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Record W2160009029 · doi:10.5555/2675983.2676288

Simulation of patient discharge process and its improvement

2013· article· en· W2160009029 on OpenAlexaff
Nancy Khurma, Farzaneh Salamati, Zbigniew J. Pasek

Bibliographic record

VenueWinter Simulation Conference · 2013
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsProcess (computing)Discharge planningInformation flowPatient dischargeOperations managementReduction (mathematics)Computer scienceMedical emergencyProcess managementMedicineBusinessEngineeringNursingMEDLINEMathematics

Abstract

fetched live from OpenAlex

This paper presents results of a study conducted jointly with a regional hospital and concerned with inpatient discharge process. In an effort to see what the hospital can do to reduce alternative level of care (ALC) days (or length of stay, LOS), a simulation model of the discharge planning path was created and validated. The model was used to explore the effects of standardizing parts of the discharge process. The results showed a potential for 4.5 day reduction in the median of LOS. Obtained results indicate that organizational changes (e.g., early involvement of social workers, improved information flow, close collaboration with external facilities accepting patients, etc.) will lead to process improvement and substantial economic benefits.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.309
Teacher spread0.286 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations5
Published2013
Admission routes1
Has abstractyes

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