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Record W2065475319 · doi:10.1097/mlr.0b013e3180536779

Socioeconomic Status, Access to Health Care, and Outcomes After Acute Myocardial Infarction in Canada's Universal Health Care System

2007· article· en· W2065475319 on OpenAlexaffabout
Louise Pilote, Jack V. Tu, Karin H. Humphries, Hassan Behouli, Patrick Bélisle, Peter C. Austin, Lawrence Joseph

Bibliographic record

VenueMedical Care · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsUniversity of British ColumbiaInstitute for Clinical Evaluative SciencesMcGill University Health CentreSunnybrook Health Science CentreUniversity of TorontoMontreal General Hospital
Fundersnot available
KeywordsSocioeconomic statusMedicineDemographyReimbursementOdds ratioLogistic regressionMyocardial infarctionHealth careOddsHousehold incomeGerontologyEnvironmental healthPopulationGeographyInternal medicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: There is a debate as to whether universal drug coverage confers similar access to care at all socioeconomic status (SES) levels. Experiences in Canada may bring light to questions raised regarding access. OBJECTIVE: To assess associations between SES and access to cardiac care and outcomes in Canada's universal health care system. DESIGN, SETTING, AND PATIENTS: All patients admitted to acute care hospitals in Quebec (QC), Ontario (ON), and British Columbia (BC), between 1996 and either 2000 (QC) or 2001 (ON, BC) with acute myocardial infarction, were identified using provincial government administrative databases (n = 145,882). MEASUREMENTS: Variables representing SES grouped at the census area level were examined in association with use of cardiac medications and procedures, survival, and readmission, while adjusting for individual-level variables. A Bayesian hierarchical logistic regression model was used to account for the nested structure of the data. RESULTS: Despite provincial variations in SES and drug reimbursement policies, there were generally no associations between the SES variables and access to cardiac medications or invasive cardiac procedures. The few exceptions were not consistent across SES indicators and/or provinces. Similarly, the only observed effect of SES on clinical outcomes was in BC, where there was increased 1-year mortality among patients living in less-affluent regions (adjusted odds ratios per standard deviation change in proportion of low-income households, 95% Bayesian credible intervals, QC: 1.09, 0.96-1.25; ON: 1.02, 0.95-1.08; and BC: 1.18, 1.09-1.28). CONCLUSIONS: These results suggest that intermediary factors other than SES, such as cardiovascular risk factors, likely account for observed "wealth-health" gradients in Canada. Implementation of a universal drug coverage policy could decrease socioeconomic disparities in access to health care.

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)0.005
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 score0.025
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.010
GPT teacher head0.269
Teacher spread0.259 · 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

Citations54
Published2007
Admission routes2
Has abstractyes

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