Cited by 117Emergency and Acute Care StudiesClinical Laboratory Practices and Quality ControlHealthcare Operations and Scheduling Optimization

The Effect of Laboratory Testing on Emergency Department Length of Stay: A Multihospital Longitudinal Study Applying a Cross‐classified Random‐effect Modeling Approach

Open access
Li, Ling, Georgiou, Andrew, Vecellio, Elia, Eigenstetter, Alex, Toouli, George, Wilson, Roger, Westbrook, Johanna I.·2015·Academic Emergency Medicine

Abstract

Objectives: The objective was to examine the relationship between laboratory testing (including test volume and turnaround time [ TAT ]) and emergency department ( ED ) length of stay ( LOS ), using linked patient‐level data from four hospitals across 4 years. Methods: This was a retrospective, multisite cohort study of patients presenting to any one of four ED s in New South Wales, Australia, during a 2‐month period (August and September) in 2008, 2009, 2010, and 2011. Data from ED information systems were linked to laboratory test data. A cross‐classified random‐effect modeling approach was applied to identify factors affecting ED LOS , taking into account the correlation between patients' presentations at the same hospital and/or in the same calendar year. Number of test order episodes (tests ordered at one point in time during the ED stay) and TAT (time from laboratory order receipt to result available) were examined. Results: As the number of test order episodes increased, so did the duration of patient ED LOS (p < 0.0001). For every five additional tests ordered per test order episode, the median ED LOS increased by 10 minutes (2.9%, p < 0.0001); each 30‐minute increase in TAT was, on average, associated with a 5.1% (17 minutes; p < 0.0001) increase in ED LOS , after adjustment for other factors. Patients presenting to the ED at night (7 p.m. to 7 a.m.) had longer stays than those presenting during the daytime, although the median TAT s at nights were shorter than those during the daytime. Conclusions: Laboratory testing has a direct effect on patients' LOS in ED . Laboratory TAT , number of testing episodes, and test volume influence ED LOS . Targeted increases of ED resources and staffing after‐hours may also contribute to reductions in ED LOS .

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1111/acem.12565

Cites

30 of 30 references verified0 citation errors · 0 not checkable

Statistics

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.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Emergency Severity Index level, specialty, destination after ED visit, and number of out-of-range tests were included as proxies for acuity level, which was identified as a confounder in previous studies.

    “The Emergency Severity Index level, the specialty, the destination after the ED visit and the number of out-of-range tests were included as proxies for the acuity level, which was identified as a confounder in previous studies [11, 12].”

    From Shorter laboratory turnaround time is associated with shorter emergency department length of stay: a retrospective cohort study (2022) · cites this paper as [12]

    The Methods (Data Analysis; page unavailable) include triage category and ED mode of separation as covariates, and the Discussion reports that both affect ED length of stay. These correspond broadly to acuity and destination after the ED visit. The paper does not identify acuity explicitly as a confounder or support the specific use of Emergency Severity Index level, specialty, and number of out-of-range tests as proxies. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. [23]Institute of Medicine. Committee on the Future of Emergency Care in the United States Health System. Hospital‐based Emergency Care: At the Breaking Point. Washington DC: National Academies Press, 2007.

Cited by

Sorted by citations

Authors
Li, L., Georgiou, A., Vecellio, E., Eigenstetter, A., Toouli, G., Wilson, R., & Westbrook, J. I.
Affiliations
  • UNSW Sydney (AU)
  • Prince of Wales Hospital (AU)
Corresponding author
Li, Ling
Venue
Academic Emergency Medicine
Publisher
Wiley
Published
2015-01
Volume
22
Issue
1
Pages
38-46
ISSN
  • 1069-6563 (ISSN-L)
  • 1553-2712
OpenAlex
W1970955942
Cited by
117
References
30
Citations by year
2026: 9 · 2025: 8 · 2024: 12 · 2023: 13 · 2022: 8 · 2021: 16 · 2020: 16 · 2019: 10 · 2018: 12 · 2017: 7 · 2016: 5 · 2015: 1
FWCI
8.11
Type
journal article
Language
en
Open access
Locations
  • Academic Emergency Medicine (publishedVersion, cc-by-nc-nd)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
Funders
Australian Government Department of Health: Quality Use of Pathology Program grant
Topics
  • Health Sciences › Medicine › Emergency Medicine › Emergency and Acute Care Studies
  • Health Sciences › Medicine › Physiology › Clinical Laboratory Practices and Quality Control
  • Health Sciences › Health Professions › Emergency Medical Services › Healthcare Operations and Scheduling Optimization
Keywords
emergency department length of stay, laboratory testing, turnaround time, test volume, hospital resource utilization
MeSH terms
Adult, Age Factors, Aged, Emergency Service, Hospital, Female, Humans, Laboratories, Hospital, Length of Stay, Longitudinal Studies, Male, Middle Aged, New South Wales, Retrospective Studies, Sex Factors, Time Factors, Triage, Diagnostic Techniques and Procedures

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