Beneficiaries Respond To California’s Program To Integrate Medicare, Medicaid, And Long-Term Services
Bibliographic record
Abstract
In 2014 California implemented a demonstration project called Cal MediConnect, which used managed care organizations to integrate Medicare and Medicaid, including long-term services and supports for beneficiaries dually eligible for Medicare and Medicaid. Postenrollment telephone surveys assessed how enrollees adjusted to Cal MediConnect over time. Results showed increased satisfaction with benefits, improved ratings of quality of care, fewer acute care visits, and increased personal care assistance hours over time. Enrollees also had somewhat better prescription medication access and lower unmet needs for personal care, compared to the comparison group. The lack of improvement in care coordination raises concerns about the implementation of the care coordination benefit, a key feature of the program. The Bipartisan Budget Act of 2018 contains provisions that permanently certify the use of managed care (such as Dual Eligible Special Needs Plans) to integrate Medicare and Medicaid, which makes the lessons learned from California's duals demonstration especially relevant for informing other integrated programs for seniors and people with disabilities.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.001 |
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 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".