Identifying Barriers to Buprenorphine Treatment for Patients with Opioid Use Disorder Among Anesthesiologists and Pain Practitioners: A Survey Study
Bibliographic record
Abstract
OBJECTIVE: The aim of the study is to investigate barriers to opioid use disorder (OUD) care among acute and chronic pain physicians and advanced practice providers, including hypothesized barriers of lack of interest in OUD care and stigma toward this patient population. METHODS: The study used an anonymous 16-item online survey through Google Forms. Respondents were 153 health practitioners across the United States and Canada, all of whom are registered in one of several pain or anesthesia professional societies. Data were analyzed with descriptive and categorical statistics. RESULTS: The most common barriers include "lack of appropriate clinical environment for prescribing by both acute and chronic pain practitioners" (48%) and "lack of administrative/departmental support" (46%). A total of 32% of respondents reported that OUD care was important but they were not interested in doing more, while 28% of practitioners believed that they treat patients with OUD differently than others in a negative way. More males reported "difficulty" in treating OUD as a barrier (45% vs 25%). Chronic pain practitioners reported poor payor mix as a barrier twice as often as their acute pain colleagues. In free response, lack of multidisciplinary OUD care was a notable barrier. CONCLUSIONS: The top barriers to OUD treatment were clinical environment, departmental support, difficulty in treating the condition, and payor mix, supporting the hypotheses. Given an OUD patient scenario, 55% of acute pain physicians and 73% of chronic pain physicians expressed a willingness to prescribe buprenorphine.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".