Patterns of health care use related to respiratory conditions in early life: A birth cohort study with linked administrative data
Bibliographic record
Abstract
OBJECTIVES: To identify distinctive patterns of respiratory-related health services use (HSU) between birth and 3 years of age, and to examine associated symptom and risk profiles. METHODS: This study included 729 mother and child pairs enrolled in the Toronto site of the Canadian Healthy Infant Longitudinal Development study in 2009-2012; they were linked to Ontario health administrative databases (2009-2016). A model-based cluster analysis was performed to identify distinct groups of children who followed a similar pattern of respiratory-related HSU between birth and 3 years of age, regarding hospitalization, emergency department (ED) and physician office visits for respiratory conditions and total health care costs (2016 Canadian dollars). RESULTS: The majority (estimated cluster weight = 0.905) showed a pattern of low and stable respiratory care use (low HSU) while the remainder (weight = 0.095) showed a pattern of high use (high HSU). From 0 to 3 years of age, the low- and high-HSU groups differed in mean trajectories of total health care costs ($783 per 6 months decreased to $114, vs $1796 to $177, respectively). Compared to low-HSU, the high-HSU group was associated with a constant risk of hospitalizations, early high ED utilization and physician visits for respiratory problems. The two groups differed significantly in the timing of wheezing (late onset in low-HSU vs early in high-HSU) and future total costs (stable vs increased). CONCLUSIONS: One in ten children had high respiratory care use in early life. Such information can help identify high-risk young children in a large population, monitor their long-term health, and inform resource allocation.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".