Adjusted Mortality Rates Are Lower For Medicare Advantage Than Traditional Medicare, But The Rates Converge Over Time
Bibliographic record
Abstract
Overall mortality rates, adjusted for age, sex, and Medicaid status, in Medicare Advantage have been below those in traditional Medicare for many years. Much attention has been paid to the resulting issue of favorable selection in Medicare Advantage. The common study design used to estimate causal effects of Medicare Advantage on utilization and outcomes compares new Medicare Advantage beneficiaries immediately before and after enrollment in Medicare Advantage with beneficiaries who choose to remain in traditional Medicare. What has not been studied is the mortality experience of a cohort that initially chooses enrollment in Medicare Advantage versus one that chooses traditional Medicare. In this study we found that the adjusted mortality rate of a cohort newly enrolled in Medicare Advantage was initially well below that of a cohort newly enrolled in traditional Medicare, but the difference markedly decreased after five years. As a result, the common study design is flawed because it assumes that any initial difference in mortality risk remains constant after enrollment in Medicare Advantage. In other words, those initially choosing Medicare Advantage become sicker relative to traditional Medicare beneficiaries over five years. Whether the mortality rates would fully converge if a period longer than five years were observed is a topic for further research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.006 | 0.001 |
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".