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Record W2400072975

The place of guidelines and their means of dissemination.

2001· article· en· W2400072975 on OpenAlexaffabout
W W Rosser

Bibliographic record

VenuePubMed · 2001
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineGuidelinePsychological interventionAcademic detailingMultidisciplinary approachContinuing medical educationFamily medicineIntervention (counseling)Community practiceAlternative medicineNursingMedical educationContinuing educationPharmacyPathology
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: The literature shows that physicians do not change their patterns of practice quickly. With thousands of conflicting guidelines available, many disseminated by print, there has been little measurable impact of new guidelines on physician prescribing patterns. METHODS: A series of interventions designed to improve physician uptake of guidelines is described. Interventions evaluated in a series of trials include mail dissemination, small group continuing medical education sessions, academic detailing by both academic detailers and pharmaceutical detailers, and a whole community program known as the Program for Appropriate Anti-Infective Community Therapy. RESULTS: Only the whole community intervention had significant impact on physician prescribing patterns. The changes involved a significant reduction in anti-infective use and a significant change from the use of second- and third-line drugs to first-line drugs, as specified in the Ontario Anti-Infective Guidelines. CONCLUSIONS: Acceptable guidelines disseminated by a multidisciplinary community program can have a positive impact on physician prescribing patterns. To increase the acceptability of guidelines for whole community dissemination, a new innovation (Guideline Advisory Committee) that scores the quality of guidelines and selects the most objectively produced guideline is described.

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)0.001
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.956
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.011
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 integrity0.0000.000
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 head0.219
GPT teacher head0.444
Teacher spread0.225 · 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.

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

Citations6
Published2001
Admission routes2
Has abstractyes

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