Healthcare utilization and costs of pediatric home mechanical ventilation in Canada
Bibliographic record
Abstract
Background and Objectives: Children using home mechanical ventilation (HMV) live at home for better quality of life, despite financial burden for their family. Previous studies of healthcare utilization and costs do not consider public and private expenditures, including family caregiver time. We sought to determine public and private healthcare utilization and costs for children using HMV and to examine factors associated with highest costs. Methods: Longitudinal, prospective, observational cost analysis study (2012-2014) on public and private (out-of-pocket, 3rd party insurance, caregiving) costs every 2 weeks for 6 months using the Ambulatory Home Care Record. Functional Independence Measure (FIM), WeeFIM and Caregiver Impact Scale (CIS) were collected at baseline and study completion. Regression modelling examined a priori selected variables associated with monthly costs using Andersen & Newman’s framework for healthcare utilization. 2015 Canadian dollars ($1CAD=$0.78USD=€0.71). Results: We enrolled 42 children and their caregivers. Overall median (interquartile range) monthly healthcare cost was $12,131 ($8,159-15,958) comprising $9,929 (89%) for family caregiving hours, $996 (9%) publicly funded and $252 (2%) out-of-pocket (<1% third party insurance) costs. For every 10 FIM points (lower dependency), median costs were reduced by 4.5% (95% confidence interval 8.3-0.5%), adjusted for age, sex, tracheostomy and daily ventilation duration. Conclusions: For HMV children, most healthcare costs were from family caregiving. The most dependent children had highest costs. The financial burden to family caregivers is substantial and must be considered in future policy decisions related to pediatric HMV.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".