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Record W3025178871 · doi:10.1002/mde.3176

Determining the optimal capacity and occupancy rate in a hospital: A theoretical model using queuing theory and marginal cost analysis

2020· article· en· W3025178871 on OpenAlexaff
Muhammad Maaz, Anastasios D. Papanastasiou

Bibliographic record

VenueManagerial and Decision Economics · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsQueueing theoryOccupancyMarginal costHolding costBalance (ability)Capacity utilizationHealth careEconomicsOperations managementOperations researchActuarial scienceMicroeconomicsStatisticsMedicineMathematicsEngineering

Abstract

fetched live from OpenAlex

We model the hospital as seeking to balance the costs to itself in providing care, as well as the societal cost of people waiting for care. We use queuing theory to show that the optimal capacity and the corresponding optimal occupancy rate are dependent on the marginal cost of expanding capacity, the marginal cost of waiting, and the rates of patient arrival and discharge. Therefore, a universal occupancy target is unfounded. As well, the model shows that increasing capacity to respond to increased patient influxes is inadequate, suggesting that the health care system must explore alternate responses to burgeoning patient populations.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.765
Threshold uncertainty score0.646

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.058
GPT teacher head0.273
Teacher spread0.215 · 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 designTheoretical or conceptual
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
Published2020
Admission routes1
Has abstractyes

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