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Record W6991524458

HEALTHCARE SERVICE UTILIZATION IN THE LAST 2 WEEKS OF LIFE: A POPULATION-BASED COHORT STUDY OF ONTARIO DECEDENTS

2018· dissertation· en· W6991524458 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2018
Typedissertation
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsnot available
Fundersnot available
KeywordsPalliative careLogistic regressionOddsHealth careAcute careRetrospective cohort studyEnd-of-life careCohort studyPlace of death
DOInot available

Abstract

fetched live from OpenAlex

Background: Place of death is a commonly reported indicator for assessing palliative care quality, but does not provide details of healthcare service utilization at the end-of-life, such as acute care. In particular, early palliative care has shown to reduce acute care service use, but findings are mostly limited to cancer patients with few population-based data available. Objectives: The purpose of this research is to: 1) explore place of care trajectories in the last 2 weeks of life in a general population and among distinct illness cohorts, and 2) investigate whether early versus late palliative care affects acute care use and other publically-funded services in the last 2 weeks of life. Research Design: A retrospective population-based cohort study using linked administrative health data to examine all Ontario decedents between April 1st, 2010 and December 31st, 2012. Methods: Descriptive statistics were used to examine place of care trajectories and service utilization trends in the last 2 weeks of life. Multivariable logistic regression analyses were conducted to assess in the 2 weeks before death: 1) the odds of using an acute care setting (yes/no), and 2) the odds of time spent (≤1 week or >1week) in acute care settings among users. Results: Overall, 235,159 decedents were identified. About 32% had cancer, 31% had organ failure, and 29% had frailty. Overall, 29% of decedents used a hospital two weeks before death, but this increased to 61% on the day of death. Those with cancer were the largest users of palliative-acute hospital care, while those with organ failure were the largest users of acute- hospital care. Assessing palliative care timing, 27% were early palliative care recipients, 13% were late. About 45% of early recipients had a community-based palliative care initiation, 74% of late recipients had a hospital-based initiation. Late recipients were more likely to use acute care settings; this was further modified by disease: comparing late to early recipients, cancer decedents were nearly two times more likely to spend >1 week in acute care settings (OR=1.84, 95%CI:1.83-1.85), frailty decedents were three times more likely (OR=3.04, 95%CI:3.01-3.07), and organ failure decedents were four times more likely (OR=4.04, 95%CI:4.02-4.06). Conclusion: Place of care trajectories differ greatly by disease cohort. Exploring place of care trajectories can provide details not evident when reporting solely place of death. Furthermore, early palliative care was associated with reduced acute care service use in cancer and non-cancer patients. Late initiations were associated with greater acute care use, and had the largest effect on those with organ failure and frailty, suggesting potential opportunities for improvement in non- cancer populations.

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)0.002
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 score0.055
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.041
GPT teacher head0.323
Teacher spread0.282 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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