Opioid Education and Prescribing Practices
Bibliographic record
Abstract
BACKGROUND: Lack of training among health care providers (HCPs) to safely prescribe opioids is a contributing factor to the opioid crisis. Training and other resources have been developed to educate providers about safe and appropriate opioid prescribing practices. METHOD: The national survey was conducted with 2000 HCPs representing primary care physicians (PCPs), including family practice, general practice, and internal medicine; specialists (SPs); physician assistants (PAs); and nurse practitioners (NPs), a mix of primary care and specialists. This survey examined exposure to opioid educational information and opioid prescribing. RESULTS: PCPs reported prescribing opioids for chronic pain to significantly more patients compared with other HCP groups. PCPs (89.8%) and NPs (85.5%) reported significantly greater exposure to opioid educational information compared with both SPs (71.9%) and PAs (78.8%). Overall, HCPs had limited knowledge about abuse-deterrent formulations, but PCPs had greater knowledge than other groups. HCPs had an increased likelihood of prescribing opioids to fewer patients in the last 3 months relative to the prior 12 months if they worked in a state or county clinic vs a solo or group practice type (adjusted odds ratio [AOR] = 1.97; 95% confidence interval [CI], 1.12-3.49) and were exposed to more opioid educational information during the last 12 months (AOR = 1.19; 95% CI, 1.06-1.32). DISCUSSION: HCPs' exposure to opioid educational information was associated with less opioid prescribing for chronic pain. Findings indicated a difference in exposure and knowledge gaps across provider groups. More information is needed on the content of opioid educational information provided to HCPs.
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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 | 0.001 | 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 | 0.001 |
| 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".