The ACA Medicaid Expansion And Perinatal Insurance, Health Care Use, And Health Outcomes: A Systematic Review
Bibliographic record
Abstract
The Affordable Care Act (ACA) Medicaid expansion increased Medicaid eligibility for low-income adults regardless of their pregnancy or parental status. Variation in states' adoption of this expansion created a natural experiment to study the effects of expanding public insurance on insurance coverage, health care use, and health outcomes during preconception, pregnancy, and postpartum. We conducted a systematic review of relevant literature on this topic, analyzing twenty-four studies published between January 2014 and April 2021. We found that the ACA Medicaid expansion increased preconception and postpartum Medicaid coverage with corresponding declines in uninsurance, private insurance coverage, and insurance churn. There was limited evidence that Medicaid expansion increased perinatal health care use or improved infant birth outcomes overall, although some studies reported reduced racial and ethnic disparities in rates of prenatal and postpartum visit attendance, maternal mortality, low birthweight, and preterm births. Stronger data collection on preconception and postpartum outcomes with sufficient sample sizes to stratify by race and ethnicity is needed to assess the full impact of the ACA and emerging Medicaid policy changes, such as the postpartum Medicaid extension.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".