The economic burden of prematurity in Canada
Bibliographic record
Abstract
BACKGROUND: Preterm birth is a major risk factor for morbidity and mortality among infants worldwide, and imposes considerable burden on health, education and social services, as well as on families and caregivers. Morbidity and mortality resulting from preterm birth is highest among early (< 28 weeks gestational age) and moderate (28-32 weeks) preterm infants, relative to late preterm infants (33-36 weeks). However, substantial societal burden is associated with late prematurity due to the larger number of late preterm infants relative to early and moderate preterm infants. METHODS: The aim in this study was to characterize the burden of premature birth in Canada for early, moderate, and late premature infants, including resource utilization, direct medical costs, parental out-of-pocket costs, education costs, and mortality, using a validated and published decision model from the UK, and adapting it to a Canadian setting based on analysis of administrative, population-based data from Québec. RESULTS: Two-year survival was estimated at 56.0% for early preterm infants, 92.8% for moderate preterm infants, and 98.4% for late preterm infants. Per infant resource utilization consistently decreased with age. For moderately preterm infants, hospital days ranged from 1.6 at age two to 0.09 at age ten. Cost per infant over the first ten years of life was estimated to be $67,467 for early preterm infants, $52,796 for moderate preterm infants, and $10,010 for late preterm infants. Based on population sizes this corresponds to total national costs of $123.3 million for early preterm infants, $255.6 million for moderate preterm infants, $208.2 million for late preterm infants, and $587.1 million for all infants. CONCLUSION: Premature birth results in significant infant morbidity, mortality, healthcare utilization and costs in Canada. A comprehensive decision-model based on analysis of a Canadian population-based administrative data source suggested that the greatest national-level burden is associated with moderate preterm infants due to both a large cost per infant and population size while the highest individual-level burden is in early preterm infants and the largest total population size is in late preterm infants. Although the highest medical costs are incurred during the neonatal period, greater resource utilization and costs extend into childhood.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".