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Record W2141712571 · doi:10.12927/hcq.2010.21809

Engaging Physicians to Improve Quality

2010· article· en· W2141712571 on OpenAlexaboutno aff
Jane Coutts

Bibliographic record

VenueHealthcare Quarterly · 2010
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMandateExcellenceDeskHealth careQuality (philosophy)Public relationsPolitical scienceBusinessLaw

Abstract

fetched live from OpenAlex

Accelerating Excellence ReportSaskatchewan's Health Quality Council (HQC) was launched in 2003 with a mandate to not only measure and report on healthcare but also work with a range of partners to improve the province's health system.In late 2007, HQC's board decided it was time for Saskatchewan to reinvent its healthcare system, using the highestperforming systems in the world as its model.And in 2008, HQC launched Accelerating Excellence, a multi-level program to rethink, redesign and renew healthcare.To help maintain momentum and show other provinces whether high-performing healthcare can be achieved in Canada, HQC is documenting its journey toward high-performing healthcare.This third article in this series discusses the challenge of physician engagement.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0080.004
Scholarly communication0.0080.005
Open science0.0020.011
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0220.004

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 head0.080
GPT teacher head0.479
Teacher spread0.399 · 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 source (direct Gemma or distilled Codex), 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
Published2010
Admission routes1
Has abstractyes

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