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Record W2066676039 · doi:10.1097/pec.0b013e31819a7e20

Impact of an Observation Unit and an Emergency Department-Admitted Patient Transfer Mandate in Decreasing Overcrowding in a Pediatric Emergency Department

2009· article· en· W2066676039 on OpenAlexaff
Geoffrey R. Hung, Niranjan Kissoon

Bibliographic record

VenuePediatric Emergency Care · 2009
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsBritish Columbia Children's Hospital
Fundersnot available
KeywordsEmergency departmentMedicineMandateEmergency medicineOvercrowdingTriageTransfer (computing)Medical emergencyNursingComputer science

Abstract

fetched live from OpenAlex

OBJECTIVES: The primary objective was to examine the effects of a simulated observation unit (OU) and a transfer mandate for admitted patients on pediatric emergency department (PED) patient flow indicators. The secondary objective was to report on the occupancy rate of the simulated OU. METHODS: Simulations were conducted using a previously designed and validated discrete event simulation model of our PED operations. A simulated OU was designed, and an emergency department-admitted patient transfer mandate was developed and then applied to a discrete event simulation model. Four scenarios (regular PED operations with and without a 5-bed OU and transfer mandate in all combinations) were modeled. RESULTS: A combination of an OU and an emergency department-admitted patient transfer mandate resulted in reductions in time to be seen by a physician and length of stay in patients who were triaged with urgent or emergent presentations as compared with PED operations with neither an OU nor a transfer mandate. Small improvements in fractile response were observed for patients triaged with urgent presentations. The OU without the transfer mandate had a simulated occupancy rate of 73.1%. The inclusion of the transfer mandate reduced the occupancy rate to 48.1%. CONCLUSIONS: Simulation scenario analyses predict that an OU and a transfer mandate would reduce overcapacity in the PED, with more substantial reductions in time to be seen and length of stay for patients of high acuity.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.023
GPT teacher head0.321
Teacher spread0.298 · 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

Citations21
Published2009
Admission routes1
Has abstractyes

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