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Introduction: Today, modern technology is used to diagnose and treat cardiovascular disease. These medical devices provide exact measures and raw data such as imaging data or biosignals. So far, the Broad Integration of These Health Data into Hospital Information Technology Structures-Especially in Germany-is Lacking, and if data integration takes place, only non-Evaluable Findings are Usually Integrated into the Hospital Information Technology Structures. A Comprehensive Integration of raw Data and Structured Medical Information has not yet Been Established. The aim of this project was to design and implement an interoperable database (cardio-vascular-information-system, CVIS) for the automated integration of al medical device data (parameters and raw data) in cardio-vascular medicine. Methods: The CVIS serves as a data integration and preparation system at the interface between the various devices and the hospital IT infrastructure. In our project, we were able to establish a database with integration of proprietary device interfaces, which could be integrated into the electronic health record (EHR) with various HL7 and web interfaces. Results: In the period between 1.7.2020 and 30.6.2022, the data integrated into this database were evaluated. During this time, 114,858 patients were automatically included in the database and medical data of 50,295 of them were entered. For technical examinations, more than 4.5 million readings (an average of 28.5 per examination) and 684,696 image data and raw signals (28,935 ECG files, 655,761 structured reports, 91,113 x-ray objects, 559,648 ultrasound objects in 54 different examination types, 5,000 endoscopy objects) were integrated into the database. Over 10.2 million bidirectional HL7 messages (approximately 14,000/day) were successfully processed. 98,458 documents were transferred to the central document management system, 55,154 materials (average 7.77 per order) were recorded and stored in the database, 21,196 diagnoses and 50,353 services/OPS were recorded and transferred. On average, 3.3 examinations per patient were recorded; in addition, there are an average of 13 laboratory examinations. Discussion: Fully automated data integration from medical devices including the raw data is feasible and already creates a comprehensive database for multimodal modern analysis approaches in a short time. This is the basis for national and international projects by extracting research data using FHIR.
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BACKGROUND: The number of cardiologically relevant genetic findings will continue to increase. This is due to the use of high-throughput sequencing techniques and the critical role of incidental findings in cardiac disease genes. Telemedicine can be a useful diagnostic tool to monitor the heart rhythm of patients with inborn cardiac diseases. METHODS: Patients were screened once they had been referred to our outpatient department for rare cardiac diseases between January 2020 and May 2022. Those patients who underwent genetic testing and were consequently diagnosed with a genetic disorder were included in this study. Their medical records were evaluated regarding implanted cardiac electronic devices and findings in the telemedical monitoring. RESULTS: 304 patients were seen in our outpatient department for rare cardiac diseases in the mentioned period. In 100 cases, genetic testing was performed. 10 patients (10%) with an identified inborn cardiac disease were monitored via telemedicine until the end of May 2022. 4 patients were monitored by implantable loop recorders (ILR), 4 patients were monitored by Implantable Cardioverter Defibrillators (ICD), and 2 patients received both devices. Clinical relevant arrhythmias making medical intervention necessary were identified in 4 cases. In two cases, data interpretation was hampered by sinus tachycardia caused by physical exercise. DISCUSSION: Telemonitoring of the heart rhythm by medical devices is beneficial for patients with monogenic heart diseases. Especially, when the indication for an ICD is not clear, implantation of a telemonitored ILR can be a suitable choice. However, rhythm analysis can be challenging in young patients who are physically active.