Choosing Wisely Canada recommendations for clinical biochemistry: test ordering for sustainable and high-quality patient care
Bibliographic record
Abstract
Laboratory Medicine is growing at a rapid rate in both the breadth of unique tests and the total number of tests performed per year. Inappropriate overutilization of laboratory tests can lead to patient harm, excessive environmental waste and increased carbon emissions. A focus on reducing inefficiencies in healthcare is needed to ensure a robust and sustainable healthcare system. To promote laboratory sustainability, the Canadian Society of Clinical Chemists (CSCC) has developed ten recommendations related to medical tests within clinical biochemistry. These recommendations are designed as 'low-hanging fruit' that should be adopted by both hospital and community laboratories. By implementing automated strategies and/or educational approaches to reduce misuse of laboratory resources, clinical laboratories can move toward a more sustainable model that improves patient care. This list of recommendations, created for Choosing Wisely Canada, covers tests for diabetes, celiac disease, monoclonal gammopathies, iron disorders, liver disorders, kidney disorders, substance use disorders, and allergen 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 | 0.011 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.013 | 0.017 |
| Insufficient payload (model declined to judge) | 0.028 | 0.008 |
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".