Impact of a Graduated Approach on Opioid Initiation and Loss of Earnings Following Workplace Injury
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to explore the impact of the Ontario Workplace Safety and Insurance Board's (WSIB's) graduated approach to opioid management on opioid prescribing and disability claim duration. METHODS: We studied patterns of opioid use and disability claim duration among Ontarians who received benefits through the WSIB between 2002 and 2013. We used interventional time series analysis to assess the impact of the WSIB graduated formulary on these trends. RESULTS: After the introduction of the graduated formulary, initiation of short- and long-acting opioids fell significantly (P < 0.0001). We also observed a shift toward the use of short-acting opioids alone (P < 0.0001). Although disability claim duration declined, this could not be ascribed to the intervention (P = 0.18). CONCLUSION: A graduated opioid formulary may be an effective tool for providers to promote more appropriate opioid prescribing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".