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

Aurélia Manns; Alix Millet; Fleur Mougin; Florence Campeotto; Benoît Vivien; Laurent Dupic; Anita Burgun; Jean-Philippe Jais; Rosy Tsopra

doi:10.1016/j.compbiomed.2025.110645

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

Comput Biol Med. 2025 Sep:195:110645. doi: 10.1016/j.compbiomed.2025.110645. Epub 2025 Jun 20.

Authors

Aurélia Manns¹, Alix Millet², Fleur Mougin³, Florence Campeotto⁴, Benoît Vivien⁵, Laurent Dupic⁶, Anita Burgun⁷, Jean-Philippe Jais⁸, Rosy Tsopra²

Affiliations

¹ Department of Medical Informatics, Hôpital Européen Georges Pompidou, Hôpital Necker Enfants Malades, AP-HP, Paris, France; Université Paris Cité, INSERM UMR1163, Imagine Institute, Clinical Bioinformatics Laboratory, Paris, F-75006, France; Université Paris Cité, UPPERS, US 007 F-75006, Paris, France. Electronic address: aurelia.manns@gmail.com.
² Department of Medical Informatics, Hôpital Européen Georges Pompidou, Hôpital Necker Enfants Malades, AP-HP, Paris, France; Université Paris Cité, INSERM UMR1163, Imagine Institute, Clinical Bioinformatics Laboratory, Paris, F-75006, France; Université Paris Cité, UPPERS, US 007 F-75006, Paris, France.
³ Université de Bordeaux, Inserm, U1219 BPH AHeaD Team, Bordeaux, France.
⁴ Digital Health Program of Université de Paris Cité, Paris, France; Régulation Régionale Pédiatrique, SAMU de Paris, Hôpital Necker Enfants Malades, AP-HP Paris, France.
⁵ Régulation Régionale Pédiatrique, SAMU de Paris, Hôpital Necker Enfants Malades, AP-HP Paris, France.
⁶ Régulation Régionale Pédiatrique, SAMU de Paris, Hôpital Robert Debré, AP-HP Paris, France.
⁷ Department of Medical Informatics, Hôpital Européen Georges Pompidou, Hôpital Necker Enfants Malades, AP-HP, Paris, France; Université Paris Cité, INSERM UMR1163, Imagine Institute, Clinical Bioinformatics Laboratory, Paris, F-75006, France.
⁸ Imagine Institute, Université Paris Cité, Paris, France; Biostatistic Unit, Necker University Hospital, AP-HP, Paris, France.

PMID: 40543269
DOI: 10.1016/j.compbiomed.2025.110645

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.

Keywords: Artificial intelligence; Clinical; Decision support systems; Digital health; Emergency care; Prehospital; Triage.

MeSH terms

Adult
Child
Cross-Over Studies
Decision Support Systems, Clinical*
Emergency Service, Hospital
Female
Humans
Male
Pediatrics*
Surveys and Questionnaires
Telephone*
Triage* / methods