Medical Expenditures during the Last Year of Life: Findings from the 1992–1996 Medicare Current Beneficiary Survey
Bibliographic record
Abstract
OBJECTIVE: To compare medical expenditures for the elderly (65 years old) over the last year of life with those for nonterminal years. DATA SOURCE: From the 1992-1996 Medicare Current Beneficiary Survey (MCBS) data from about ten thousand elderly persons each year. STUDY DESIGN: Medical expenditures for the last year of life and nonterminal years by source of payment and type of care were estimated using robust covariance linear model approaches applied to MCBS data. DATA COLLECTION: The MCBS is a panel survey of a complex weighted multilevel random sample of Medicare beneficiaries. A structured questionnaire is administered at four-month intervals to collect all medical costs by payer and service. Medicare costs are validated by claims records. PRINCIPAL FINDINGS: From 1992 to 1996, mean annual medical expenditures (1996 dollars) for persons aged 65 and older were $37,581 during the last year of life versus $7,365 for nonterminal years. Mean total last-year-of-life expenditures did not differ greatly by age at death. However, non-Medicare last-year-of-life expenditures were higher and Medicare last-year-of-life expenditures were lower for those dying at older ages. Last-year-of-life expenses constituted 22 percent of all medical, 26 percent of Medicare, 18 percent of all non-Medicare expenditures, and 25 percent of Medicaid expenditures. CONCLUSIONS: While health services delivered near the end of life will continue to consume large portions of medical dollars, the portion paid by non-Medicare sources will likely rise as the population ages. Policies promoting improved allocation of resources for end-of-life care may not affect non-Medicare expenditures, which disproportionately support chronic and custodial 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".