Universal Health Insurance and the Effect of Cost Containment on Mortality Rates: Strokes and Heart Attacks in Japan
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
For more than four decades, Japan has offered universal health insurance. Despite the demand subsidy entailed, it has kept costs low by regulatorily capping the amounts it pays doctors, particularly for the most modern and sophisticated procedures. Facing subsidized demand but stringently capped prices on complex procedures, Japanese physicians have had little incentive to invest in specialized expertise. Instead, they have invested in small private clinics and hospitals. The resulting proliferation of primitive clinics and hospitals has cut both the number of complex modern medical procedures performed, and the number of hospitals with any substantial experience in those procedures. With a quarter of the heart disease in the United States, Japan performs less than 3 percent as many coronary bypass operations and less than 6 percent as many angioplasties. Of the 855 cities and regions in Japan, 77 percent lack any hospital with substantial experience in the sophisticated modern treatment (defined below) of cerebrovascular disease, and 89 percent lack much experience in angioplasties. In this article, I estimate one of the costs of this regulatorily‐driven lack of expertise. Toward that end, I combine mortality data from 855 cities with information on local hospital expertise and local demographic composition. In the typical city, I find that the addition of one hospital with substantial experience in modern stroke treatment would cut annual stroke mortality by 7 to 16 deaths. The addition of one hospital with substantial experience in angioplasties would cut the annual deaths from heart attacks in the city by over 19.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it