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Record W3204425181 · doi:10.1186/s12888-021-03446-1

Exploring the experience of boarded psychiatric patients in adult emergency departments

2021· article· en· W3204425181 on OpenAlexaffabout
Daniel H. Major, Katherine Rittenbach, Frank P. MacMaster, Hina Walia, Stephanie VandenBerg

Bibliographic record

VenueBMC Psychiatry · 2021
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsFoothills Medical CentreUniversity of CalgaryAlberta HealthAlberta Health ServicesMount Royal University
Fundersnot available
KeywordsMedicineEmergency departmentOddsEmergency medicineOdds ratioAdverse effectPsychiatryRetrospective cohort studyPediatricsLogistic regressionInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: This study quantifies the frequency of adverse events (AEs) experienced by psychiatric patients while boarded in the emergency department (ED) and describes those events over a broad range of categories. METHODS: A retrospective chart review (RCR) of adult psychiatric patients aged 18-55 presenting to one of four Calgary EDs (Foothills Medical Centre (FMC), the Peter Lougheed Centre (PLC), the Rockyview General Hospital (RGH), and South Health Campus (SHC)) who were subsequently admitted to an inpatient psychiatric unit between January 1, 2019 and May 15, 2019 were eligible for review. A test of association was used to determine the odds of an independent variable being associated with an adverse event. RESULTS: During the study time period, 1862 adult patients were admitted from EDs (city wide) to the psychiatry service. Of the 200 charts reviewed, the average boarding time was 23.5 h with an average total ED length of stay of 31 h for all presentations within the sample. Those who experienced an AE while boarded in the ED had a significantly prolonged average boarding time (35 h) compared to those who did not experience one (6.5 h) (p = 0.005). CONCLUSIONS: The length of time a patient is in the emergency department and the length of time a patient is boarded after admission significantly increases the odds that the patient will experience an AE while in the ED. Other significant factors associated with AEs include the type of admission and the hospital the patient was admitted from.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.020
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

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

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 head0.075
GPT teacher head0.362
Teacher spread0.287 · 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.

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

Citations23
Published2021
Admission routes2
Has abstractyes

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