Specialist paediatric palliative care program development in the standard-of-care era
Bibliographic record
Abstract
Objectives: The number of Canadian children living with serious illness is increasing. Access to specialist paediatric palliative care is recognized as essential for these children, their families, and their care providers, and yet programs remain under-resourced or non-existent in much of Canada. Health services planning requires current data. This study examined the initial experience of a specialist program established in 2015 at a tertiary paediatric centre in Canada. Methods: A prospective database study of referred patients was conducted from 2015 to 2023 (prenatal referrals were first accepted in 2021). Data were collected at referral, consult, and discharge/death/end of pregnancy. Program clinician growth was tracked. The analysis included descriptive statistics and a Kaplan-Meier survival curve. Results: The program received 650 unique paediatric referrals plus 55 prenatal referrals. The number of patients receiving care annually quadrupled over the course of the study. Two-hundred and twenty-seven children died: 99% with goal-concordant care at end-of-life and most frequently in hospital, although death at home was increasingly common. A rapid increase in program resources was required to meet care needs per modern standards of care. Conclusions: This study demonstrates that a new paediatric palliative care program was met with demand akin to existing established comparator programs. These results are congruent with the increase in prevalence of children with serious illness and the evolution of care standards to incorporate specialist care provision. These findings can help advocacy and resource planning for modernizing Canada's paediatric palliative care infrastructure.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".