Most Marketplace Plans Included At Least 25 Percent Of Local-Area Physicians, But Enrollment Disparities Remained
Bibliographic record
Abstract
The Affordable Care Act allows commercial insurers participating in the Marketplaces to vary the size of their provider networks as long as the providers are "sufficient" in numbers and types. Concerns have been growing over the increasing use of restricted-provider or narrow networks in Marketplace plans because of their implications for reduced access to care, but little is known about the breadth and stability of these networks over time or what types of enrollees choose such plans. Using national data, we found that in 2016, 60 percent of provider networks in plans offered in the federally facilitated Marketplaces included at least one-quarter of local-area physicians, and that consumers' access to broad-network plans remained stable between 2015 and 2016. Hispanic and low-income people made up a disproportionate share of enrollees in smaller-network plans (those with fewer than one-quarter of local-area physicians). It will be important to monitor the impact of narrow networks on access to and quality of care as well as on health outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".