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Tracing the Progression of Sepsis in Critically Ill Children: Clinical Decision Support for Detection of Hematologic Dysfunction

  • 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 rulebased 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

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Metadaten
Author:Louisa BodeORCiDGND, Sven Schamer, Julia BöhnkeORCiD, Oliver Johannes BottORCiDGND, Michael MarschollekGND, Thomas JackGND, Antje WulffGND
URN:urn:nbn:de:bsz:960-opus4-24003
DOI:https://doi.org/10.25968/opus-2400
DOI original:https://doi.org/10.1055/a-1950-9637
ISSN:1869-0327
Parent Title (English):Applied Clinical Informatics
Document Type:Article
Language:English
Year of Completion:2022
Publishing Institution:Hochschule Hannover
Release Date:2022/12/16
Tag:clinical hematology; decision support systems; intensive care units; openEHR; organ failure; pediatric diagnostic accuracy
GND Keyword:Entscheidungsunterstützungssystem; Hämatologie; Organversagen; Intensivstation; Sepsis
Volume:13
Issue:5
First Page:1002
Last Page:1014
Institutes:Fakultät III - Medien, Information und Design
DDC classes:610 Medizin, Gesundheit
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International