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Record W2611547096 · doi:10.1177/2333721416684400

Transitions Between Care Settings at the End of Life Among Older Homecare Recipients

2016· article· en· W2611547096 on OpenAlexafffundabout
Sneha Abraham, Verena Menec

Bibliographic record

VenueGerontology and Geriatric Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of Manitoba
FundersMax Rady College of Medicine, University of Manitoba
KeywordsMedicineGerontologyEnd-of-life careHealth careCohortNursingPalliative care

Abstract

fetched live from OpenAlex

Objectives: Objectives were to (a) describe transitions between care settings in older homecare recipients at the end of life, and (b) examine what personal (e.g., age, sex) and health system factors (e.g., hospital bed supply) predict care transitions. Methods: The study involved analysis of administrative health care data and was based on a complete cohort of homecare recipients aged 65 years or older who died in Manitoba, Canada between 2003 and 2006 ( N = 7,866). Results: More than half of homecare recipients had at least one care transition in the last 30 days before death and 21% had two or more hospitalizations in the last 90 days. Both personal characteristics and health system factors were related to transitions and hospitalizations. Discussion: The findings suggest that homecare recipients are an important population to focus on in terms of reducing potentially burdensome transitions and enhancing the end-of-life experience for them and their family.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.059
GPT teacher head0.356
Teacher spread0.297 · 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

Citations29
Published2016
Admission routes3
Has abstractyes

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