Inappropriate Repeats of Six Common Tests in a Canadian City: A Population Cohort Study Within a Laboratory Informatics Framework
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
OBJECTIVES: To identify inappropriate repeats of six common laboratory tests in a population sample of patients, using highly specific criteria based only on repeat time and test value. METHODS: We used a laboratory informatics database to conduct a retrospective cohort study using a population sample of 103,000 patients in the city of Calgary with an index test in 2010 and uniform follow-up of 1 year. We examined six tests (cholesterol, hemoglobin A1c, thyroid-stimulating hormone, vitamin B12, vitamin D, and ferritin) with consensus-based or easily justified criteria for inappropriate repeats based solely on time to repeat and the index test value. RESULTS: The percentages of tests repeated at 3, 6, and 12 months were 11%, 23%, and 41%, respectively. In total, 16% of these six tests were inappropriately repeated, representing an annual internal cost of $0.6 to $2.2 million Canadian dollars and corresponding to population-scaled national estimates for Canada and the United States of $160 million and $2.4 billion, respectively. CONCLUSIONS: Objective definitions based on repeated testing identified 16% of six studied tests as inappropriate, delineating a subset of inappropriate testing that is well suited to automated identification and intervention and that provides a likely lower bound on the true burden of inappropriate testing.
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 | 0.017 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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