A Map of Racial and Ethnic Disparities in Influenza Vaccine Uptake in the Medicare Fee-for-Service Program
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Despite improved understanding of the risks of influenza and better vaccines for older patients, influenza vaccination rates remain subpar, including in high-risk groups such as older adults, and demonstrate significant racial and ethnic disparities. METHODS: This study considers demographic, clinical, and geographic correlates of influenza vaccination among Medicare Fee-for-Service (FFS) beneficiaries in 2015-2016 and maps the data on a geographic information system (GIS) at the zip code level. RESULTS: Analyses confirm that only half of the senior beneficiaries evidenced a claim for receiving an inactivated influenza vaccine (IIV), with significant disparities observed among black, Hispanic, rural, and poorer beneficiaries. More extensive disparities were observed for the high-dose (HD) vaccine, with its added protection for older populations and confirmed economic benefit. Most white beneficiaries received HD; no non-white subgroup did so. Mapping of the data confirmed subpar vaccination in vulnerable populations with wide variations at the zip code level. CONCLUSION: Urgent and targeted efforts are needed to equitably increase IIV rates, thus protecting the most vulnerable populations from the negative health impact of influenza as well as the tax-paying public from the Medicare costs from failing to do so.
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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 it