Reducing overutilisation of serum vitamin D testing at a tertiary care centre
Bibliographic record
Abstract
INTRODUCTION: Testing of 25-hydroxy (25-OH) vitamin D serum levels has increased drastically in recent years and much of it is considered inappropriate based on current guidelines. METHODS: In consultation with our physician groups (experts and frequent orderers), we modified existing guidelines and implemented a rational policy for 25-OH vitamin D testing and 1,25 dihydroxy (1,25 di-OH) vitamin D testing at a tertiary care centre. A computer decision support tool requiring selection of one of five acceptable testing indications was created for each test as part of a computerised physician order entry system. RESULTS: As a result of our intervention, we observed a 27% decrease in the average monthly test volume for 25-OH vitamin D from 504±62 (mean±SD) tests per month to 370±33 (p<0.001). 1,25 di-OH vitamin D testing decreased 58% from 71±18 to 30±10 (p<0.001). The departments ordering the tests were similar during the preintervention and postintervention periods, and further audits, patient chart reviews and individualised physician feedback were required to ensure appropriate ordering of 1,25 di-OH vitamin D. The most common ordering reasons selected were malabsorption/dietary concerns (46%) for 25-OH vitamin D and renal failure (42%) for 1,25 di-OH vitamin D. CONCLUSIONS: Limitations of our computer decision support tool include a dependence on an honour system in selecting the testing indication and an inability to limit ordering frequency. Periodic monitoring of test volumes will be required to ensure adherence to guidelines. Despite these limitations, we have improved appropriate utilisation of these tests and reduced costs by approximately $C60 375 per year.
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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 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".