Bibliographic record
Abstract
OBJECTIVE: To provide a population-based, Canada-wide picture of health care needs and health care use, and present it in a highly accessible manner, allowing provincial comparisons and comparisons with other international jurisdictions. DESIGN: A comparison of the rates of health care use among jurisdictions, using Canadian-population survey data and health administrative data. SETTING: Provincial jurisdictions across Canada. MAIN OUTCOME MEASURES: Canadian and provincial rates of ill health (presence of chronic conditions) and health care use (contacts with family physicians, contacts with other specialist physicians, contacts with nurses, and hospitalizations) as monthly rates per 1000 population standardized by age and sex. RESULTS: The monthly rate per 1000 population of having at least 1 chronic condition ranged from 524 in Quebec to 638 in Nova Scotia; contacts with family physicians ranged from 158 in Quebec to 295 in British Columbia; contacts with other physician specialists ranged from 53 in Saskatchewan to 79 in Ontario; and contacts with nurses ranged from 23 in British Columbia to 41 in Quebec. Hospital stays ranged from 8 to 11 per 1000 people, and rates were similar among the provinces. CONCLUSION: Recognizing the differences among jurisdictions is critical to informing health care policy across the country. Differences persisted when rates were standardized for different age and sex compositions in the provinces. This article provides a straightforward methodology using publicly available data that can be employed in each province to examine, in the future, the evolution over time of health care use by provincial jurisdictions.
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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 | 0.004 | 0.012 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".