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Record W2183070080

Use of acute care hospital services by immigrant seniors in Ontario: A linkage study.

2014· article· en· W2183070080 on OpenAlexaffabout
Edward Ng, Claudia Sanmartin, Jack V. Tu, Douglas G. Manuel

Bibliographic record

VenuePubMed · 2014
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsInstitute for Clinical Evaluative SciencesStatistics Canada
Fundersnot available
KeywordsImmigrationOddsMedicineDemographyLogistic regressionOdds ratioGerontologySocioeconomic statusCensusHealth carePopulationEnvironmental healthGeography
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Seniors constitute the largest group of hospital users. The increasing share of immigrants in Canada's senior population can affect the demand for hospital care. DATA AND METHODS: This study used the linked 2006 Census-Hospital Discharge Abstract Database to examine hospitalization during the 2004-to-2006 period, by immigrant status, of Ontario seniors living in the community. Hospitalization was assessed with logistic regressions; cumulative length of stay, with zero-truncated negative binomial regressions. All-cause hospitalization and hospitalizations specific to circulatory and digestive diseases were examined. RESULTS: Immigrant seniors had significantly low age-/sex-adjusted odds of hospitalization, compared with Canadian-born seniors (OR = 0.81). The odds varied from 0.4 among East Asians to 0.89 among Europeans, and rose with length of time since arrival from 0.54 for recent (1994 to 2003) to 0.86 for long-term (before 1984) immigrants. Adjustment for demographic and socio-economic characteristics did not change the overall patterns. Immigrants' cumulated length of hospital stay tended to be shorter than or similar to that of Canadian-born seniors. INTERPRETATION: Immigrant seniors, especially recent arrivals, had lower odds of hospitalization and similar time in hospital, compared with Canadian-born seniors. These patterns likely reflect differences in health status. Variations by world region and disease reflect the diverse health care needs of immigrant seniors.

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 score0.037
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.253
Teacher spread0.239 · 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

Citations15
Published2014
Admission routes2
Has abstractyes

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