How End-Of-Life Home Care Services Are Used from Admission to Death: A Population-Based Cohort Study
Bibliographic record
Abstract
AIM: Our goal was to describe the trajectories of end-of-life nursing and personal support worker (PSW) use from home care admission until death. METHODS: We studied a historical prospective cohort of end-of-life home care patients in Ontario, Canada, linking administrative databases. We calculated the odds of using any nursing or PSW hours and the incidence rate ratio of services used for each week approaching death, controlling for confounders. RESULTS: Among all patients (n = 11,867), the odds of using any nursing and PSW hours increased by 4 percent and 10 percent, respectively, each week closer to death. Among patients using services, the ratio of nursing and PSW hours increased 20 percent and 11 percent, respectively, in the last 4 weeks of life compared to use at 24 weeks before death. CONCLUSION: Use of nursing and PSW hours increases slightly each week before death and sharply in the last month of life. Understanding the trajectory of home care services use can help decision makers design better end-of-life care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".