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Record W2155621305 · doi:10.1377/hlthaff.24.1.138

Evidence-Based Quality Improvement: The State Of The Science

2005· article· en· W2155621305 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

VenueHealth Affairs · 2005
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsChildren’s Health Research Institute
Fundersnot available
KeywordsIntuitionQuality managementEvidence-based medicineQuality (philosophy)Evidence-based practiceClinical PracticeManagement scienceMedicinePsychologyKnowledge managementComputer scienceAlternative medicineBusinessNursingMarketingEngineeringEpistemology

Abstract

fetched live from OpenAlex

Routine practice fails to incorporate research evidence in a timely and reliable fashion. Many quality improvement (QI) efforts aim to close these gaps between clinical research and practice. However, in sharp contrast to the paradigm of evidence-based medicine, these efforts often proceed on the basis of intuition and anecdotal accounts of successful strategies for changing provider behavior or achieving organizational change. We review problems with current approaches to QI research and outline the steps required to make QI efforts based as much on evidence as the practices they seek to implement.

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)0.018
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.764
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.279
GPT teacher head0.538
Teacher spread0.259 · 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