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Record W7000146490

Emergency Department Delays Prior to Admission and In-hospital Health and Economic Outcomes

2009· article· en· W7000146490 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2009
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEmergency departmentHealth careHospital admissionRetrospective cohort studyMultivariate analysisHealth economicsHealthcare Cost and Utilization ProjectHospital care
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: The Emergency Department (ED) plays an important role in the health care safety net, but its ability to deliver care is compromised due to crowding. This is the major issue currently facing emergency care in Canada. OBJECTIVE: The aim of this study is to determine whether the length of stay (LOS) in the ED affects subsequent hospital outcomes for patients admitted through the ED. METHODS: This was a retrospective study using London Health Science Centre (LHSC) administrative data from April 2006 to April 2007. Three databases were linked to gather information on patient characteristics, health outcomes, and cost of care. There were 15,959 ED visits that led to subsequent admissions. 13,460 ED visits made by adult patients at either University Hospital or Victoria Hospital were included. The predictor variable was ED LOS. The primary outcomes of interest were hospital LOS in days and total hospital cost. Correlation coefficients were used to characterize the relationship of ED LOS with hospital LOS and costs. We fitted log normal models for each outcome: one with ED LOS expressed as a continuous variable; one using 8 hour ED LOS to define delayed care; and the last model with ED LOS expressed as an ordinal variable using quartiles. Multivariate statistical analyses were performed using SAS (version 9.1.3,\nSAS Institute, Inc.). RESULTS: When ED LOS is defined as a binary variable using an 8 hour cutoff, 31% of patients (n=4,198) experienced delayed care. On average, delayed care in the ED is associated with a 7.2% increase in inpatient LOS and a 4.8% increase in inpatient cost. When ED LOS is modeled continuously, each additional hour of ED LOS adds 1.1% to inpatient LOS and 0.86% to inpatient cost. All calculations were adjusted for age, sex,\nin\nED triage urgency, arrival by ambulance, admission to ICU or surgery, site of ED, and case mix group. We estimated that these delays resulted in an additional 3,038 inpatient days and $2,268,014 hospital cost. CONCLUSION: Delays in the ED are associated with increased inpatient LOS and inpatient cost. As such, improving patient flow through the ED may reduce hospital costs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.340
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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