Promoting resource stewardship: Reducing inappropriate free thyroid hormone testing
Bibliographic record
Abstract
RATIONALE: Free thyroxine (fT4) and free triiodothyronine (fT3) tests are often ordered when not clinically warranted. Preventing laboratory overuse by reducing inappropriate fT4 and fT3 testing is one strategy to promote resource stewardship. OBJECTIVES: (1) To characterize the frequency of inappropriate fT4 and fT3 testing and (2) to implement a quality improvement strategy aimed at reducing the number of these tests performed. METHODS: Quality improvement tools were used to create sequential change ideas: (1) education of physicians regarding appropriate indications for ordering fT4/fT3 and (2) implementation of a hospital-wide laboratory and forced-function system with a reflex fT4. This study was conducted at an academic ambulatory care hospital in Toronto, Canada. The main outcomes were the differences in weekly median number of thyroid-stimulating hormone, fT4, and fT3 tests performed during the preintervention, education, and reflex periods using the Kruskal-Wallis test and analysis for special cause variation with statistical process control charts. RESULTS: The median number of fT4/fT3 processed per week was significantly reduced from 90/39 at baseline to 78/34 posteducation and 59/14 postreflex (P < .0001). Comparing preintervention to the reflex period, there was 34% reduction in fT4 and 64% reduction in fT3. The number of processed thyroid-stimulating hormone tests was stable with only 2% variation. Statistical process control charts demonstrated special cause variation following implementation of the reflex system for both fT4 and fT3. CONCLUSIONS AND RELEVANCE: Inappropriate testing of free thyroid indices occurs frequently. The implementation of a reflex fT4 strategy after education was feasible in reducing overall testing by 49% and was effective in promoting resource stewardship.
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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 | 0.012 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".