The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
The association between hospital overcrowding and mortality among patients admitted via Western Australian emergency departments
Abstract
Objective: To examine the relationship between hospital and emergency department (ED) occupancy, as indicators of hospital overcrowding, and mortality after emergency admission. Design: Retrospective analysis of 62 495 probabilistically linked emergency hospital admissions and death records. Setting: Three tertiary metropolitan hospitals between July 2000 and June 2003. Participants: All patients 18 years or older whose first ED attendance resulted in hospital admission during the study period. Main outcome measures: Deaths on days 2, 7 and 30 were evaluated against an Overcrowding Hazard Scale based on hospital and ED occupancy, after adjusting for age, diagnosis, referral source, urgency and mode of transport to hospital. Results: There was a linear relationship between the Overcrowding Hazard Scale and deaths on Day 7 (r = 0.98; 95% CI, 0.79–1.00). An Overcrowding Hazard Scale > 2 was associated with an increased Day 2, Day 7 and Day 30 hazard ratio for death of 1.3 (95% CI, 1.1–1.6), 1.3 (95% CI, 1.2–1.5) and 1.2 (95% CI, 1.1–1.3), respectively. Deaths at 30 days associated with an Overcrowding Hazard Scale > 2 compared with one of < 3 were undifferentiated with respect to age, diagnosis, urgency, transport mode, referral source or hospital length of stay, but had longer ED durations of stay (risk ratio per hour of ED stay, 1.1; 95% CI, 1.1–1.1; P < 0.001) and longer physician waiting times (risk ratio per hour of ED wait, 1.2; 95% CI, 1.1–1.3; P = 0.01). Conclusions: Hospital and ED overcrowding is associated with increased mortality. The Overcrowding Hazard Scale may be used to assess the hazard associated with hospital and ED overcrowding. Reducing overcrowding may improve outcomes for patients requiring emergency hospital admission.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Crossing the Quality Chasm: A New Health System for the 21st Century
Committee on Quality of Health Care in America (2002) · Journal For Healthcare Quality · doi:10.1111/j.1945-1474.2002.tb00463.x · Cited by 8,483
Reason, J. (1990) · doi:10.1017/cbo9781139062367 · Cited by 5,108
Holman, C. D. J., Bass, A. J., Rouse, I. L., & Hobbs, M. S. T. (1999) · Australian and New Zealand Journal of Public Health · doi:10.1111/j.1467-842x.1999.tb01297.x · Cited by 1,037
Probabilistic linkage of large public health data files
Jaro, M. A. (1995) · Statistics in Medicine · doi:10.1002/sim.4780140510 · Cited by 782
Dynamics of bed use in accommodating emergency admissions: stochastic simulation model
Bagust, A., Place, M., & Posnett, J. W. (1999) · BMJ · doi:10.1136/bmj.319.7203.155 · Cited by 475
The Effect of Hospital Occupancy on Emergency Department Length of Stay and Patient Disposition
Forster, A. J., Stiell, I. G., Wells, G. A., Lee, A. J., & van Walraven, C. (2003) · Academic Emergency Medicine · doi:10.1111/j.1553-2712.2003.tb00029.x · Cited by 446
The Business Case For Quality: Case Studies And An Analysis
Leatherman, S., Berwick, D., Iles, D., Lewin, L. S., Davidoff, F., Nolan, T., & Bisognano, M. (2003) · Health Affairs · doi:10.1377/hlthaff.22.2.17 · Cited by 365
Fatovich, D. M. (2005) · Emergency Medicine Journal · doi:10.1136/emj.2004.018002 · Cited by 269
Emergency department length of stay independently predicts excess inpatient length of stay
Liew, D., Liew, D., & Kennedy, M. P. (2003) · Medical Journal of Australia · doi:10.5694/j.1326-5377.2003.tb05676.x · Cited by 261
Decreased health care quality associated with emergency department overcrowding
MIRÓ, Ò., ANTONIO, M. T., JIMÉNEZ, S., DE DIOS, A., SÁNCHEZ, M., BORRÁS, A., & MILLÁ, J. (1999) · European Journal of Emergency Medicine · doi:10.1097/00063110-199906000-00003 · Cited by 250
Cited by
Emergency department crowding: A systematic review of causes, consequences and solutions
Morley, C., Unwin, M., Peterson, G. M., Stankovich, J., & Kinsman, L. (2018) · PLOS ONE · doi:10.1371/journal.pone.0203316 · Cited by 1,386
The Effect of Emergency Department Crowding on Clinically Oriented Outcomes
Bernstein, S. L., Aronsky, D., Duseja, R., Epstein, S., Handel, D., Hwang, U., McCarthy, M., John McConnell, K., Pines, J. M., Rathlev, N., et al. (2009) · Academic Emergency Medicine · doi:10.1111/j.1553-2712.2008.00295.x · Cited by 1,147
Forero, R., Nahidi, S., De Costa, J., Mohsin, M., Fitzgerald, G., Gibson, N., McCarthy, S., & Aboagye-Sarfo, P. (2018) · BMC Health Services Research · doi:10.1186/s12913-018-2915-2 · Cited by 688
Optimizing Emergency Department Front-End Operations
Wiler, J. L., Gentle, C., Halfpenny, J. M., Heins, A., Mehrotra, A., Mikhail, M. G., & Fite, D. (2010) · Annals of Emergency Medicine · doi:10.1016/j.annemergmed.2009.05.021 · Cited by 339
ED overcrowding is associated with an increased frequency of medication errors
Kulstad, E. B., Sikka, R., Sweis, R. T., Kelley, K. M., & Rzechula, K. H. (2010) · The American Journal of Emergency Medicine · doi:10.1016/j.ajem.2008.12.014 · Cited by 306
Metadata
- Authors
- Sprivulis, P. C., Da Silva, J., Jacobs, I. G., Jelinek, G. A., & Frazer, A. R. L.
- Venue
- Medical Journal of Australia
- Publisher
- AMPCo
- Published
- 2006-03
- Volume
- 184
- Issue
- 5
- Pages
- 208-212
- ISSN
- 0025-729X (ISSN-L)
- 1326-5377
- OpenAlex
- W4256436395
- Cited by
- 759
- References
- 18
- FWCI
- 28.47
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The association between hospital overcrowding and mortality among patients admitted via Western Australian emergency departments. https://app.cochat.ai/papers/10.5694/j.1326-5377.2006.tb00203.x
- The paper
- Sprivulis, P. C., Da Silva, J., Jacobs, I. G., Jelinek, G. A., & Frazer, A. R. L. (2006). The association between hospital overcrowding and mortality among patients admitted via Western Australian emergency departments. Medical Journal of Australia. https://doi.org/10.5694/j.1326-5377.2006.tb00203.x
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.