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Smart hospital: achieving interoperability and raw data collection from medical devices in clinical routine.
Martens, Eimo; Haase, Hans-Ulrich; Mastella, Giulio; Henkel, Andreas; Spinner, Christoph; Hahn, Franziska; Zou, Congyu; Fava Sanches, Augusto; Allescher, Julia; Heid, Daniel; Strauss, Elena; Maier, Melanie-Maria; Lachmann, Mark; Schmidt, Georg; Westphal, Dominik; Haufe, Tobias; Federle, David; Rueckert, Daniel; Boeker, Martin; Becker, Matthias; Laugwitz, Karl-Ludwig; Steger, Alexander; Müller, Alexander.
Afiliação
  • Martens E; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Internal Medicine I, University Medical Center, Technical University of Munich, Munich, Germany.
  • Haase HU; European Reference Network Guard Heart, European Union, Amsterdam, Netherlands.
  • Mastella G; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Internal Medicine I, University Medical Center, Technical University of Munich, Munich, Germany.
  • Henkel A; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Internal Medicine I, University Medical Center, Technical University of Munich, Munich, Germany.
  • Spinner C; TUM School of Medicine and Health, Department of Clinical Medicine-Department of Information Technology, University Medical Center, Technical University of Munich, Munich, Germany.
  • Hahn F; IHE Deutschland e.V, Berlin, Germany.
  • Zou C; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Internal Medicine II, University Medical Center, Technical University of Munich, Munich, Germany.
  • Fava Sanches A; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Internal Medicine I, University Medical Center, Technical University of Munich, Munich, Germany.
  • Allescher J; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Internal Medicine I, University Medical Center, Technical University of Munich, Munich, Germany.
  • Heid D; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Internal Medicine I, University Medical Center, Technical University of Munich, Munich, Germany.
  • Strauss E; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Internal Medicine I, University Medical Center, Technical University of Munich, Munich, Germany.
  • Maier MM; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Internal Medicine I, University Medical Center, Technical University of Munich, Munich, Germany.
  • Lachmann M; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Internal Medicine I, University Medical Center, Technical University of Munich, Munich, Germany.
  • Schmidt G; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Internal Medicine I, University Medical Center, Technical University of Munich, Munich, Germany.
  • Westphal D; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Internal Medicine I, University Medical Center, Technical University of Munich, Munich, Germany.
  • Haufe T; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Internal Medicine I, University Medical Center, Technical University of Munich, Munich, Germany.
  • Federle D; Working Group of Medical Ethics Committees in the Federal Republic of Germany e.V., Berlin, Germany.
  • Rueckert D; TUM School of Medicine and Health, Department of Clinical Medicine-Ethics Committee, University Medical Center, Technical University of Munich, Munich, Germany.
  • Boeker M; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Internal Medicine I, University Medical Center, Technical University of Munich, Munich, Germany.
  • Becker M; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Human Genetics, University Medical Center, Technical University of Munich, Munich, Germany.
  • Laugwitz KL; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Internal Medicine I, University Medical Center, Technical University of Munich, Munich, Germany.
  • Steger A; TUM School of Medicine and Health, Department of Clinical Medicine-Clinical Department for Internal Medicine I, University Medical Center, Technical University of Munich, Munich, Germany.
  • Müller A; TUM School of Medicine and Health, Center for Digital Health & Technology-Institute for Artificial Intelligence and Informatics in Medicine, University Medical Center, Technical University of Munich, Munich, Germany.
Front Digit Health ; 6: 1341475, 2024.
Article em En | MEDLINE | ID: mdl-38510279
ABSTRACT

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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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article