Development and feasibility testing of the Pediatric Emergency Discharge Interaction Coding Scheme
Bibliographic record
Abstract
BACKGROUND: Discharge communication is an important aspect of high-quality emergency care. This study addresses the gap in knowledge on how to describe discharge communication in a paediatric emergency department (ED). OBJECTIVE: The objective of this feasibility study was to develop and test a coding scheme to characterize discharge communication between health-care providers (HCPs) and caregivers who visit the ED with their children. DESIGN: The Pediatric Emergency Discharge Interaction Coding Scheme (PEDICS) and coding manual were developed following a review of the literature and an iterative refinement process involving HCP observations, inter-rater assessments and team consensus. SETTING AND PARTICIPANTS: The coding scheme was pilot-tested through observations of HCPs across a range of shifts in one urban paediatric ED. MAIN VARIABLES STUDIED: Overall, 329 patient observations were carried out across 50 observational shifts. Inter-rater reliability was evaluated in 16% of the observations. The final version of the PEDICS contained 41 communication elements. RESULTS: Kappa scores were greater than .60 for the majority of communication elements. The most frequently observed communication elements were under the Introduction node and the least frequently observed were under the Social Concerns node. HCPs initiated the majority of the communication. CONCLUSION: Pediatric Emergency Discharge Interaction Coding Scheme addresses an important gap in the discharge communication literature. The tool is useful for mapping patterns of discharge communication between HCPs and caregivers. Results from our pilot test identified deficits in specific areas of discharge communication that could impact adherence to discharge instructions. The PEDICS would benefit from further testing with a different sample of HCPs.
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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 | 0.120 | 0.204 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".