Comparison of Health Care Utilization: U.S. versus Canada
Bibliographic record
Abstract
Objective. To compare health care utilization between Canadian and U.S. residents.Data Sources. Nationally representative 2007 surveys from the Medical Expenditure Panel Survey (MEPS) for the U.S. and the Canadian Community Health Survey (CCHS) for Canada.Study Design. We use descriptive and multivariate methods to examine differences in health care utilization rates for visits to medical providers, nurses, chiropractors, specialists, dentists, and overnight hospital stays, usual source of care, Pap smear tests and mammograms. Principal Findings. The poor and less educated were more likely to utilize health care in Canada than in the U.S. The differences were especially pronounced for having a usual source of care and for visits to providers, specialists, and dentists. Health care use for residents with high incomes and higher levels of education were not markedly different between the two countries and often higher for U.S residents. Foreign-born residents were more likely to use health care in Canada than in the U.S. The descriptive results were confirmed in multivariate regressions.Conclusions. Given the magnitude of our results, the health insurance structure in Canada might have played an important role in improving access to care for subpopulations examined in this study.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.014 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".