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Record W6921418120 · doi:10.6084/m9.figshare.c.6587693

Emergency department crowding negatively influences outcomes for adults presenting with asthma: a population-based retrospective cohort study

2023· other· en· W6921418120 on OpenAlexaffabout

Bibliographic record

VenueFigshare · 2023
Typeother
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsSimon Fraser UniversityUniversity of Alberta
Fundersnot available
KeywordsTriageCrowdingEmergency departmentRetrospective cohort studyOddsOvercrowdingOdds ratioCohort

Abstract

fetched live from OpenAlex

Abstract Background Access to emergency department (ED) services is important for patients with acute asthma; however, ED crowding may impact the quality of care and compromise outcomes. We examine the association between ED crowding metrics and individual patient outcomes for adults presenting with asthma. Methods This population-based retrospective cohort study extracted all ED presentations made by patients aged 18 to 55 years to 18 high-volume EDs in Alberta from April 2014 to March 2019. Physician initial assessment (PIA) time and ED length of stay (LOS) for discharged and admitted patients were calculated. Other metrics and patient outcomes were also obtained. Linear and generalized linear models were fit for continuous and categorical outcomes. Cox proportional hazards models were used for time-to-event outcomes. Results There were 17,724 ED presentations by 12,569 adults. The median age was 33 years, and females (58.7%) made more presentations. ED crowding affected the PIA time for all triage groups. For the high acuity group (Canadian Triage and Acuity Scale [CTAS] 1/2), 1 h increase in median facility-specific PIA was associated with 26 min (95%CI: 24,28) increase; for the moderate acuity (CTAS 3) and low acuity (CTAS 4/5) groups, the individual-level PIA increased by 54 min (95%CI: 53,55) and 61 min (95%CI: 59,63), respectively adjusted by other predictors. Increases in facility PIA resulted in increase in odds of admissions for the high acuity group and increase odds of left without completion of care for the moderate and low acuity groups. Conclusion The care provided for patients from all triage groups was impacted when EDs experienced crowding. Effective interventions are needed to mitigate ED crowding and improve care and outcomes for this important patient group.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.734
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.287
Teacher spread0.261 · 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
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
Published2023
Admission routes2
Has abstractyes

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