Agreement between survey data and Régie de l'assurance maladie du Québec (RAMQ) data with respect to the diagnosis of asthma and medical services use for asthma in children
Bibliographic record
Abstract
INTRODUCTION: The goal of this study was to assess the agreement between the results of a respiratory health survey conducted in Montréal on children aged 6 months to 12 years and the Régie de l'assurance maladie du Québec (RAMQ, Quebec health insurance board) database in terms of the diagnosis of asthma and medical services use. A secondary aim was to evaluate the effect of the survey method used (Internet-based survey or telephone survey). METHODS: We assessed whether a diagnosis of asthma was made for 7922 children. In addition, we compared the use of medical services for asthma (emergency department visits and hospitalizations) in the 12 months preceding the survey for the 402 children considered to have asthma, using 2 groups of respiratory diagnoses and 2 data linkage periods. The agreement between the 2 data sources was evaluated using the kappa statistic (κ) and sensitivity and specificity, as well as percentages of agreement, overreporting and under-reporting with respect to health services use. RESULTS: Moderate agreement was found between the 2 data sources (survey and RAMQ data) in terms of the diagnosis of asthma (κ = 0.54 and κ = 0.60 depending on the definition used). Specificity was high (93% and 96%), but sensitivity varied (50% and 65%). Respondents over-reported health services use, resulting in moderate kappa values (0.49 for emergency department visits and 0.48 for hospitalizations). However, when more diagnoses were included in the definition and when the linkage period was extended (15 rather than 12 months), the kappa values increased (0.59 for emergency department visits and 0.64 for hospitalizations) and sensitivity and specificity were high. Slightly higher agreement was obtained for the Internet-based survey relative to the telephone survey. CONCLUSION: The findings validate the use of survey data with respect to the diagnosis of pediatric asthma and major health services use for this disease.
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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 | 0.030 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".