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Record W3168334985 · doi:10.12927/hcpol.2021.26498

Despite Interventions, Emergency Flow Stagnates in Urban Western Canada

2021· article· fr· W3168334985 on OpenAlexafffundvenueabout
Sara A. Kreindler, Michael J. Schull, Brian H. Rowe, Malcolm Doupe, Colleen Metge

Bibliographic record

VenueHealthcare policy · 2021
Typearticle
Languagefr
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsUniversity of AlbertaInstitute for Clinical Evaluative SciencesUniversity of ManitobaManitoba Health
FundersCanadian Institutes of Health ResearchUniversity of Manitoba
KeywordsPsychological interventionGeographyMedicineNursing

Abstract

fetched live from OpenAlex

Purpose: This paper reports the quantitative component of a mixed-methods study of patient flow in the 10 urban health regions/zones of Western Canada. We assessed whether jurisdictions differed meaningfully in their emergency flow performance, defined as mean emergency department length of stay (ED LOS). Methods: We used hierarchical linear modelling to compare ED LOS across jurisdictions, based on nationally reported data for 2017 to 2018. We also explored 36-month performance trends. Admitted and discharged patients were analyzed separately. Results: With the exception of one high performer, no region's performance differed significantly from average for both admitted and discharged patients. The regions' levels of performance remained largely static throughout the study period. Conclusions: Results precluded any mixed-methods comparison of high- and low-performing regions. However, they converged with our qualitative findings, which suggested that most regions were pursuing similar flow-improvement strategies with limited effectiveness. Deeper changes may be required to address persistent misalignment between capacity and demand.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.642
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.375
Teacher spread0.334 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreReview

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

Citations6
Published2021
Admission routes4
Has abstractyes

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