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Record W7096226972

A STRATEGIC GOVERNANCE MODEL TO IMPROVE THE PERFORMANCE OF EMERGENCY DEPARTMENTS IN PUBLIC HOSPITALS IN THE PROVINCE OF Ontario, Canada

2013· article· en· W7096226972 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsnot available
Fundersnot available
KeywordsQuality (philosophy)Corporate governanceQuality managementPublic hospitalPublic healthHealth careClinical governanceTotal quality management
DOInot available

Abstract

fetched live from OpenAlex

The rapidly increasing demand for health care in the province of Ontario has led to greater numbers of patients turning to public hospitals for the care they need. The primary entrance for them into the public hospital system is through Emergency Departments. The poor performance of public hospital Emergency Departments in handling the demands put on them calls into question the quality of the Emergency Departments. Assuming that the management of hospitals focuses their attention and resources on problem areas, the quality of management in the Emergency Departments are likely symptomatic of the quality of the management throughout the hospital. Ultimately, responsibility for the quality of management in the hospital rests with the board of directors and is a matter of governance. While prior studies have examined the quality of health care as affected by governance, none appear to have considered the quality of management. This study is a first to our knowledge in addressing whether the quality of management is a reason for differences in performance across hospitals. This study connects the performance of the Emergency Departments with the ultimate

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.849

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 head0.083
GPT teacher head0.368
Teacher spread0.285 · 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 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
Published2013
Admission routes1
Has abstractyes

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