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Towards a decision support system for pediatric emergency telephone triage
Aurélia Manns1, Alix Millet1, Florence Campeotto2
1Department of Medical Informatics, Hôpital Européen Georges Pompidou, Hôpital Necker Enfants Malades, APHP, Paris, France; Université Paris Cité, INSERM UMR1163, Imagine Institute, Clinical Bioinformatics Laboratory, Paris F-75006, France.
International Journal of Medical Informatics
|June 20, 2025
Summary
A new clinical decision support system (CDSS) was developed for pediatric telephone triage, achieving 77.1% accuracy. This tool aims to improve emergency department admissions and support healthcare professionals.
Area of Science:
- Medical Informatics
- Pediatric Emergency Medicine
- Artificial Intelligence in Healthcare
Background:
- Telephone triage is crucial for emergency department (ED) admissions but challenging in pediatrics due to nonspecific symptoms and parental reporting.
- Current clinical decision support systems (CDSSs) are not optimized for pediatric nuances, necessitating specialized tools.
- Developing a tailored CDSS for pediatric emergency telephone triage is essential to improve accuracy and quality of care.
Purpose of the Study:
- To develop and evaluate a novel CDSS specifically designed for pediatric emergency telephone triage.
- To enhance the accuracy and efficiency of triage decisions made over the phone for pediatric patients.
- To provide real-time, interpretable recommendations to healthcare professionals during pediatric triage.
Main Methods:
- Developed a three-layered CDSS featuring an ontology-oriented knowledge base (KB) with 303 concepts and 1780 axioms.
- Implemented a generic medical reasoning system mimicking clinical judgment in pediatric emergency triage.
- Assessed the CDSS performance using 96 fictitious clinical cases, comparing its recommendations against written guidelines and expert panels.
Main Results:
- The CDSS demonstrated 100% internal validity against written recommendations.
- Achieved 77.1% accuracy when compared to a panel of three pediatric emergency experts.
- Discrepancies with experts (22.9%) arose from undocumented expert information (11.5%) or differing interpretations of guidelines (10.4%).
Conclusions:
- The developed CDSS offers explainable recommendations, aiming to reduce cognitive load for healthcare professionals.
- Future work includes expanding the knowledge base and integrating data-driven approaches with the current knowledge-based system.
- Enhancing user interaction with patient-friendly language is a key area for future development.
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