22 Family-reported experiences for the management of children in palliative care during emergency visits
Bibliographic record
Abstract
Abstract Background Almost all children receiving care from paediatric palliative care (PPC) teams will visit the emergency department at some point during their illness trajectory, especially for acute unexpected health deterioration. Previous research conducted by the author has shown that emergency providers perceive several barriers to providing high-quality care for these children, including the discomfort with goals of care discussions. The families' perspectives during their ED visits have yet to be explored. Objectives To explore the experiences of families of children followed by a PPC team during their emergency department visits. Design/Methods This is a qualitative study using 15 semi-structured interviews across 3 paediatric hospitals in Canada, from January 2021 to December 2023. Parents of children followed by a paediatric palliative care program were invited to participate if their child had ever presented to the ED during their illness trajectory. Questions aimed to explore what happened before, during and after an ED visit, as well as the overall rating of their experiences. Anonymized one-hour interviews were transcribed verbatim and analysed using thematic analysis to identify emerging themes. Results A total of 14 mothers and 3 fathers participated in the study. All families had access to a healthcare professional prior to coming to the ED, and most of the children visited the ED < 2 times per month. Main themes emerging from the interviews include the universal desire to avoid any ED visit given the unadapted physical environment, the overall long ED length-of-stay, the exhaustion of having to repeat their child’s medical history and the diagnosis uncertainty at discharge. Most parents prefer receiving direct information and engaging in honest conversations with the ED physician. Parents also acknowledge the necessity of discussing goals of care during acute deterioration, and some identify professionals’ discomfort with those discussions. Elements contributing to positive encounter in the ED include trustful relationship with ED healthcare professionals, short wait time and presence of known primary team in the ED to ensure continuity of care. Conclusion This is the first study to explore the ED experiences of families in PPC. These findings will enhance the understanding of families’ realities and adapt emergency services to the specific needs of these children.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".