Medicaid Patients With ED Visits For Overdose: Disparities In Initiation Of Medications For Opioid Use Disorder
Bibliographic record
Abstract
Medications for opioid use disorder (MOUD) after emergency department (ED) visits for overdose can reduce subsequent overdose deaths, but disparities in receiving MOUD persist in the US. Using national Medicaid claims data from the period 2016-20, we examined racial and ethnic disparities in MOUD initiation after ED visits for opioid overdose. Overall, 6.4 percent of Medicaid ED visits were associated with a claim for MOUD within thirty days. This rate was highest among non-Hispanic White (7.3 percent) patients and lowest among non-Hispanic Black (4.3 percent) and Hispanic (4.9 percent) patients. The adjusted rate of MOUD initiation was 2.5 percentage points lower among Black patients compared with White patients, and this disparity increased nearly twofold between 2016 and 2020. Although policy and clinical efforts to increase MOUD use in the Medicaid population are important, findings suggest that efforts targeting patients from racial and ethnic minority groups may be warranted.
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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 | 0.000 |
| 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) | 0.000 | 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".