Serious Illness Conversations in Pediatrics: A Case Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Serious Illness Conversation Guide program developed by Ariadne Labs, a Joint Center for Health Systems Innovation, includes a list of patient-centered questions designed to assist clinicians to gain a more thorough understanding of their patient's life in order to inform future care decisions. In July 2017, specialist pediatric palliative care clinicians at Canuck Place Children's Hospice (CPCH) (Vancouver, BC, Canada), adapted the original guide to use with parents of children with serious illness. This tool is referred to as the Serious Illness Conversation Guide-Peds (SICG-Peds). Using the SICG-Peds, along with enhanced communication skills, can help illuminate the parents' (child's) understanding of illness and the values they hold. Expanding the application of the guide will promote goal-based, efficient, comprehensive and consistent communication between families and clinicians and help ensure that seriously ill children receive care that is tailored to their needs through the disease trajectory. This paper explores the guide through the lens of a case study. The steps-seeking permission, assessing understanding, sharing prognosis and exploring key topics (hopes, fears, strengths, critical abilities and trade-offs)-as well as formulating clinician recommendations, are described.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it