Changes in early high‐risk opioid prescribing practices after policy interventions in Washington State
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To test associations between several opioid prescribing policy interventions and changes in early (acute/subacute) high-risk opioid prescribing practices. DATA SOURCES: Population-based workers' compensation pharmacy billing and claims data, Washington State Department of Labor and Industries (January 2008-June 2015). STUDY DESIGN: We used interrupted time series analysis to test associations between three policy intervention timepoints and monthly proportions of population-based measures of high-risk, low-risk, and any workers' compensation-related opioid prescribing. We also tested associations between the policy intervention timepoints and five high-risk opioid prescribing indicators among workers prescribed any opioids within 3 months after injury: (a) >7 cumulative (not necessarily consecutive) days' supply of opioids during the acute phase, (b) high-dose opioids, (c) concurrent sedatives, (d) chronic opioids, and (e) a composite high-risk opioid prescribing indicator. PRINCIPAL FINDINGS: Within 3 months after injury, 9 percent of workers were exposed to high-risk and 12 percent to low-risk workers' compensation-related opioid prescribing; 79 percent filled no workers' compensation-related opioid prescription. Among workers prescribed any early (acute/subacute) opioids, the indicator for >7 days' supply of opioids during the acute phase was present for 30 percent, high-dose opioids for 18 percent, concurrent sedatives for 3 percent, and chronic opioids for 2 percent. Beyond a general shift toward more infrequent and lower-risk workers' compensation-related opioid prescribing, each policy intervention timepoint was significantly associated with reductions in specific acute/subacute high-risk opioid prescribing indicators; each of the four specific high-risk opioid prescribing indicators had significant reductions associated with at least one policy. CONCLUSIONS: Several state-level opioid prescribing policies were significantly associated with safer workers' compensation-related opioid prescribing practices during the first 3 months after injury (acute/subacute phase), which should in turn reduce transition to chronic opioids and associated negative health outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it