Preferred and Actual Location of Death: What Factors Enable a Preferred Home Death?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Fulfillment of patient preferences for location of dying is of continued end-of-life care interest. Of those voicing a preference, most prefer home. However the majority of deaths occur in an institutional setting. OBJECTIVES: The study objective was to report on the congruence between the last preferred and actual location of death among adult Nova Scotians who died from chronic disease, and to identify individual, illness-related, and environmental factors associated with achieving a preferred home death. METHODS: The study employed a population-based mortality follow-back telephone survey interview. Subjects were eligible death certificate identified informants (next-of-kin) of adults (aged 18+) (n = 1316) who died of advanced chronic diseases in the Canadian province of Nova Scotia between June 2009 and May 2011 who were knowledgeable about the decedent's care over the last month of life. Congruence was assessed as to whether or not the decedent died in their preferred death location. Among decedents preferring a home death, individual, illness-related, and environmental risk factor multivariable analyses were used to identify predictors of home death achievement. RESULTS: Among all who voiced a preference (n = 606), 52% died in their preferred location (kappa: 0.29). Factors contributing independently to achievement of a preferred home death were emotional needs being met, nursing and family physician home visits, palliative care program involvement, and being at home for the majority of the last month. CONCLUSIONS: This study identifies elements of primary and integrated care that address the gap between preferred and actual place of care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| 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 | 0.000 |
| 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 it