Development of a peripheral blood morphology proficiency assessment program using the CellaVision<sup>®</sup> Proficiency Software
Bibliographic record
Abstract
Abstract Objectives Proficiency programs allow hospital laboratories to evaluate and improve diagnostic performance. A cloud-based proficiency program was launched in 2017 to standardize peripheral blood morphology assessments in hospital laboratories across the province of Nova Scotia. Methods The CellaVision ® Proficiency Software was used to evaluate peripheral blood morphology assessments. A different blood film featuring a specific red or white cell finding or normal morphology was evaluated each month. Each hospital’s proficiency slide completion and pass rates were monitored, which helped inform remediation efforts. Results In 2017, 213 medical laboratory technologists from 14 hospital laboratories enrolled in the proficiency program. The average completion rate for monthly proficiency assessments between 2017 and 2022 was 90 %. During that time, the pass rate increased from 59 to 95 % and 73 to 89 % for red and white blood cell assessments, respectively. By 2022, four hospital laboratories and 83 medical laboratory technologists stopped performing peripheral blood assessments. Conclusions The CellaVision ® Proficiency Software facilitated a centralized peripheral blood morphology proficiency assessment program for geographically distributed hospital sites. The use of this software increased the quality of peripheral blood morphology assessments in Nova Scotia by simplifying the evaluation of and education on peripheral blood morphology skills.
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How this classification was reachedexpand
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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".