Social-economic status and rates of hospital admission for chronic disease in urban Canada.
Bibliographic record
Abstract
Socio-economic status (SES) is recognized as an important factor that influences the utilization of health-care services. We set out to explore this association in the context of hospital admissions for the treatment of ambulatory care sensitive conditions (ACSCs)--chronic conditions normally managed on an outpatient basis. We examined rates of hospital admission for the treatment of ACSCs overall and for three specific conditions: chronic obstructive pulmonary disease (COPD), diabetes and asthma in children. Data were obtained from the Canadian Institute for Health Information, the Institut national de santé du Québec, and Statistics Canada. SES was determined using a measure known as the Deprivation Index, applied at the level of the census dissemination area (DA), the smallest geographical unit for which population statistics are available. This study accounted for 46,173 urban DAs classified into low, average and high SES groups. Statistically significant variations in rates of hospital admission were found across the three SES groups for all four ACSC categories examined. For example, hospital admission rates for COPD and diabetes in the low SES group were about 3.0 and 2.7 times higher, respectively, than those in the high SES group. Further research is needed to understand the mechanisms and underlying causes of higher rates of hospital admission for the treatment of chronic disease among people with low SES.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".