Knowledge, attitudes, and practices regarding opioid use in the pediatric emergency department
Bibliographic record
Abstract
Abstract BACKGROUND Inadequate pain management in children is ubiquitous in the emergency department (ED). Inadequate pain management in children can have both short and long term detrimental effects. As the current national opioid crisis has highlighted, physicians are caught between balancing pain management and the risk of long term opioid dependence. OBJECTIVES This study aimed to describe paediatric emergency physicians’ (PEPs) willingness to prescribe opioids to children in the ED and at discharge, perceived knowledge regarding common fears and myths about opioid use, management approach to hypothetical scenarios of varying musculoskeletal injury (MSK-I) pain in children, and perceived facilitators and barriers to prescribing opioids. DESIGN/METHODS A unique survey tool was created using published methodology guidelines. Information regarding practices, knowledge, attitudes, perceived barriers, facilitators and demographics were collected. The survey was distributed to all physician members of Pediatric Emergency Research Canada (PERC), using a modified Dillman’s Tailored Design method, from October to December 2017. RESULTS The response rate was 49.7% (124/242); 53% (57/107) were female, mean age was 43.6 years (+/- 8.7), and 58% (72/124) had paediatric emergency subspecialty training. The most common first line pain medication in the ED was ibuprofen for mild, moderate and severe MSK-I related pain (94.4% (117/124), 89.5% (111/124), and 62.9% (78/124), respectively). For moderate and severe MSK-I pain, intranasal fentanyl was the most common opioid for first (35.5% (44/124) and 61.3% (76/124), respectively) and second line pain management (41.1% (51/124) and 20.2% (25/124), respectively). 74.8% (89/119) of PEPs reported that an opioid protocol would be helpful, specifically for morphine, fentanyl, and hydromorphone. Using a 0–100 scale, physicians minimally worried about physical dependence (13.3 +/-19.3), addiction (16.6 +/-19.8), and diversion of opioids (32.8+/-26.4) when prescribing short-term opioids to children. They reported that the current opioid crisis minimally influenced their willingness to prescribe opioids (30.0 +/-26.2). Physicians reported rarely (36%; 45/125) or never (28%; 35/125) completing a screening risk assessment prior to prescribing opioids. CONCLUSION Intranasal fentanyl was the top opioid for all MSK-I pain intensities. PEPs are minimally concerned regarding dependence, addiction, and the current opioid crisis when prescribing short-term opioids to children. There is an urgent need for evidence regarding the dependence and addiction risk for children receiving short term opioids in order to create knowledge translation tools for ED physicians. Opioid specific protocols in the ED would likely improve physician comfort in responsible and adequate pain management for children.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".