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Record W3123761738 · doi:10.12927/hcq.2020.26393

Use of High-Reliability Principles in the Evolution of a Hospital Command Centre

2021· article· en· W3123761738 on OpenAlexaffvenue
Barbara Collins

Bibliographic record

VenueHealthcare Quarterly · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsHumber River Regional Hospital
Fundersnot available
KeywordsHarmPerspective (graphical)Best practiceReliability (semiconductor)NursingOperations managementProcess managementMedical emergencyMedicineBusinessPolitical scienceComputer scienceEngineeringLaw

Abstract

fetched live from OpenAlex

Hospitals and health systems across the world strive to achieve consistently safe care delivery and reduce patient harm. In November 2017, Humber River Hospital became one of the first hospitals in North America to implement a hospital command centre to manage patient access and flow. The command centre outputs relevant real-time data that have been integrated from multiple automated systems and uses predictive analytics to support early identification of patients at risk of harm and deterioration. The aim of this descriptive article is to present the conceptual development of Humber River Hospital's Command Centre.

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)0.002
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 score0.387
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.088
GPT teacher head0.387
Teacher spread0.299 · 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

Citations13
Published2021
Admission routes2
Has abstractyes

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