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Record W2905448886 · doi:10.12927/hcq.2018.25637

Bringing Together Research and Quality Improvement: The Saskatchewan Approach

2018· article· en· W2905448886 on OpenAlexaffabout
Gary Teare, Malori Keller

Bibliographic record

VenueHealthcare Quarterly · 2018
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsSaskatchewan Health Quality Council
Fundersnot available
KeywordsQuality managementUnit (ring theory)Quality (philosophy)BusinessHealth careNursingPublic relationsPsychologyProcess managementMedical educationKnowledge managementMedicineOperations managementPolitical scienceMarketingEngineeringComputer science

Abstract

fetched live from OpenAlex

Improving health and health services requires both better knowledge (a key function of research) and better action to adapt and use what is already known (quality improvement). However, organizational and cultural divides between academic research institutions and health system organizations too often result in missed opportunities to integrate research and improvement. The Saskatchewan Health Quality Council's experience and relationships, from linking research, quality improvement and patient engagement in its leadership of the province's healthcare quality improvement journey, provided core support and leadership in the development of Saskatchewan's Strategy for Patient-Oriented Research SUPPORT Unit. The vision is for the SUPPORT Unit to integrate research and quality improvement into a continuous learning health system.

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)0.006
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.947
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
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 integrity0.0000.001
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 head0.376
GPT teacher head0.547
Teacher spread0.171 · 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 designOther design
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
Published2018
Admission routes2
Has abstractyes

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