16.F. Workshop: Expanding coverage and improving quality: health reforms and policy learning across North America
Bibliographic record
Abstract
Abstract Health systems globally share challenges with expanding coverage while increasing quality. This workshop organized by the North American Observatory on Health Systems and Policies (NAO) will draw on the results of major health system studies of Canada, the United States (US) and Mexico. The NAO is a partnership of researchers, governments, and health organizations in the three countries, promoting evidence-informed health system policy decision-making. It works with the European Observatory on Health Systems and Policies and other global affiliates. One of the NAO's activities is co-publishing, with the European Observatory and the University of Toronto Press, full-length books about the health care systems in each of the three countries, modeled after the European Observatory's Health System in Transition (HiT) book series that includes full-length treatments of the systems in 70 countries. In 2020 new books will be jointly released in all three countries (Canada's third edition, the US's second, and Mexico's first). This workshop has two overarching Objectives first, to describe the recent health policy developments to provide insights into the successes and challenges of the three North American countries' health systems; second, to explore the potential for policy learning across the three countries with shared challenges but quite different institutional, political and economic contexts. Lead authors of each of these studies will deliver a short presentation describing the major public health and health system challenges faced in their country, and providing an analysis of recent health sector reforms. A panel discussion will follow, facilitated by the chairperson, that will start with a speaker that brings an international perspective to comment on the areas of convergence and divergence in health sector reforms in North America with those taking place across the European region. Each of the lead authors will then respond to the questions and comments raised, and will take questions and comments from the participants. This workshop brings together leading health system and public health scholars from Canada, the US, and Mexico for the first time at this international conference, which will provide participants with an opportunity to learn about these complex and ever-changing health systems and to engage in rich and lively discussion. Key messages In-depth health system studies provide the opportunity to identify lessons that may be transferable across national boundaries. Comparing recent health reforms in the three largest North American countries provide insight into policy learning across high- and middle- income contexts.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.028 | 0.004 |
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".