The utilization of appropriate osteoporosis medications improves following a multifaceted educational intervention: the Canadian quality circle project (CQC)
Bibliographic record
Abstract
BACKGROUND: Osteoporosis is a serious but treatable condition. However, appropriate therapy utilization of the disease remains suboptimal. Thus, the objective of the study was to change physicians' therapy administration behavior in accordance with the Osteoporosis Canada 2002 guidelines. METHODS: The Project was a two year cohort study that consisted of five Quality Circle (QC) phases that included: 1) Training & Baseline Data Collection, 2) First Educational Intervention & First Follow-Up Data Collection 3) First Strategy Implementation Session, 4) Final Educational Intervention & Final Follow-up Data Collection, and 5) Final Strategy Implementation Session. A total of 340 family physicians formed 34 QCs and participated in the study. Physicians evaluated a total of 8376, 7354 and 3673 randomly selected patient charts at baseline, follow-up #1 and the final follow-up, respectively. Patients were divided into three groups; the high-risk, low-risk, and low-risk without fracture groups. The generalized estimating equations technique was utilized to model the change over time of whether physicians RESULTS: The odds of appropriate therapy was 1.29 (95% CI: 1.13, 1.46), and 1.41 (95% CI: 1.20, 1.66) in the high risk group, 1.15 (95% CI: 0.97, 1.36), and 1.16 (95% CI: 0.93, 1.44) in the low risk group, and 1.20 (95% CI: 1.01, 1.43), and 1.23 (95% CI: 0.97, 1.55) in the low risk group without fractures at follow-up #1 and the final follow-up, respectively. CONCLUSION: QCs methodology was successful in increasing physicians' appropriate use of osteoporosis medications in accordance with Osteoporosis Canada guidelines.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".