Age, costs of acute and long-term care and proximity to death: evidence for 1987-88 and 1994-95 in British Columbia
Bibliographic record
Abstract
BACKGROUND: the consequences of ageing populations for health care costs have become a concern for governments and health care funders in most countries. However, there is increasing evidence that costs are more closely related to proximity to death than to age. This means that projections using age-specific costs will exaggerate the impact of ageing. Previous studies of the relationship of age, proximity to death and costs have been restricted to acute medical care. OBJECTIVE: to assess the effects of age and proximity to death on costs of both acute medical care and nursing and social care, and to assess if this relationship was stable in a time of rapid change in health care expenditure. DESIGN AND METHODS: we compared all decedents in the chosen age categories for the years 1987-88 and 1994-95 with all survivors in the same age groups. We measured use of health and social care for each individual using the British Columbia linked data, and costs of care assessed by multiplying the number of services by the unit cost of each service. SETTING: the Province of British Columbia. SUBJECTS: all decedents in 1987-88 and 1994-95 in British Columbia in the chosen age groups, and all survivors in the same age groups. RESULTS: costs of acute care rise with age, but the proximity to death is a more important factor in determining costs. The additional costs of dying fall with age. In contrast, costs of nursing and social care rise with age, but additional costs for those who are dying increase with age. Similar patterns were found for the two cohorts. CONCLUSIONS: age is less important than proximity to death as a predictor of costs. However, the pattern of social and nursing care costs is different from that for acute medical care. In planning services it is important to take into account the relatively larger impact of ageing on social and nursing care than on acute care.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".