Buprenorphine/naloxone initiation and referral as a quality improvement intervention for patients who live with opioid use disorder: quantitative evaluation of provincial spread to 107 rural and urban Alberta emergency departments
Bibliographic record
Abstract
OBJECTIVES: Opioid use disorder is a major public health concern that accounts for a high number of potential years of life lost. Buprenorphine/naloxone is a recommended treatment for opioid use disorder that can be started in the emergency department (ED). We developed an ED-based program to initiate buprenorphine/naloxone for eligible patients who live with opioid use disorder, and to provide unscheduled, next-day follow-up referrals to an opioid use disorder treatment clinic (in person or virtual) for continuing patient care throughout Alberta. METHODS: In this quality improvement initiative, we supported local ED teams to offer buprenorphine/naloxone to eligible patients presenting to the ED with suspected opioid use disorder and refer these patients for follow-up care. Process, outcome, and balancing measures were evaluated over the first 2 years of the initiative (May 15, 2018-May 15, 2020). RESULTS: The program was implemented at 107 sites across Alberta during our evaluation period. Buprenorphine/naloxone initiations in the ED increased post-intervention at most sites with baseline data available (11 of 13), and most patients (67%) continued to fill an opioid agonist prescription at 180 days post-ED visit. Of the 572 referrals recorded at clinics, 271 (47%) attended their first follow-up visit. Safety events were reported in ten initiations and were all categorized as no harm to minimal harm. CONCLUSIONS: A standardized provincial approach to initiating buprenorphine/naloxone in the ED for patients living with opioid use disorder was spread to 107 sites with dedicated program support staff and adjustment to local contexts. Similar quality improvement approaches may benefit other jurisdictions.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".