PED-IA, a CDSS to support decision in pediatrics telephone triage: a crossover evaluation

Abstract

Background

Pediatric emergency departments face overcrowding, often driven by non-urgent consultations. Telephone triage, supported by clinical decision support systems (CDSSs), offers a potential solution to improve decision accuracy and reduce unnecessary visits. However, pediatric-specific CDSSs are scarce and underexplored.

Objective

This study aimed to evaluate the impact of a pediatric-specific CDSS, PED-IA, on decision-making accuracy, confidence, and response time.

Methods

PED-IA is an ontology-based CDSS featuring a rule-driven inference engine and a dynamic interface that guides practitioners through structured clinical reasoning. A crossover study was conducted with 51 practitioners who had to answer clinical cases with and without the CDSS. Decision accuracy, confidence, and response times were measured, and satisfaction was assessed through questionnaires.

Results

The CDSS significantly improved decision accuracy from 52.9 % to 76.0 % (+23.1 %, p < 0.01) and increased confidence levels by 0.65 points on a 10-point scale (p < 0.01). Residents benefited the most, with an improved accuracy (odds ratio of 3.70 [2.15, 6.36]). Response times increased by an average of 261.8 s per case (p < 0.01). Practitioners expressed high satisfaction, with 88.2 % finding the system useful for decision-making and 84.3 % believing it could reduce stress in clinical practice.

Conclusion

The PED-IA CDSS significantly enhances triage decision accuracy and user confidence, making it a promising system for clinical practice and medical education. Practitioners viewed the system positively and identified its long-term time-saving potential. Future works should focus on refining system ergonomics and exploring hybrid models that combine data-driven and logic-based approaches to improve usability and adaptability.