Practices Caring For The Underserved Are Less Likely To Adopt Medicare’s Annual Wellness Visit
Bibliographic record
Abstract
In 2011 Medicare introduced the annual wellness visit to help address the health risks of aging adults. The visit also offers primary care practices an opportunity to generate revenue, and may allow practices in accountable care organizations to attract healthier patients while stabilizing patient-practitioner assignments. However, uptake of the visit has been uneven. Using national Medicare data for the period 2008-15, we assessed practices' ability and motivation to adopt the visit. In 2015, 51.2 percent of practices provided no annual wellness visits (nonadopters), while 23.1 percent provided visits to at least a quarter of their eligible beneficiaries (adopters). Adopters replaced problem-based visits with annual wellness visits and saw increases in primary care revenue. Compared to nonadopters, adopters had more stable patient assignment and a slightly healthier patient mix. At the same time, visit rates were lower among practices caring for underserved populations (for example, racial minorities and those dually enrolled in Medicaid), potentially worsening disparities. Policy makers should consider ways to encourage uptake of the visit or other mechanisms to promote preventive care in underserved populations and the practices that serve them.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".