Associations of Medicaid Expansion With Access to Care, Severity, and Outcomes for Acute Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND: Multiple states have not expanded Medicaid under the Affordable Care Act, resulting in higher uninsured rates in states with high stroke burdens. This study aimed to evaluate the association of Medicaid expansion with changes in health insurance coverage, severity of presentation, access to care, and outcomes among patients with acute ischemic stroke. METHODS: A retrospective, difference-in-differences analysis of Get With The Guidelines-Stroke registry data. The study population comprised first-time ischemic stroke admissions from 2012 to 2018 for patients aged 19 to 64 in 45 states (27 that expanded Medicaid and 18 that did not). A probable low-income cohort was defined based on having Medicaid, no insurance/self-pay, or undocumented insurance. Outcomes analyzed were indicators of health insurance status, stroke severity, use of emergency services, time to acute care, in-hospital mortality, receipt of rehabilitation, discharge disposition, and level of disability. RESULTS: In the starting population (N=342 765), Medicaid-covered stroke admissions rose from 12.2% to 18.1% in expansion states and from 10.0% to only 10.6% in nonexpansion states, while uninsured admissions declined from 15.0% to 6.7% in expansion states and from 24.0% to 19.2% in nonexpansion states. In the low-income cohort (N=95 086; 28% of starting population), Medicaid expansion was associated with increased odds of discharge to a skilled nursing facility (adjusted odds ratio, 1.33 [95% CI, 1.12-1.59]) and transfer to any rehabilitation facility among those eligible (adjusted odds ratio, 1.24 [95% CI, 1.08-1.41]) and lower odds of discharge home (adjusted odds ratio, 0.89 [95% CI, 0.80-0.98]). Expansion was not associated with any other outcomes. CONCLUSIONS: Medicaid expansion is associated with fewer uninsured hospitalizations for acute ischemic stroke and increased rehabilitation at skilled nursing facilities. More targeted interventions may be needed to improve other stroke outcomes in the low-income US population. Future research should evaluate the impact of health care reform on primary stroke prevention.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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 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".