Primary Care Appointment Availability for Medicaid Patients
Bibliographic record
Abstract
BACKGROUND: Arkansas and Iowa received waivers from the federal government in 2014 to use federal Medicaid expansion funding to enroll beneficiaries in commercial insurance plans on the Marketplaces. One key hypothesis of these "private option" or "premium assistance" programs was that Medicaid beneficiaries would experience increased access to care. In this study, we compare new patient primary care appointment availability and wait-times for beneficiaries of traditional Medicaid and premium assistance Medicaid. METHODS: Trained field staff posing as patients, randomized to traditional Medicaid or Marketplace plans, called primary care practices seeking new patient appointments in Arkansas and Iowa in May to July 2014. All calls were made to offices that previously indicated being in-network for the plan. Offices were drawn randomly, within insurance type, based on the county proportion of the population with each insurance type. We calculated appointment rates and wait-times for new patients for traditional Medicaid and Marketplace plans. RESULTS: In Arkansas, Marketplace appointment rates were 27.2 percentage points higher than traditional Medicaid appointment rates (83.2% compared with 55.5%, P<0.001), while in Iowa, Marketplace appointment rates were 12.0 percentage points higher (86.3% compared with 74.3%, P<0.001). Conditional on receiving an appointment, median wait-times were roughly 1 week in each state without significant differences by insurance type. CONCLUSIONS: The experiences of Arkansas and Iowa suggest that enrolling Medicaid beneficiaries into Marketplace plans may lead to higher primary care appointment availability for new patients at participating providers. Further research is needed on whether premium assistance programs affect quality and continuity of care, and at what cost.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".