Concentrating Hospital-Wide Deaths in a Palliative Care Unit: The Effect on Place of Death and System-Wide Mortality
Bibliographic record
Abstract
INTRODUCTION: We studied the impact of an 11-bed inpatient palliative care unit (PCU) on site of death and observed mortality in the health system, oncology, and palliative care units. Observers were concerned that an active PCU would attract dying patients and worsen comparative mortality rates for Medicare and U.S. News & World Report comparisons. METHODS: We reviewed 10 years of experience with all patients who died in the hospital before and after we opened our PCU in 2000. RESULTS: The PCU concentrated dying patients on the PCU but total deaths did not change over 10 years and remained approximately 3% of admissions. Within 2 years, one quarter of all health system decedents died on the PCU. The proportion who died on the oncology floor and general units declined, but the number of intensive care unit deaths did not change. CONCLUSIONS: An inpatient PCU did not increase the hospital-wide death rate. The PCU did change the site of death to a more appropriate venue for one quarter of patients.
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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".