“Just give them a choice”: Patients' perspectives on starting medications for opioid use disorder in the <scp>ED</scp>
Bibliographic record
Abstract
OBJECTIVES: Medications for opioid use disorder (MOUD) prescribed in the emergency department (ED) have the potential to save lives and help people start and maintain recovery. We sought to explore patient perspectives regarding the initiation of buprenorphine and methadone in the ED with the goal of improving interactions and fostering shared decision making (SDM) around these important treatment options. METHODS: We conducted semistructured interviews with a purposeful sample of people with opioid use disorder (OUD) regarding ED visits and their experiences with MOUD. The interview guide was based on the Ottawa Decision Support Framework, a framework for examining decisional needs and tailoring decisional support, and the research team's experience with MOUD and SDM. Interviews were recorded, transcribed, and analyzed in an iterative process using both the Ottawa Framework and a social-ecological framework. Themes were identified and organized and implications for clinical care were noted and discussed. RESULTS: Twenty-six participants were interviewed, seven in person in the ED and 19 via video conferencing software. The majority had tried both buprenorphine and methadone, and almost all had been in an ED for an issue related to opioid use. Participants reported social, pharmacological, and emotional factors that played into their decision making. Regarding buprenorphine, they noted advantages such as its efficacy and logistical ease and disadvantages such as the need to wait to start it (risk of precipitated withdrawal) and that one could not use other opioids while taking it. Additionally, participants felt that: (1) both buprenorphine and methadone should be offered; (2) because "one person's pro is another person's con," clinicians will need to understand the facets of the options; (3) clinicians will need to have these conversations without appearing judgmental; and (4) many patients may not be "ready" for MOUD, but it should still be offered. CONCLUSIONS: Although participants were supportive of offering buprenorphine in the ED, many felt that methadone should also be offered. They felt that treatment should be tailored to an individual's needs and circumstances and clarified what factors might be important considerations for people with OUD.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".