Association of Inadequate Provider Networks with Unmet Need for Health Services and Self-Employment among People with Disabilities
Bibliographic record
Abstract
People with disabilities (PWD) make up over a quarter of the U.S. population and often have complex medical needs. Insurance plans with narrow provider networks are growing in popularity despite concerns about limiting access to care, which may detrimentally affect PWD. This study used logistic regression to assess the relationship between inadequate networks and unmet health care needs and employment using the 2018 National Survey on Health and Disability (n= 1,009) adjusting for demographic and health factors. Having an inadequate network was associated with unmet needs (OR=5.56, 95%CI[3.33,9.28]) but not being employed for wages (OR=0.70, 95%CI[0.42,1.17]) or self-employed (OR=2.35, 95%CI[0.99,5.55]). There was an association between an inadequate network and selfemployment for those with good health (OR=3.37, 95%CI[1.19,9.57]). Providers for PWD should be aware of the role insurance quality can play in health outcomes. Policymakers should continue to monitor the impact of provider network adequacy on health outcomes.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".