Implementation of an intervention to reduce population-based screening for vitamin D deficiency: a cross-sectional study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: We describe the implementation of an intervention in Alberta in support of the Choosing Wisely Canada recommendation against population screening for vitamin D deficiency (as determined by serum total 25-hydroxyvitamin D testing). We hypothesized that the introduction of a specialized requisition for vitamin D testing would reduce the annual number of vitamin D tests performed. METHODS: We performed a cross-sectional observational study that included all vitamin D tests ordered in Alberta between Apr. 1, 2015, and Mar. 31, 2016. There were no exclusion criteria. A special requisition for ordering vitamin D tests in Alberta was introduced on Apr. 1, 2015. Using an interrupted time series model, we compared predicted versus observed vitamin D test volumes for the 12-month period following the introduction of the new requisition. The sole outcome measure was the monthly change in volume of vitamin D testing. In addition, we calculated any cost savings as a result of reduced testing. RESULTS: Over the first 12 months of the intervention, there was a reduction in the number of tests ordered from a predicted 342 477 tests to 29 525 tests (91.4% reduction). This decrease represented a direct spending decrease of Can$938 856-$1 564 760 per year in Alberta. INTERPRETATION: A provincially led implementation of a Choosing Wisely Canada recommendation resulted in a large and sustained reduction in serum total 25-hydroxyvitamin D testing in Alberta. This study shows that provincially led interventions based on Choosing Wisely Canada recommendations can result in substantial reductions in laboratory tests.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it