Association between the Availability of Hospital-based Palliative Care and Treatment Intensity for Critically Ill Patients
Bibliographic record
Abstract
RATIONALE: In the intensive care unit (ICU), studies involving specialized palliative care services have shown decreases in the use of nonbeneficial life-sustaining therapies and ICU length of stay for patients. However, whether widespread availability of hospital-based palliative care is associated with less frequent use of high intensity care is unknown. OBJECTIVES: To determine whether availability of hospital-based palliative care is associated with decreased markers of treatment intensity for ICU patients. METHODS: Retrospective cohort study of adult ICU patients in New York State hospitals, 2008-2014. Multilevel regression was used to assess the relationship between availability of hospital-based palliative care during the year of admission and hospital length of stay, use of mechanical ventilation, dialysis and artificial nutrition, placement of a tracheostomy or gastrostomy tube, days in ICU and discharge to hospice. RESULTS: Of 1,025,503 ICU patients in 151 hospitals, 814,794 (79.5%) received care in a hospital with a palliative care program. Hospital length of stay was similar for patients in hospitals with and without palliative care programs (6 d [interquartile range, 3-12] vs. 6 d [interquartile range, 3-11]; adjusted rate ratio, 1.04 [95% confidence interval 1.03-1.05]; P < 0.001), as were other healthcare use outcomes. However, patients in hospitals with palliative care programs were 46% more likely to be discharged to hospice than those in hospitals without palliative care programs (1.7% vs. 1.4%; adjusted odds ratio, 1.46 [95% confidence interval 1.30-1.64]; P < 0.001). CONCLUSIONS: The availability of hospital-based palliative care was not associated with differences in in-hospital treatment intensity, but it was associated with significantly increased hospice use for ICU patients. Currently, the measurable benefit of palliative care programs for critically ill patients may be the increased use of hospice facilities, as opposed to decreased healthcare use during an ICU-associated hospitalization.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".