl):59-69.
department (ED) managed acute care unit on ED overcrowding 97. Lee KH, Davenport L. Can case management interventions
and emergency medical services diversion. Acad Emerg Med. reduce the number of emergency department visits by frequent
2001;8:1095-1100. users? Health Care Manag (Frederick). 2006;25:155-159.
79. Moloney ED, Bennett K, O’Riordan D, et al. Emergency 98. Bernstein SL, Verghese V, Leung W, et al. Development and
department census of patients awaiting admission following validation of a new index to measure emergency department
reorganisation of an admissions process. Emerg Med J. 2006; crowding. Acad Emerg Med. 2003;10:938-942.
23:363-367. 99. Weiss SJ, Derlet R, Arndahl J, et al. Estimating the degree of
80. Ross MA, Naylor S, Compton S, et al. Maximizing use of the emergency department overcrowding in academic medical
emergency department observation unit: a novel hybrid design. centers: results of the National ED Overcrowding Study
Ann Emerg Med. 2001;37:267-274. (NEDOCS). Acad Emerg Med. 2004;11:38-50.
81. McConnell KJ, Richards CF, Daya M, et al. Effect of increased 100. Reeder TJ, Burleson DL, Garrison HG. The overcrowded
ICU capacity on emergency department length of stay and emergency department: a comparison of staff perceptions. Acad
ambulance diversion. Ann Emerg Med. 2005;45:471-478. Emerg Med. 2003;10:1059-1064.
82. Dunn R. Reduced access block causes shorter emergency 101. Epstein SK, Tian L. Development of an emergency department
department waiting times: an historical control observational work score to predict ambulance diversion. Acad Emerg Med.
study. Emerg Med (Fremantle). 2003;15:232-238. 2006;13:421-426.
83. Miro O, Sanchez M, Espinosa G, et al. Analysis of patient flow in 102. Weiss SJ, Ernst AA, Nick TG. Comparison of the National
the emergency department and the effect of an extensive Emergency Department Overcrowding Scale and the Emergency
reorganisation. Emerg Med J. 2003;20:143-148. Department Work Index for quantifying emergency department
84. Lee-Lewandrowski E, Corboy D, Lewandrowski K, et al. crowding. Acad Emerg Med. 2006;13:513-518.
Implementation of a point-of-care satellite laboratory in the 103. Raj K, Baker K, Brierley S, et al. National Emergency
emergency department of an academic medical center. Impact Department Overcrowding Study tool is not useful in an
on test turnaround time and patient emergency department
Australian emergency department. Emerg Med Australas. 2006;
length of stay. Arch Pathol Lab Med. 2003;127:456-460.
18:282-288.
85. Washington DL, Stevens CD, Shekelle PG, et al. Next-day care
104. Weiss SJ, Arndahl J, Ernst AA, et al. Development of a site
for emergency department users with nonacute conditions. A
sampling form for evaluation of ED overcrowding. Med Sci
randomized, controlled trial. Ann Intern Med. 2002;137:707-
Monit. 2002;8:CR549-553.
714.
105. Solberg LI, Asplin BR, Weinick RM, et al. Emergency department
86. Derlet RW, Nishio D, Cole LM, et al. Triage of patients out of the
crowding: consensus development of potential measures. Ann
emergency department: three-year experience. Am J Emerg Med.
Emerg Med. 2003;42:824-834.
1992;10:195-199.
106. Connelly LG, Bair AE. Discrete event simulation of emergency
87. Diesburg-Stanwood A, Scott J, Oman K, et al. Nonemergent ED
department activity: a platform for system-level operations
patients referred to community resources after medical
research. Acad Emerg Med. 2004;11:1177-1185.
screening examination: characteristics, medical condition after
107. Chin L, Fleisher G. Planning model of resource utilization in an
72 hours, and use of follow-up services. J Emerg Nurs. 2004;
30:312-317. academic pediatric emergency department. Pediatr Emerg Care.
88. Lagoe RJ, Hunt RC, Nadle PA, et al. Utilization and impact of 1998;14:4-9.
ambulance diversion at the community level. Prehosp Emerg 108. Cameron P, Scown P, Campbell D. Managing access block. Aust
Care. 2002;6:191-198. Health Rev. 2002;25:59-68.
89. Scheulen JJ, Li G, Kelen GD. Impact of ambulance diversion 109. Lagoe RJ, Kohlbrenner JC, Hall LD, et al. Reducing ambulance
policies in urban, suburban, and rural areas of Central Maryland. diversion: a multihospital approach. Prehosp Emerg Care. 2003;
Acad Emerg Med. 2001;8:36-40. 7:99-108.
90. Vilke GM, Brown L, Skogland P, et al. Approach to decreasing 110. Schneider S, Zwemer F, Doniger A, et al. Rochester, New York:
emergency department ambulance diversion hours. J Emerg a decade of emergency department overcrowding. Acad Emerg
Med. 2004;26:189-192. Med. 2001;8:1044-1050.
91. Patel PB, Derlet RW, Vinson DR, et al. Ambulance diversion 111. Cardin S, Afilalo M, Lang E, et al. Intervention to decrease
reduction: the Sacramento solution. Am J Emerg Med. 2006;24: emergency department crowding: does it have an effect on
206-213. return visits and hospital readmissions? Ann Emerg Med. 2003;
92. Vilke GM, Castillo EM, Metz MA, et al. Community trial to 41:173-185.
decrease ambulance diversion hours: the San Diego county 112. Salazar A, Corbella X, Sanchez JL, et al. How to manage the ED
patient destination trial. Ann Emerg Med. 2004;44:295-303. crisis when hospital and/or ED capacity is reaching its limits.
93. Sprivulis P, Gerrard B. Internet-accessible emergency Report about the implementation of particular interventions
department workload information reduces ambulance diversion. during the Christmas crisis. Eur J Emerg Med. 2002;9:79-80.
Prehosp Emerg Care. 2005;9:285-291. 113. Schull MJ, Kiss A, Szalai JP. The effect of low-complexity
94. Shah MN, Fairbanks RJ, Maddow CL, et al. Description and patients on emergency department waiting times. Ann Emerg
evaluation of a pilot physician-directed emergency medical Med. 2007;49:257-264.
services diversion control program. Acad Emerg Med. 2006;13: 114. Siddharthan K, Jones WJ, Johnson JA. A priority queuing model
54-60. to reduce waiting times in emergency care. Int J Health Care
95. Haines CJ, Lutes RE, Blaser M, et al. Paramedic initiated non- Qual Assur. 1996;9:10-16.
transport of pediatric patients. Prehosp Emerg Care. 2006;10: 115. Gross D, Harris CM. Fundamentals of Queuing Theory. New
213-219. York, NY: Wiley; 1985.

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 #: _____________ Author: _______________________ Year: _________

Quality: ________ Reason: ________________________

__ ____________________

Design: ________________________
_______________________________________

Institution: _____________________________________________________________

Volume: __________ Acuity System: ___________ Trauma Level: _________

Population: ________________________
____________________________________

Sample: _______________________________________________________________

Endpoint: ______________________________________________________________

Analysis: ______________________________________________________________

Causes: _______________________________________________________________

Effects: _______________________________________________________________

Solutions: _____________________________________________________________

Notes: ________________________________________________________________
Appendix E1. Data extraction form

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