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Tracing the Progression of Sepsis in Critically Ill Children: Clinical Decision Support for Detection of Hematologic
Louisa Bode1, Sven Schamer2, Julia Böhnke3
1Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Hannover, Germany.
Insights
This study developed an enhanced clinical decision support system (CDSS) to accurately detect hematologic organ dysfunction (OD) in critically ill children with sepsis. The system achieved high sensitivity and specificity, offering a valuable tool for pediatric intensive care.
Area of Science:
- Pediatric Intensive Care Medicine
- Clinical Informatics
- Artificial Intelligence in Healthcare
Background:
- Detecting pediatric organ dysfunction (OD) in critical care is challenging due to time constraints and data complexity.
- Computerized decision support systems (CDSS) can aid clinicians, but their application in pediatric OD detection is underexplored.
Purpose of the Study:
- To enhance an existing interoperable CDSS for tracking pediatric sepsis progression.
- To augment the CDSS with the capability to detect Systemic Inflammatory Response Syndrome/sepsis-associated hematologic OD.
- To determine the diagnostic accuracy of this enhanced CDSS for hematologic OD.
Main Methods:
- Reproduced an interoperable CDSS using commonKADS for knowledge modeling.
- Standardized and harmonized clinical data with openEHR.
- Developed and implemented a rule-based CDSS in a business rule management system.
- Estimated diagnostic accuracy using data from 168 patients.
Main Results:
- Successfully enhanced an interoperable CDSS to detect pediatric SIRS/sepsis-associated hematologic OD.
- Achieved a sensitivity of 0.821 (95% CI: 0.708-0.904) and specificity of 0.970 (95% CI: 0.942-0.987).
Conclusions:
- The developed interoperable CDSS approach is reproducible and transferable to other critical conditions.
- Presents one of the first interoperable CDSS modules for detecting pediatric SIRS/sepsis-associated hematologic OD.
- Offers direct practical relevance for improving care in pediatric intensive care units.
Background:
One of the major challenges in pediatric intensive care is the detection of life-threatening health conditions under acute time constraints and performance pressure. This includes the assessment of pediatric organ dysfunction (OD) that demands extraordinary clinical expertise and the clinician's ability to derive a decision based on multiple information and data sources. Clinical decision support systems (CDSS) offer a solution to support medical staff in stressful routine work. Simultaneously, detection of OD by using computerized decision support approaches has been scarcely investigated, especially not in pediatrics.
Objectives:
The aim of the study is to enhance an existing, interoperable, and rule-based CDSS prototype for tracing the progression of sepsis in critically ill children by augmenting it with the capability to detect SIRS/sepsis-associated hematologic OD, and to determine its diagnostic accuracy.
Methods:
We reproduced an interoperable CDSS approach previously introduced by our working group: (1) a knowledge model was designed by following the commonKADS methodology, (2) routine care data was semantically standardized and harmonized using openEHR as clinical information standard, (3) rules were formulated and implemented in a business rule management system. Data from a prospective diagnostic study, including 168 patients, was used to estimate the diagnostic accuracy of the rule-based CDSS using the clinicians' diagnoses as reference.
Results:
We successfully enhanced an existing interoperable CDSS concept with the new task of detecting SIRS/sepsis-associated hematologic OD. We modeled openEHR templates, integrated and standardized routine data, developed a rule-based, interoperable model, and demonstrated its accuracy. The CDSS detected hematologic OD with a sensitivity of 0.821 (95% CI: 0.708-0.904) and a specificity of 0.970 (95% CI: 0.942-0.987).
Conclusion:
We could confirm our approach for designing an interoperable CDSS as reproducible and transferable to other critical diseases. Our findings are of direct practical relevance, as they present one of the first interoperable CDSS modules that detect pediatric SIRS/sepsis-associated hematologic OD.
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