Communication and Quality of Care on Palliative Care Units: A Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Clinician-patient communication is central in palliative care, but it has not been described qualitatively which specific elements of communication are important for high-quality palliative care, particularly in the inpatient setting. OBJECTIVE: Our aim was to identify elements of communication that are central to quality of care and satisfaction with care on palliative care units (PCUs), as described by inpatients, family caregivers, and health care providers. METHODS: Qualitative interviews with patients/caregivers and focus groups with staff were conducted on four PCUs. Semi-structured interviews and focus groups elicited thoughts about the characteristics of satisfaction with care and quality of care for PCU inpatients and their family caregivers. Data were analyzed using a grounded theory method with an inductive, constant comparison approach; themes were coded to saturation. RESULTS: There were 46 interviews and eight focus groups. Communication was the most prevalent theme regarding satisfaction and quality of care, with five subthemes describing elements important to patients, caregivers, and staff. These included: 1) building rapport with patients and families to build trust and kinship; 2) addressing expectations and explaining goals of care; 3) keeping patients and families informed about the patient's condition; 4) listening actively to validate patients' concerns and individual needs; and 5) providing a safe space for conversations about death and dying. CONCLUSIONS: Patients, family caregivers, and health care providers affirmed that communication is a central element of quality of care and family satisfaction on PCUs. The five subthemes identified may serve as a structure for education and for quality improvement tools in palliative care inpatient settings.
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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 | 0.016 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| 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".