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Record W2536208089 · doi:10.5539/ibr.v9n11p208

Hospital Technical Efficiency Measurement Through of a Stochastic Frontier Cost Panel

2016· article· en· W2536208089 on OpenAlexvenueno aff
João Serafim Tusi da Silveira, Lucélia Ivonete Juliani, Lucas Veiga Ávila, José Tavares de Borba

Bibliographic record

VenueInternational Business Research · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicEfficiency Analysis Using DEA
Canadian institutionsnot available
Fundersnot available
KeywordsEconometricsSample (material)FrontierPanel dataEconomicsEconometric modelCost efficiencyMaximum likelihoodStochastic frontier analysisStatisticsMathematicsOperations managementComputer scienceMicroeconomicsGeographyProduction (economics)

Abstract

fetched live from OpenAlex

<p class="1main-text">This article aims to evaluate the relative technical efficiency of the three clinics belonging to the University Hospital of the Federal University of Santa Catarina, RS, Brazil, in a two years period. The specification of the econometric model includes the analysis of productive sectors from the same institution in different periods of time. A stochastic frontier cost CD function using the composed error model was estimated by maximum likelihood (MLE) for a monthly data panel. The efficiency measures were computed using the formula adapted to the costs, based on parameters estimated by MLE. The results are encouraging and intriguing, especially regarding the inclusion of new variables, the expansion of the sample and the real utility of the efficiency ratios in the effective management task of productive resources within a single firm.</p>

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)0.009
metaresearch head score (Gemma)0.040
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.899
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.040
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.288
GPT teacher head0.462
Teacher spread0.174 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2016
Admission routes1
Has abstractyes

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