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Record W2006690339 · doi:10.5430/jha.v3n6p205

A modular simulation study to improve patient flow to inpatient units in the emergency department

2014· article· en· W2006690339 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Hospital Administration · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Operations and Scheduling Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsOvercrowdingWorkflowEmergency departmentDiscrete event simulationModular designProcess (computing)Operations managementComputer scienceMedical emergencyEvent (particle physics)Patient satisfactionMedicineEmergency medicineSimulationEngineeringNursing

Abstract

fetched live from OpenAlex

In this study, a modular discrete event simulation (computer modeling) has been presented to support process improvements in a hospital’s emergency department (ED) to streamline admitted patient flow to inpatient units. Because the ED in this study has less than 10 beds, unnecessary occupation of beds affects the patient wait time dramatically. Additionally, ED overcrowding diminishes the quality of care, increases costs, and decreases employee and patient satisfaction. The modular simulation model evaluated the effectiveness of several recommended workflow improvements, resulting from comprehensive statistical analysis, based on their impact on cycle time and time traps in the process. The results suggested that, to ensure better efficiency and optimal cycle time, all of the suggested workflow improvements should be implemented simultaneously. The model also suggested that achieving customer satisfaction is possible 96.26% of the time with the current resource allocations in the ED.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.036
GPT teacher head0.394
Teacher spread0.358 · 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