Opportunities to improve end-of-life communication and decision-making for seriously ill hospitalised patients and their families
Bibliographic record
Abstract
In face-to-face interviews with seriously ill patients and/or their family members, we used a validated questionnaire to assess key components of in-hospital end-of-life (EOL) communication and decision-making at 11 Canadian hospitals. We report preliminary data from 123 seriously ill hospitalised patients (age 80±9 years, mean±SD) and 77 family members (age 62±13 years). Patients rated being comfortable and minimising suffering as 8.8±2.5 (1=not at all important; 10=very important) and avoidance of being attached to machines as 7.5±3.5. Nearly 50% of participants reported that a decision was made in hospital about the use of life-sustaining treatments (LST) in the event of a life-threatening deterioration. However, when patients were asked about EOL communication with their in-hospital care providers, only 8 (6.5%) reported receiving a disclosure of prognosis, 37 (30.1%) received information about comfort measures to control symptoms, 15 (12.2%) were asked what was important to them when considering decisions about EOL care, and 16 (13.0%) had discussed the risks and benefits of life-sustaining treatments (LST) with a physician. In family members who were asked about EOL communication regarding their relative (the patient), 12 (15.6%) received a disclosure of prognosis, 24 (31.2%) received information about comfort measures, 12 (15.6%) were asked what was important to them when considering decisions about EOL care for their relative, and 11 (14.3%) had discussed risks and benefits of LST with a physician. There are many opportunities to improve the quality of EOL communication and decision-making with seriously ill hospitalised patients and their families.
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How this classification was reachedexpand
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".