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Record W2402393495 · doi:10.1177/082585971503100203

Predictors of Place of Death for those in Receipt of Home-Based Palliative Care Services in Ontario, Canada

2015· article· en· W2402393495 on OpenAlexafffundabout
Denise N. Guerriere, Amna Husain, Denise Marshall, Brandon Zagorski, Hsien Seow, Kevin Brazil, Julia Kennedy, Robin McLernon, Sheri Burns, Peter C. Coyte

Bibliographic record

VenueJournal of Palliative Care · 2015
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsSt. Joseph’s Healthcare HamiltonJuravinski Cancer CentreMount Sinai HospitalMcMaster UniversityUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsReceiptPlace of deathPalliative careMedicineFamily medicineNursingGerontologyMedical emergencyBusiness

Abstract

fetched live from OpenAlex

Many cancer patients die in institutional settings despite their preference to die at home. A longitudinal, prospective cohort study was conducted to comprehensively assess the determinants of home death for patients receiving home-based palliative care. Data collected from biweekly telephone interviews with caregivers (n = 302) and program databases were entered into a multivariate logistic model. Patients with high nursing costs (odds ratio [OR]: 4.3; confidence interval [CI]: 1.8-10.2) and patients with high personal support worker costs (OR: 2.3; CI: 1.1-4.5) were more likely to die at home than those with low costs. Patients who lived alone were less likely to die at home than those who cohabitated (OR: 0.4; CI: 0.2-0.8), and those with a high propensity for a home-death preference were more likely to die at home than those with a low propensity (OR: 5.8; CI: 1.1-31.3). An understanding of the predictors of place of death may contribute to the development of effective interventions that support home death.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.480
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.102
GPT teacher head0.376
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations40
Published2015
Admission routes3
Has abstractyes

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