Evidence map›Paper›PMID 30161242›Full record

SynthesisPloS one2018

Emergency department crowding: A systematic review of causes, consequences and solutions.

Claire Morley, Maria Unwin, Gregory M Peterson, Jim Stankovich, Leigh Kinsman

2 registry-linked trialsAbstract readSystematic Review
In one paragraph

Synthesis in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 592 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
592citing papers in PubMed, 9 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

NCT05252182 completednot on this mapstarted 2022, after this paper: background citation

Comprehensive Geriatric Assessment in the Emergency Department: a Prospective Cohort Study of Clinical and Process Outcomes

TypeobservationalSponsorUniversity of LimerickRan2022 to 2023Enrolled133ConditionsFrailty
NCT07532564 completednot on this mapstarted 2022, after this paper: background citation

Cost of Emergency Department Boarding for Hospitalized Patients in a Statewide Medical System

TypeobservationalSponsorUniversity of Maryland, BaltimoreRan2022 to 2025Enrolled30,486ConditionsStroke (CVA) or TIA, Diabetes, Asthma (Diagnosis), COPD (Chronic Obstructive Pulmonary Disease)
3 · Its place in the literature

Who cites it

592 citing papers in PubMed, 9 syntheses or guidelines pooled it.

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  17. Patient-Reported Outcome Measures in the Emergency Department: A Scoping Review.Journal of the American College of Emergency Physicians open · 2026
    Review
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532 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Claire MorleySchool of Health Sciences, College of Health and Medicine, University of Tasmania, Hobart, Tasmania, Australia.ORCID 0000-0001-9721-9225
Maria UnwinSchool of Health Sciences, College of Health and Medicine, University of Tasmania, Hobart, Tasmania, Australia.ORCID 0000-0002-8431-3164
Gregory M PetersonSchool of Medicine, College of Health and Medicine, University of Tasmania, Hobart, Tasmania, Australia.
Jim StankovichSchool of Medicine, College of Health and Medicine, University of Tasmania, Hobart, Tasmania, Australia.
Leigh KinsmanSchool of Health Sciences, College of Health and Medicine, University of Tasmania, Hobart, Tasmania, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEmergency department crowding is a major global healthcare issue. There is much debate as to the causes of the phenomenon, leading to difficulties in developing successful, targeted solutions.

aimThe aim of this systematic review was to critically analyse and summarise the findings of peer-reviewed research studies investigating the causes and consequences of, and solutions to, emergency department crowding.

methodThe Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. A structured search of four databases (Medline, CINAHL, EMBASE and Web of Science) was undertaken to identify peer-reviewed research publications aimed at investigating the causes or consequences of, or solutions to, emergency department crowding, published between January 2000 and June 2018. Two reviewers used validated critical appraisal tools to independently assess the quality of the studies. The study protocol was registered with the International prospective register of systematic reviews (PROSPERO 2017: CRD42017073439).

resultsFrom 4,131 identified studies and 162 full text reviews, 102 studies met the inclusion criteria. The majority were retrospective cohort studies, with the greatest proportion (51%) trialling or modelling potential solutions to emergency department crowding. Fourteen studies examined causes and 40 investigated consequences. Two studies looked at both causes and consequences, and two investigated causes and solutions.

conclusionsThe negative consequences of ED crowding are well established, including poorer patient outcomes and the inability of staff to adhere to guideline-recommended treatment. This review identified a mismatch between causes and solutions. The majority of identified causes related to the number and type of people attending ED and timely discharge from ED, while reported solutions focused on efficient patient flow within the ED. Solutions aimed at the introduction of whole-of-system initiatives to meet timed patient disposition targets, as well as extended hours of primary care, demonstrated promising outcomes. While the review identified increased presentations by the elderly with complex and chronic conditions as an emerging and widespread driver of crowding, more research is required to isolate the precise local factors leading to ED crowding, with system-wide solutions tailored to address identified causes.

Indexed as

Emergency Medical ServicesEmergency Service, HospitalCrowdingDelivery of Health CareHumans

Identifiers

PMID30161242
PMCPMC6117060

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.