Home versus Hospice Inpatient Care: Discharge Characteristics of Palliative Care Patients in an Acute Care Hospital
Bibliographic record
Abstract
This prospective survey was initiated to identify factors that helped and hindered home discharge for 100 consecutive patients who did not require further specialist palliative or acute care. Information was collected on demographics, functional ability (using the Palliative Performance Scale [PPS] and Karnofsky Performance Scale [KPS]), cognitive function at discharge as measured by the Mini-Mental State Examination (MMSE), home support circumstances, and patient and family preference for discharge. 59 patients were discharged home and 41 were transferred to a hospice. Younger patients with younger caregivers were discharged home more often. Patients with better MMSE and better functional ability (PPS and KPS) were also more likely to go home. Patients going home were more likely to be married. Preference for site of discharge was met for 76% of patients and 90% of families. Of the patients going to a hospice, 24% of patients and 7% of families preferred a home discharge. More physical support at home could have facilitated a home discharge for 13 patients. Functionally dependent and cognitively impaired patients were generally unable to return home. To support patients and their families in an environment of their choice, access to increased physical support in the home must be addressed.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".