State-Level Surveillance of Underinsurance and Health Care-Related Financial Burden
Bibliographic record
Abstract
BACKGROUND: The Affordable Care Act (ACA) has reduced uninsurance, but underinsurance, health care-related financial burden, and dental uninsurance may not follow suit. Underinsurance is associated with reduced access to care, household debt, and bankruptcy but has been difficult to track without economic data. METHODS: We used readily available state-level survey data to build a model that states can adopt to implement surveillance over underinsurance and health care-related financial burden, as well as assess related disparities and health profiles. RESULTS: The state prevalence of underinsurance and dental uninsurance did not change in the first year of the ACA's individual mandate. Underinsurance was associated with poorer health-related quality-of-life measures: compared with the fully insured, underinsured adults had an adjusted odds ratio of 2.40 (95% CI, 1.71-3.38) of fair or poor general health. CONCLUSION: Tracking underinsurance and medical debt can help public health and health care access stakeholders evaluate which mechanisms (deductibles, co-pays, uncovered services, or is proportionately priced health care services and products) are barriers to care and improved health outcomes.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".