Triage Decision-Making in Interdisciplinary Pediatric Chronic Pain Programs
Bibliographic record
Abstract
BACKGROUND: Interdisciplinary pediatric chronic pain programs are ideal treatment settings for youth with chronic pain who are complex from a biopsychosocial perspective. There is currently no evidence-based clinical decision support to guide nurses triaging patients to such programs, which increases the risk for haphazard triage decisions. AIMS: To explore and describe the decision-making practices of and contextual influences on nurses triaging patients to interdisciplinary pediatric chronic pain programs. DESIGN: A qualitative exploratory descriptive design. SETTINGS: Interdisciplinary Pediatric Chronic Pain Programs. PARTICIPANTS/SUBJECTS: In all, 12 nurses across 11 different interdisciplinary pediatric chronic pain programs participated in this study. METHODS: Individual, semi-structured interviews were conducted, transcribed verbatim, and analyzed using concurrent content analysis, guided by the Cognitive Continuum Theory and the Theoretical Domains Framework. RESULTS: Findings focused on the complexity of the pediatric chronic pain population and the leading role nurses play in triage without evidence-based guidance. Analysis generated three prominent themes: (1) nurse-led triage determinants; (2) process of triage decision-making; and (3) external influences on triage decision-making. CONCLUSIONS: Triage decision making in the setting of interdisciplinary pediatric chronic pain programs is complex and often led by nurses. There is a desire amongst nurses to adopt an evidence-based clinical decision support triage tool (CDS), which may streamline the referral and triage process and foster a system whereby patients in highest need for interdisciplinary care are best prioritized.
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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 | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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".