Six-year review of a spirometry quality control program utilized across British Columbia, Canada
Bibliographic record
Abstract
Introduction/Objective: The Diagnostic Accreditation Program (DAP) of British Columbia is responsible for accrediting clinical sites performing spirometry. The purpose of this study is to review compliance and outcomes with the DAP quality control (QC) program requirements over a 6 year period (two reporting cycles per year). Methodology: We analyzed 12 reporting cycles for flags of the various QC components which include BioQC, linearity (also includes flags for verification of the 3L syringe), and calibration. Technical performance and medical interpretation are accessed by reviewing a sampling of patient reports. Of note, Cycle 16 was during COVID-19 when many facilities paused service. DAP also introduced the updated requirements (compliant with ATS/ERS 2019 Spirometry standards AJRCCM 2019 Oct 15;200(8):e70-e88) in Cycle 17 without formal grading (provided feedback only). In Cycle 19 DAP implemented formal grading to the requirements introduced in Cycle 17. Results: Figure 1 erj;64/suppl_68/PA2333/F1 F1 F1 Discussion: There has been an overall decline in the number of flags noted across all categories of the QC program. Of interest was the increase of the technical performance flags which occurred after the implementation of the 2019 Spirometry (Cycle 19). DAP’s QC program continues to influence the quality of spirometry testing throughout the province.
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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 | 0.026 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".