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DOI: 10.1055/a-1950-9637
Tracing the Progression of Sepsis in Critically Ill Children: Clinical Decision Support for Detection of Hematologic Dysfunction
Funding This work is fully funded by the Federal Ministry of Health; Grant No. 2520DAT66A. This work was also partly supported by the Lower Saxony “Vorab” of the Volkswagen Foundation and assisted by the Center for Digital Innovations (ZDIN) as well as the Ministry for Science and Culture of Lower Saxony; Grant No. ZN3491.![](https://www.thieme-connect.de/media/10.1055-s-00035026/202205/lookinside/thumbnails/10-1055-a-1950-9637_202203ra0079-1.jpg)
Abstract
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.
Keywords
decision support systems, clinical - hematology - openEHR - organ failure - intensive care units, pediatric - diagnostic accuracyStatement of Ethics
All study participants, their parents, or legal guardians gave written informed consent. The study has been approved by the Ethics Committee of Hannover Medical School (No. 7804_BO_S_2018 and No. 9819_BO_S_2021). The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects, and was reviewed by the Ethics Committee of Hannover Medical School.
Author Contributions
All authors including the study group members contributed to the manuscript according to the ICMJE (International Committee of Medical Journal Editors) recommendations and were involved in data, knowledge, and rule acquisition as well as manuscript reviewing. L.B. was responsible for organizing the drafting process and manuscript writing, developing the OD rules, and outlining the manuscript. A.W. was responsible for the design and implementation of the interoperable CDSS approach, enhancement of the database, and support of knowledge acquisition and rule development. S.S. and T.J. provided clinical expertise and data, independently evaluated the patients to define ground truth decisions and to discuss evaluation results, and co-drafted the manuscript. J.B. was responsible for conducting the statistical analysis and PoC evaluation and drafting the corresponding method and result sections. The ELISE study group includes all researchers participating in the ELISE project discussions of data models, data extraction and integration, CDSS design, rules, and evaluation. O.J.B. supervised the work, critically revised the manuscript, and gave further methodological advice. M.M. critically revised the manuscript. All authors approved the final manuscript version.
* : ELISE study group members can be found in [Supplementary] Appendix A (available in the online version)
Publication History
Received: 08 April 2022
Accepted: 06 July 2022
Accepted Manuscript online:
26 September 2022
Article published online:
26 October 2022
© 2022. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)
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