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Record W2153835189

Implementing a discharge assessment tool in palliative home care.

2002· article· en· W2153835189 on OpenAlexaffabout
Reanne Booker

Bibliographic record

VenuePubMed · 2002
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPalliative careMedicineHome healthInclusion (mineral)Family medicineHealth careNursingIncidence (geometry)PopulationGerontologyPsychologyEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

With an aging population and limited health care resources, reflection on end-of-life care is essential. While terminally ill cancer patients spend much of their last year in the home, the literature reveals that the majority of these patients would also prefer to die at home. Despite patients' and families' cited preference for home deaths, dying at home continues to be infrequent. In Edmonton's Capital Health Region (CHR) only 16% of cancer patients died at home in 1999. While many reasons for the low incidence of home death are cited, little data exists regarding discharges from the palliative home care program in the CHR. As such, it is difficult to assess where resources are needed in the community. The implementation of a discharge assessment tool for use in the Capital Health Palliative Home Care program may provide insight into potential correlates of home death. Not only providing information on individual patients, the inclusion of such data in the palliative home care database would allow for trends to be monitored over time.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.076
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.076
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.003

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 head0.130
GPT teacher head0.392
Teacher spread0.262 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2002
Admission routes2
Has abstractyes

Explore more

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