Factors affecting hospice care use among long-term care facility residents in Canada
Bibliographic record
Abstract
Hospice care can improve quality of life for persons nearing end of life. Little is known about hospice care practices in long-term care facilities (LTCFs) in Canada. This thesis included 185,715 residents in LTCFs in Canada in 2015 and followed their death records to 2016 to examine the characteristics of residents who received hospice care and those who did not but may have benefitted from it. Univariate, bivariate and multivariate analyses were used depending on the variable type. Results show the actual use of hospice care in LTCFs is very low in Canada (i.e. less than 3%). Residents who received hospice care had more severe and complex clinical needs than those who did not. Findings suggest several possible barriers to hospice use in the LTCF population including ageism, rurality, and disease diagnoses. Immediate action is needed to provide improved access to, and utilization of, hospice care in LTCFs in Canada.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".