How Single-payer Stacks Up: Evaluating Different Models of Universal Health Coverage on Cost, Access, and Quality
Bibliographic record
Abstract
Described as "universal prepayment," the national health insurance (or single-payer) model of universal health coverage is increasingly promoted by international actors as a means of raising revenue for health care and improving social risk protection in low- and middle-income countries. Likewise, in the United States, the recent failed efforts to repeal and replace the Affordable Care Act have renewed debate about where to go next with health reform and arguably opened the door for a single-payer, Medicare-for-All plan, an alternative once considered politically infeasible. Policy debates about single-payer or national health insurance in the United States and abroad have relied heavily on Canada's system as an ideal-typical single-payer system but have not systematically examined health system performance indicators across different universal coverage models. Using available cross-national data, we categorize countries with universal coverage into those best exemplifying national health insurance (single-payer), national health service, and social health insurance models and compare them to the United States in terms of cost, access, and quality. Through this comparison, we find that many critiques of single-payer are based on misconceptions or are factually incorrect, but also that single-payer is not the only option for achieving universal coverage in the United States and internationally.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".