Patients’, family caregivers’, and professionals’ perspectives on quality of palliative care: A qualitative study
Bibliographic record
Abstract
BACKGROUND: The quality of palliative care is the foremost preoccupation of clinicians, decision-makers, and managers as well as patients and families. Major input from healthcare professionals is required to develop indicators for the quality of palliative care, but the involvement of patients and families is also recognized as essential, even though this is rarely achieved in practice. AIM: The objectives of this study were to identify (1) convergences and divergences in the points of view of different stakeholders (patients, families, healthcare professionals) relative to key elements of the quality of palliative care and (2) avenues for refining existing indicators of quality of palliative care. DESIGN: Cross-sectional qualitative study. SETTING/PARTICIPANTS: There were six settings: two hospital-based palliative care units, one hospice, and three other medical units where a mobile palliative care team intervene. Semi-structured interviews were conducted among 61 patients, families, healthcare professionals, and managers. RESULTS: Four major dimensions of quality of care are deemed critical by patients, their families, and professionals: comprehensive support for the patients themselves, clinical management, involvement of families, and care for the imminently dying person and death. Differences exist between various stakeholders regarding perceptions of some dimensions of quality of care. Avenues for improving current quality of care indicators are identified. CONCLUSION: Our study results can be used to refine or develop quality indicators that truly mirror the points of view of patients and their families and of healthcare professionals.
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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 | 0.020 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".