An Interoperable System toward Cardiac Risk Stratification from ECG Monitoring

Cristina Soguero-Ruiz, Inmaculada Mora-Jiménez, Javier Ramos-López, Teresa Quintanilla Fernández, Antonio García-García, Daniel Díez-Mazuela, Arcadi García-Alberola and José Luis Rojo-Álvarez
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Cristina Soguero-Ruiz: Department of Signal Theory and Communications and Telematics Systems and Computing, Rey Juan Carlos University, 28942 Madrid, Spain
Inmaculada Mora-Jiménez: Department of Signal Theory and Communications and Telematics Systems and Computing, Rey Juan Carlos University, 28942 Madrid, Spain
Javier Ramos-López: Department of Signal Theory and Communications and Telematics Systems and Computing, Rey Juan Carlos University, 28942 Madrid, Spain
Teresa Quintanilla Fernández: Department of Signal Theory and Communications, Carlos III University, 28912 Madrid, Spain
Antonio García-García: Niño Jesús Hospital, 28009 Madrid, Spain
Daniel Díez-Mazuela: Doce de Octubre Hospital, 28041 Madrid, Spain
Arcadi García-Alberola: Unit of Arrhythmias, University Hospital Virgen de la Arrixaca, 30120 Murcia, Spain
José Luis Rojo-Álvarez: Department of Signal Theory and Communications and Telematics Systems and Computing, Rey Juan Carlos University, 28942 Madrid, Spain

IJERPH, 2018, vol. 15, issue 3, 1-16

Abstract: Many indices have been proposed for cardiovascular risk stratification from electrocardiogram signal processing, still with limited use in clinical practice. We created a system integrating the clinical definition of cardiac risk subdomains from ECGs and the use of diverse signal processing techniques. Three subdomains were defined from the joint analysis of the technical and clinical viewpoints. One subdomain was devoted to demographic and clinical data. The other two subdomains were intended to obtain widely defined risk indices from ECG monitoring: a simple-domain (heart rate turbulence (HRT)), and a complex-domain (heart rate variability (HRV)). Data provided by the three subdomains allowed for the generation of alerts with different intensity and nature, as well as for the grouping and scrutinization of patients according to the established processing and risk-thresholding criteria. The implemented system was tested by connecting data from real-world in-hospital electronic health records and ECG monitoring by considering standards for syntactic (HL7 messages) and semantic interoperability (archetypes based on CEN/ISO EN13606 and SNOMED-CT). The system was able to provide risk indices and to generate alerts in the health records to support decision-making. Overall, the system allows for the agile interaction of research and clinical practice in the Holter-ECG-based cardiac risk domain.

Keywords: electronic health records; archetypes; semantic interoperability; heart rate turbulence; heart rate variability; cardiovascular risk stratification; web system (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2018
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