Health Care Utilization by Canadian Women
Bibliographic record
Abstract
Health Issues: While women are reported to be more frequent users of health services in Canada, differences in women's and men's health care utilization have not been fully explored. To provide an overview on women's healthcare utilization, we selected two key issues that are important for public policy purposes: access to care and patterns of utilization. These issues are examined using primarily data from the 1998/99 National Population Health Survey, complemented by the 2000 Canadian Community Health Survey and the 2001 Health Service Access Survey. Key Findings • Women are twice as likely as men to report a regular family physician, but that proportion is very low (15.8%). • Women report significantly shorter specialist wait times (20.9 days) than men (55.4 days) for mental health, while the reverse is true for asthma and other breathing conditions (10.8 for men, 78.8 for women). • Reported mean wait times are significantly lower for men than for women pertaining to overall diagnostic tests: for MRI, 70.3 days for women compared to 29.1 days for men. Data Gaps and Recommendations • Measurement of possible system bias and its implication for equitable and quality healthcare for women requires larger provincial samples of the national surveys, along with a longitudinal design. • Either a national database on preventive services, or better alignment of provincial databases pertaining to health promotion and preventive services, is needed to facilitate data linkage with national surveys to undertake longitudinal studies that support gender based analyses.
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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 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".