Changes In End-Of-Life Care In The Medicare Shared Savings Program
Bibliographic record
Abstract
End-of-life care is often overly aggressive and inconsistent with patients' preferences. Although end-of-life care could therefore be a natural target for accountable care organizations (ACOs) in their efforts to reduce spending, identifying and curbing wasteful care for patients at high risk of death may be challenging. To date, the impact of ACOs on end-of-life care has not been quantified. Using fee-for-service Medicare claims through 2015 and a difference-in-differences approach, we found evidence of some changes in end-of-life care associated with providers' participation in the Medicare Shared Savings Program among both decedents and patients at high risk of death. Although generally suggestive of less aggressive care, most effects were small and inconsistent across cohorts of ACOs entering the program in different years. This suggests that ACOs have not yet substantially altered end-of-life care patterns and that additional incentives, time, or both may be needed. Alternatively, curbing wasteful end-of-life care might not be a viable source of substantial savings under population-based payment models.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".