Income inequalities in the risk of potentially avoidable hospitalisation for chronic obstructive pulmonary disease
Bibliographic record
Abstract
Introduction: Hospitalizations for ambulatory care sensitive conditions, of which chronic obstructive pulmonary disease (COPD) is among the most common, represent an indirect measure of the healthcare system to manage chronic disease. Research has pointed to disparities in various COPD-related outcomes between persons of lower versus higher income; however, few studies have examined the influence of patients' social context on potentially avoidable COPD admissions. Objective: The research explores the use of linked population census and administrative health data to assess the influence of income inequalities on the risk of hospitalization and rehospitalization for COPD among Canadian adults. Methods: This analysis utilizes data from the 2006 Census linked longitudinally to the 2006/07-2008/09 Discharge Abstract Database. Multiple logistic regressions were conducted to assess the independent influence of income inequality on the risks of hospitalization and of six-month readmission due to COPD among the population aged 30-69, controlling for age, sex, education and other sociodemographic characteristics. Results: Compared with adults in the most affluent income quintile, the adjusted odds of COPD hospitalization were significantly greater in the 4th highest income quintile (OR: 1.38; 95%CI: 1.30-1.47), and peaked for those in the least affluent quintile (OR: 2.92; 95%CI: 2.77-3.09). Among individuals who had been hospitalized at least once for COPD in the study period, and compared with the most affluent group, the adjusted odds of readmission were highest in the least affluent group (OR: 1.39; 95%CI: 1.22-1.58). Conclusions: Despite Canada's system of universal coverage for physician and hospital care, a clear income gradient in the risk of being hospitalized and, to some extent, rehospitalized for COPD, is found. Income inequalities may be contributing to excess hospitalizations, reinforcing the importance of integrating social and economic issues in primary care to meet the ambulatory needs of this population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".