Reducing red blood cell folate testing: a case study in utilisation management
Bibliographic record
Abstract
Mandatory enrichment of wheat flour in Canada with folic acid since 1998 has caused folate deficiency to be rare. There were 3019 red blood cell (RBC) folate tests performed during an 18-month period at London Health Sciences Centre (LHSC)/St. Joseph's Healthcare London (SJHC) without any folate deficiency detected. We implemented a quality improvement initiative to reduce RBC folate testing at LHSC/SJHC. We began with a retrospective review of RBC folate tests performed during the previous 18 months. We identified physicians who had ordered more than five tests during this period and sent them an educational email to inform them of our intentions and solicit their input. We then discontinued RBC folate testing in-house and a pop-up window was introduced to the computerised physician order entry system stating that biochemist approval would be needed before samples would be sent out for testing. During the audited 18-month period, the average monthly test volume was 168 (SD 20). The three departments ordering the most RBC folate testing were nephrology (15%), haematology (7%) and oncology (7%). Physician feedback was supportive of the change, and during the 2 months after targeted email correspondence, the average monthly test volume decreased 24% (p<0.01) to 128 (SD 1). On discontinuation of the test in-house and implementation of the pop-up, the average monthly test volume decreased another 74% (p<0.01) to 3 (SD 2). In the 10 months following discontinuation of the test on-site, there were only 39 RBC folate tests performed with no deficiency detected. This initiative significantly reduced unnecessary RBC folate orders. The change in ordering on email contact suggests that physician education was an important factor reducing overutilisation. However, the most significant decrease came from restricting the test so that only orders approved by a biochemist would be performed.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".