Mapping the current state of pediatric surgical pain care across Canada and assessing readiness for change
Bibliographic record
Abstract
Preventing pediatric chronic postsurgical pain is a patient, parent/caregiver, health care professional, and policymaker priority. Poorly managed presurgical and acute postsurgical pain are established risk factors for pediatric chronic postsurgical pain. Effective perioperative pain management is essential to prevent the transition from acute to chronic pain after surgery. The aim of this study was to identify current pediatric surgical pain management practices and assess health system readiness for change at health care institutions conducting pediatric surgery in Canada. An online survey was completed by 85 multidisciplinary health care professionals (nurses, surgeons, anesthesiologists, allied health) from 20 health institutions in Canada regarding institutional pre- and postsurgical pediatric pain care, specialty pain services, and Organizational Readiness for Implementing Change (ORIC). Of all specialty pain services, acute and chronic/complex pain services were most common, primarily with physician and nursing involvement. Alignment to recommended practices for pediatric pre- and postsurgical pain care varied (38.1%–79.8% reported “yes, for every child”), with tertiary/quaternary children’s hospitals reporting less alignment than other institutions (community/regional or rehabilitation hospitals, community treatment centers). No significant differences were reported between health care institutions serving pediatric populations only versus those also serving adults. Health care professional experience/practice was the most reported strength in pediatric surgical pain care, with inconsistent standard of care the most common gap. Participants “somewhat agreed” that their institutions were committed and capable of change in pediatric surgical pain care. There is a continued need to improve pediatric pain care during the perioperative period at Canadian health care institutions to effectively prevent the development of pediatric postsurgical pain.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".