Optimizing care in osteoporosis: The Canadian quality circle project
Bibliographic record
Abstract
BACKGROUND: While the Osteoporosis Canada 2002 Canadian guidelines provided evidence based strategies in preventing, diagnosing, and managing this condition, publication and distribution of guidelines have not, in and of themselves, been shown to alter physicians clinical approaches. We hypothesize that primary care physicians enrolled in the Quality Circle project would change their patient management of osteoporosis in terms of awareness of osteoporosis risk factors and bone mineral density testing in accordance with the guidelines. METHODS: The project consisted of five Quality Circle 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 circle members formed 34 quality circles and participated in the study. The generalized estimating equations approach was used to model physician awareness of risk factors for osteoporosis and appropriate utilization of bone mineral density testing pre and post educational intervention (first year of the study). Odds ratios (OR) and 95% confidence intervals (95% CI) were calculated. RESULTS: After the 1st year of the study, physicians' certainty of their patients' risk factor status increased. Certainty varied from an OR of 1.4 (95% CI: 1.1, 1.8) for prior vertebral fracture status to 6.3 (95% CI: 2.3, 17.9) for prior hip fracture status. Furthermore, bone mineral density testing increased in high risk as compared with low risk patients (OR: 1.4; 95% CI: 1.2, 1.7). CONCLUSION: Quality Circle methodology was successful in increasing both physicians' awareness of osteoporosis risk factors and appropriate bone mineral density testing in accordance with the 2002 Canadian guidelines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".