Income-related inequities: Cross-sectional analyses of the use of medicare services in British Columbia in 1992 and 2002.
Bibliographic record
Abstract
BACKGROUND: The primary demonstration of the principle of income-related equity in Canada is the provision of health care services based on need rather than ability to pay. Despite this principle, Canada, along with other OECD countries, exhibits income-related variations in the use of health care services. This paper extends previous analyses to include surgical day care, assesses changes in income-related equity between 1992 and 2002 in British Columbia and tests the feasibility of using administrative data for general equity analyses. METHODS: Data derive from the BC Linked Health Database and from a custom tabulation of income tax filer data provided by Statistics Canada. Cross-sectional analyses measure inequity in the probability and conditional use of services using concentration indices, which summarize health care services use for individuals ranked by income, after standardization for age, sex, region of residence and need for health care services. RESULTS: Small but systematic relationships were found between income and use of health care services for all types of services, with the exception of visits to general practitioners (GPs). Lower income is associated with greater conditional use of GPs and greater use of acute inpatient care. Higher income is associated with the greater use of specialist and surgical day care services; the latter inequity was found to grow substantially over time. CONCLUSIONS: Deviations from equity deserve further investigation, especially because the use of day care surgery is continually expanding. For example, an understanding of the reasons for differential admission rates to acute and day surgery might provide insight as to whether community-based services could help shift some acute care use among lower income groups to surgical day care. It is possible to use administrative data to monitor income-related equity, and future research should take advantage of this possibility.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".