Drug treatment of stable angina pectoris and mass dissemination of therapeutic guidelines: a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Public agencies responsible for implementing health care policies often adapt and disseminate clinical practice guidelines, but the effectiveness of mass dissemination of guidelines is unknown. AIM: To study the effects of guideline dissemination on physicians' prescribing practices for the treatment of stable angina pectoris. DESIGN: Randomized controlled trial. METHODS: A sample of 3293 Quebec physicians were randomly assigned to receive a one-page summary of clinical practice guidelines on the treatment of stable angina (in February 1999), to receive the summary and a reminder (in February and March 1999, respectively), or to receive no intervention (controls). The prescribing profiles of participants, as well as sociodemographic characteristics of the physicians and their patients, were examined for June-December 1999. RESULTS: The intervention had no effect on prescription rates of beta-blockers, antiplatelet agents, or hypolipaemic drugs. Compared to 1997 data for the same physicians, there was an overall 10% increase in appropriate prescription rates, irrespective of the intervention. DISCUSSION: In-house production and dissemination of clinical practice guidelines may not improve physicians' practice patterns if there is pre-existing substantial scientific consensus on the issue.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".