Choosing Wisely Canada campaign associated with less overuse of thyroid testing: Retrospective parallel cohort study.
Bibliographic record
Abstract
OBJECTIVE: To assess the effectiveness of a Choosing Wisely Canada (CWC) initiative to improve thyroid-stimulating hormone (TSH) test ordering for patients with no identified indication for this test. DESIGN: Retrospective parallel cohort study using routinely collected electronic medical record (EMR) data. The CWC initiative included supporting primary care leads in each participating family health team, providing education on better test ordering, and allowing adaptation appropriate to each local context. SETTING: Toronto, Ont, and surrounding areas. PARTICIPANTS: Family physicians contributing EMR data to the University of Toronto Practice-Based Research Network and their patients aged 18 or older. MAIN OUTCOME MEASURES: Proportion of adult patients with a TSH test done in a 2-year period (2016 to 2017) in the absence of EMR data with an indication for TSH testing; proportion of TSH test results in the normal range for those patients; and change in the rate of TSH screening in sites participating in the CWC initiative compared with sites not participating. RESULTS: = .03), a relative difference of 11.4%. The TSH testing decreased for almost all CWC patient subgroups. More than 95% of patients tested in both groups had TSH results in the normal range. CONCLUSION: This study found high rates of TSH testing without identified indications in the practices studied. A CWC initiative implemented in primary care was effective in reducing TSH testing.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".