Refining Estimates of Public Health Spending as Measured in National Health Expenditure Accounts
Bibliographic record
Abstract
The recent focus on public health stemming from, among other things, severe acute respiratory syndrome and avian flu has created an imperative to refine health-spending estimates in the Canadian Health Accounts. This article presents the Canadian experience in attempting to address the challenges associated with developing the needed taxonomies for systematically capturing, measuring, and analyzing the national investment in the Canadian public health system. The first phase of this process was completed in 2005, which was a 2-year project to estimate public health spending based on a more classic definition by removing the administration component of the previously combined public health and administration category. Comparing the refined public health estimate with recent data from the Organization for Economic Cooperation and Development still positions Canada with the highest share of total health expenditure devoted to public health than any other country reporting. The article also provides an analysis of the comparability of public health estimates across jurisdictions within Canada as well as a discussion of the recommendations for ongoing improvement of public health spending estimates. The Canadian Institute for Health Information is an independent, not-for-profit organization that provides Canadians with essential statistics and analysis on the performance of the Canadian health system, the delivery of healthcare, and the health status of Canadians. The Canadian Institute for Health Information administers more than 20 databases and registries, including Canada's Health Accounts, which tracks historically 40 categories of health spending by 5 sources of finance for 13 provincial and territorial jurisdictions. Until 2005, expenditure on public health services in the Canadian Health Accounts included measures to prevent the spread of communicable disease, food and drug safety, health inspections, health promotion, community mental health programs, public health nursing, as well as all the costs for the general administration of government health departments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.069 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".