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Record W2795339097 · doi:10.1097/qmh.0000000000000164

VA Quality Scholars Quality Improvement Coach Model to Facilitate Learning and Success

2018· article· en· W2795339097 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueQuality Management in Health Care · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Satisfaction
Canadian institutionsOlds College
Fundersnot available
KeywordsQuality (philosophy)Quality managementComputer scienceProcess managementEngineering managementKnowledge managementBusinessEngineeringMarketingEpistemology

Abstract

fetched live from OpenAlex

Despite the increase in quality improvement (QI) education both in practice and in health professions' education, gaps exist in the usefulness and success of QI projects. Barriers to successful QI are a result of delays in implementation, teamwork issues, and lack of QI knowledge. These barriers can be addressed using a QI Coach. A QI Coach is an expert in QI principles who has excellent communication and collaboration skills, and is experienced with organizational policies. The purpose of this article is to (a) describe the VA Quality Scholars (VAQS) QI Coach Model that includes the role of a coach and effective coaching strategies and (b) discuss lessons learned from the application of the VAQS QI Coach Model. The QI Coach facilitates success by providing novice QI teams with practical skills, encouragement, and support.

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.

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)0.024
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.002
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 head0.290
GPT teacher head0.548
Teacher spread0.257 · 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