Bibliographic record
Abstract
BACKGROUND: health policy makers in many countries have expressed concern over the pressures that increased numbers of older people will exert on health care costs. Previous studies have shown that, in addition to increasing size of older populations, per capita expenditures have risen disproportionately among the old compared to the middle age groups. Documentation of such trends is essential for more accurate projection of health expenditures. OBJECTIVE: we examined detailed national age-specific expenditure trends for England and Wales, comparing findings with Canada, Japan, and Australia. METHODS: we obtained total health expenditures for each age group from the UK Department of Health for time periods 1985-87 to 1996-99. We examined changes in age-specific per capita expenditure, population demographics, and the allocation of national expenditures to the different age groups. We then determined the association of changes in population, age structure, and age-specific per capita expenditure to increases in national health care expenditure for England and Wales, comparing results to Canada, Japan, and Australia. RESULTS: per capita health expenditures in England and Wales increased by 8% for ages 65 and over, compared to 31% for ages 5-64. Hence the proportion of total expenditures allocated to the population aged 65 and over decreased from 40% to 35%, a trend most noticeable for non-acute hospital costs. Demographic shifts and population growth accounted for only 18% of the observed increases in health care expenditures in England and Wales, compared to 68%, 44%, and 34% in Japan, Canada, and Australia respectively. CONCLUSIONS: in contrast to other countries, England and Wales had slower rises in per capita costs and a decreasing proportion of national expenditures allocated to older people. These differences invite future research into the actual demand drivers of these costs.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".