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Record W2794845017 · doi:10.3917/spub.181.0095

Trajectoires des patients âgés en fin de soins actifs

2018· article· fr· W2794845017 on OpenAlexaffabout
L.M.V. Zubieta, Réjean Hébert, Michel Raı̂che

Bibliographic record

VenueSanté Publique · 2018
Typearticle
Languagefr
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversité de SherbrookeUniversité de MontréalInstitut National de Santé Publique du QuébecBishop's University
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

INTRODUCTION: To determine the palliative care pathways of older patients in Sherbrooke, Qc by examining their transfers to other facilities. METHODS: This analysis was conducted by linking 3 databases: emergency department, hospitalizations and nursing homes. The study period ranged from January 2011 to December 2015. SPSS was used for statistical analysis. The study only included palliative care patients. RESULTS: 25% of patients waited less than 7 days for transfer, and 74% waited less than 3 weeks. 64.9% of patients were transferred to a long-term facility for dependent adults (LTF), 15.2% returned home or were transferred to private accommodation, and 15.9% were transferred to an intermediate care facility. One-half of patients subsequently changed facility, mainly those in homes or intermediate care. Palliative care patient bed occupation rates represented 1% of available bed-days and less than 2% of total beds for 86.4% of days. Only 12% of patients returned to hospital within 90 days after discharge. CONCLUSION: The number of beds occupied by palliative care patients does not seem to disrupt the hospital capacity. The majority of the palliative care patients were well managed, as reflected by the low readmission rate. Our results indicate good management of transfers and an adequate supply of long-term care facilities and home services.

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)0.000
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 score0.136
Threshold uncertainty score0.271

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.062
GPT teacher head0.402
Teacher spread0.339 · 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
Published2018
Admission routes2
Has abstractyes

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