International comparison of spending and utilization at the end of life for hip fracture patients
Bibliographic record
Abstract
OBJECTIVE: To identify and explore differences in spending and utilization of key health services at the end of life among hip fracture patients across seven developed countries. DATA SOURCES: Individual-level claims data from the inpatient and outpatient health care sectors compiled by the International Collaborative on Costs, Outcomes, and Needs in Care (ICCONIC). STUDY DESIGN: We retrospectively analyzed utilization and spending from acute hospital care, emergency department, outpatient primary care and specialty physician visits, and outpatient drugs. Patterns of spending and utilization were compared in the last 30, 90, and 180 days across Australia, Canada, England, Germany, New Zealand, Spain, and the United States. We employed linear regression models to measure age- and sex-specific effects within and across countries. In addition, we analyzed hospital-centricity, that is, the days spent in hospital and site of death. DATA COLLECTION/EXTRACTION METHODS: We identified patients who sustained a hip fracture in 2016 and died within 12 months from date of admission. PRINCIPAL FINDINGS: Resource use, costs, and the proportion of deaths in hospital showed large variability being high in England and Spain, while low in New Zealand. Days in hospital significantly decreased with increasing age in Canada, Germany, Spain, and the United States. Hospital spending near date of death was significantly lower for women in Canada, Germany, and the United States. The age gradient and the sex effect were less pronounced in utilization and spending of emergency care, outpatient care, and drugs. CONCLUSIONS: Across seven countries, we find important variations in end-of-life care for patients who sustained a hip fracture, with some differences explained by sex and age. Our work sheds important insights that may help ongoing health policy discussions on equity, efficiency, and reimbursement in health care systems.
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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 | 0.001 | 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 | 0.000 |
| 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".