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Record W2005690672 · doi:10.1016/j.hcmf.2013.12.002

Creating and Sustaining Value: Building a Culture of Continuous Improvement

2014· article· en· W2005690672 on OpenAlexaffabout
Saleem Chattergoon, Shelley Darling, Rob Devitt, Wolf Klassen

Bibliographic record

VenueHealthcare Management Forum · 2014
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of TorontoInstitute for Work & HealthToronto East General Hospital
Fundersnot available
KeywordsPulmonary diseaseOrganizational cultureBusinessEmergency departmentValue (mathematics)Operations managementMedicineMedical emergencyNursingProcess managementPublic relationsComputer sciencePolitical scienceEngineeringInternal medicine

Abstract

fetched live from OpenAlex

In 2011, the Toronto East General Hospital (TEGH) began its journey towards developing a culture of continuous improvement. TEGH evolved to an organization-wide improvement system through a commitment to fiscal responsibility, practical innovation, team-based performance management, and daily management systems. This culture enabled the TEGH to achieve the lowest Emergency Department wait times for admitted patients in its local health integration network and reduce length of stay for patients with chronic obstructive pulmonary disease by 46%.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.789
Threshold uncertainty score0.887

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.018
GPT teacher head0.377
Teacher spread0.359 · 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 designNot applicable
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

Citations9
Published2014
Admission routes2
Has abstractyes

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