A Review of the Essential Components of Quality Palliative Care in the Home
Bibliographic record
Abstract
OBJECTIVE: The home is an important and often preferable setting of palliative care. While much research has demonstrated the benefits of specialized palliative homecare on patient and system outcomes, there has been little delineation of the underlying components of these efficacious programs. We synthesized the essential elements of palliative homecare from a combined review of successful programs, perspectives of patients and caregivers, and views of healthcare providers in palliative care. METHODS: Five unique palliative homecare studies were included in the rapid review and synthesis-(1) systematic review of the components of efficacious programs; (2) in-depth analysis of 11 effective community-based teams; (3) survey of bereaved caregivers; (4) survey of the general public; and (5) interviews of providers and administrators. A qualitative approach was used to identify transcending themes across the studies. RESULTS: Six essential elements of quality palliative homecare were common across the studies: (1) Integrated teamwork; (2) Management of pain and physical symptoms; (3) Holistic care; (4) Caring, compassionate, and skilled providers; (5) Timely and responsive care; and (6) Patient and family preparedness. CONCLUSIONS: Our metasynthesis of effective palliative homecare models, as well as, the values of those who use and provide these services, illuminates the underpinning elements of quality home-based care for patients with a life-limiting illness. However, the application of these elements must be relevant to the local community context. To create impactful, sustainable homecare programs, it is critical to capitalize on existing processes, partnerships, and assets.
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.
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 | 0.023 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.024 | 0.024 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".