Trends In Self-Pay Charges And Insurance Acceptance For Abortion In The United States, 2017–20
Bibliographic record
Abstract
The Hyde Amendment prevents federal funds, including Medicaid, from covering abortion care, and many states have legal restrictions that prevent private insurance plans from covering abortion. As a result, most people pay for abortion out of pocket. We examined patient self-pay charges for three abortion types (medication abortion, first-trimester procedural abortion, and second-trimester abortion), as well as facilities' acceptance of health insurance, during the period 2017-20. We found that during this time, median patient charges increased for medication abortion (from $495 to $560) and first-trimester procedural abortion (from $475 to $575) but not second-trimester abortion (from $935 to $895). The proportion of facilities that accept insurance decreased over time (from 89 percent to 80 percent). We noted substantial regional variation, with the South having lower costs and lower insurance acceptance. Charges for first-trimester procedural abortions are increasing, and acceptance of health insurance is declining. According to the Federal Reserve, one-quarter of Americans could not pay for a $400 emergency expense solely with the money in their bank accounts-an amount lower than any abortion cost in 2020. Lifting Hyde restrictions and requiring public and private health insurance to cover this essential, time-sensitive health service without copays or deductibles would greatly reduce the financial burden of abortion.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".