Variation in Site of Death among Nursing Home Residents in British Columbia, Canada
Bibliographic record
Abstract
OBJECTIVE: To assess the proportion of in-hospital versus in-nursing home deaths among a population of decedent nursing home residents in British Columbia, Canada, and to identify facility and individual characteristics associated with in-hospital death. METHODS: We examined nursing home (ownership/organization, size) and individual (age, level of care, sex, previous hospitalization within 30 days) characteristics of all decedent residents of British Columbia's freestanding publicly funded nursing homes. Secondary administrative data from the Ministry of Health, supplemented with facility data were analyzed. The study population included those aged 65 years and older who died between April 1, 1996 and August 1, 1999 (n = 14,413). Mixed models were used to estimate unadjusted and adjusted odds ratios (AOR; 95% confidence intervals [CI]) for factors associated with in-hospital death. RESULTS: Almost one quarter (24.6%) of deaths occurred in hospital. In-hospital death was more frequent in nonprofit (NP) single-site facilities compared to NP facilities owned and/or operated by a health authority (AOR = 1.37, 95% CI: 1.15, 1.64). Smaller nursing home size (AOR = 1.25, 95% CI: 1.05, 1.50) and male gender (AOR = 1.17, 95% CI: 1.07, 1.27) were also associated with a greater odds of in-hospital death. Progressively lower odds ratios of in-hospital death were observed for each category of increasing age and declining function, respectively. CONCLUSIONS: While individual characteristics play a significant role in explaining variation in site of death, residence in a NP single-site and smaller-sized facility was also associated with a greater frequency of in-hospital death.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".