Validity of asthma diagnoses recorded in the Medical Services database of Quebec
Bibliographic record
Abstract
The goal of this study was to evaluate the validity of asthma diagnoses recorded in the Medical Services (physician billing) database of the Canadian province of Quebec. The predictive positive value (PPV) and predictive negative value (PNV) of two operational definitions of asthma based on diagnoses recorded in the database were evaluated. Patients 16-80 years old treated by a respiratory or a family physician in 2002 were selected from the database. The diagnosis derived from the Medical Services database was compared to the diagnosis written in the patient's medical chart. The PPV and PNV of the first operational definition based on one asthma diagnosis or more recorded in the database over a 1-year period were found to be 0.75 and 0.96 for respiratory physicians and 0.67 and 0.99 for family physicians, for patients 16-44 years old. The PPV increased to 0.78 for family physicians and to 0.77 for respiratory physicians when the second operational definition based on two diagnoses of asthma or more was used. Results tended to be lower for 45-80 years old patients. We conclude that diagnoses recorded in the Medical Services database of Quebec are valid to identify patients with asthma.
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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 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".