State Mandates On Naloxone Coprescribing Associated With Short-Term Increase In Naloxone Codispensing
Bibliographic record
Abstract
In the midst of the opioid crisis in the US, efforts to mitigate overdose risks have become paramount, leading some states to introduce mandates for coprescribing the life-saving overdose reversal drug naloxone. These mandates were designed to specifically address people receiving opioid analgesics who had an elevated risk for overdose. This included people receiving high opioid dosages, those concurrently using benzodiazepines, or those with a history of substance use disorder or overdose. Using a nationally representative, multipayer cohort of patients receiving prescription opioids, we investigated how naloxone codispensing rates changed at the state level from 2016 to 2021 among patients with an elevated risk for overdose. Then we used controlled interrupted time series analyses to assess mandates' longitudinal impact on naloxone codispensing in ten states that implemented mandates. We observed an immediate and significant increase in the naloxone codispensing rates in eight states after the implementation of mandates. Nevertheless, in five of these states, the codispensing rates exhibited a subsequent downward trend after the initial increase. State mandates show potential for improving naloxone codispensing; however, mandates alone might not be adequate for sustained change. Further research is needed to identify strategies complementing and enhancing the impact of mandates in combating the overdose crisis.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".