Evidence map›Paper›PMID 39385858›Full record

ArticleCureus2024

Retrospective Cohort Analysis of the Relationship Between Emergency Department Length of Stay and Timing of First Laboratory Orders.

Wayne A Martini, Nicole R Hodgson

Abstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Wayne A MartiniEmergency Medicine, Mayo Clinic, Phoenix, USA.
Nicole R HodgsonEmergency Medicine, Mayo Clinic, Phoenix, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background The efficiency of patient management in the Emergency Department (ED) is critical for optimizing healthcare delivery. Provider in triage (PIT) and similar ED flow models attempt to expedite throughput by decreasing the amount of time between patient arrival and initial order placement. The exact relationship between ED length of stay (LOS) and the timing of the first laboratory order, however, is unclear. The varying speed at which clinicians of different ages place laboratory orders and move patients through an ED also is understudied.  Methods A retrospective analysis was conducted using SQL from the Clarity data archive to pull all patient encounters in 2023. Linear regression models using Analysis ToolPak in Microsoft Excel were used to create and examine the relationship between LOS and the timing of the first laboratory order. Secondary outcomes using the same models were created to analyze the impact of clinician age on LOS and the relationship between clinician age and the timing of first laboratory orders.  Results Two hundred sixty-nine thousand eight hundred and eight ED visits were reviewed across three academic and 17 community emergency departments. We report a weak but statistically significant positive relationship between the timing of the first laboratory order and LOS (R² = 0.0378, p < 0.001). Secondary outcomes indicated a very weak negative correlation between clinician age and LOS (R² ≈ 0, p < 0.001) and no significant relationship between clinician age and the timing of the first laboratory order (R² ≈ 0, p > 0.05). Conclusion The timing of the first laboratory order is a significant, albeit weak, predictor of LOS in the ED. Clinician age has minimal impact on LOS and does not significantly influence the timing of the first laboratory order.

Indexed as

diagnostic timinged operationsemergency departmenthealthcare efficiencylaboratory orderslength of staypatient managementpatient throughputphysician ageretrospective analysis

Identifiers

PMID39385858
PMCPMC11461991

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Registered trials

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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.