Does Inpatient Palliative Care Facilitate Home-Based Palliative Care Postdischarge? A Retrospective Cohort Study
Bibliographic record
Abstract
Introduction: Evidence of the impact of inpatient palliative care on receiving home-based palliative care remains limited. Objectives: The objective of this study was to examine, at a population level, the association between receiving inpatient palliative care and home-based palliative care postdischarge. Design: We conducted a retrospective cohort study to examine the association between receiving inpatient palliative care and home-based palliative care within 21 days of hospital discharge among decedents in the last six months of life. Setting/Subjects: We captured all decedents who were discharged alive from an acute care hospital in their last 180 days of life between April 1, 2014, and March 31, 2017, in Ontario, Canada. The index event was the first hospital discharge furthest away from death (i.e., closest to 180 days before death). Results: Decedents who had inpatient palliative care were significantly more likely to receive home-based palliative care after discharge (80.0% vs. 20.1%; p < 0.001). After adjusting for sociodemographic and clinical covariates, the odds of receiving home-based palliative care were 11.3 times higher for those with inpatient palliative care (95% confidence interval [CI]: 9.4–13.5; p < 0.001). The strength of the association incrementally decreased as death approached. The odds of receiving home-based palliative care after a hospital discharge 60 days before death were 7.7 times greater for those who received inpatient palliative care (95% CI: 6.0–9.8). Conclusion: Inpatient palliative care offers a distinct opportunity to improve transitional care between hospital and home, through enhancing access to home-based palliative care.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".