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Title
Development of an interoperable exchange, aggregation and analysis platform for health and environmental data / von Mhd Adnan Jouned
AuthorJouned, Mhd Adnan
CensorKaniusas, Eugenijus
Thesis advisorThürk, Florian
PublishedWien, 2018
Description81 Blätter : Illustrationen, Diagramme
Institutional NoteTechnische Universität Wien, Diplomarbeit, 2018
Annotation
Zusammenfassung in deutscher Sprache
LanguageEnglish
Document typeThesis (Diplom)
Keywords (DE)Interoperabilität / HL7 / Telemedizin
Keywords (EN)Interoperability / HL7 / telemedicine
URNurn:nbn:at:at-ubtuw:1-108719 Persistent Identifier (URN)
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 The work is publicly available
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Development of an interoperable exchange, aggregation and analysis platform for health and environmental data [4.74 mb]
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Abstract (English)

The continuous growth in hospitalization-related healthcare costs has been a strong incentive for the spread of telemedicine systems, which contributes to cost savings and reduces the risk of patient re-hospitalization. Although there are many systems currently in place in the field of telemedicine, most of them lack the ability to operate and connect with other systems to exchange information, which results in turn in a cost burden and an increase in the rate of medical errors. Health interoperability provides a solid ground for proper exchange and understanding of information between different systems including telemedicine. Several studies have been conducted on healthcare information systems based on different Health interoperability standards, but few of them are looking for the latest standard “Fast Healthcare Interoperability Resources” FHIR which has been developed by Health Level seven HL7. On the other hand, current studies on telemedicine systems focus either on the application of the standard itself or on the design and implementation of telemedicine without paying attention to health interoperability. In this work, we provide a wide overview of a HL7 FHIR based telemedicine system, which transmits data from health monitoring devices via smartphone to the central aggregation server. This work covers theoretical aspects on how to design the healthcare information system components that support interoperability with its structural, semantic and syntactic levels. To reflect the theoretical study into practical telemedicine system, this work provides a detailed view of healthcare data acquisition and transmission from health monitoring device via Bluetooth Low Energy (BLE) to a smartphone, highlighting the role of BLE healthcare profiles. Further, the conversion of these acquired data into HL7 FHIR protocol, and the possible integration of semantic standard into FHIR to make data ready to be transmitted to the server are covered. To exchange data from the server point of view, the work also explains the process of building a programming application interface to receive information and pass it to database management systems. In addition to describe the inter-relationship between the programming environments and the protocols used in the implementation like FHIR, Bluetooth GATT profiles, and SSL, and provide a view of healthcare data flow in the parts of the system. The practical part has succeeded in providing smartphone applications and server software that enables developed telemedicine system to acquire blood pressure signs and heart rate from health monitoring devices. These can be send it via BLE to a smartphone and then to the central server according to health interoperability standards. The data on the server will become part of a healthcare information management system and will be accessible and transferable by other systems using the HL7 FHIR Interoperability standard. This thesis is part of the "Interoperable Exchange, Aggregation and Analysis Platform for Health and Environmental Data" project which aims to provide a platform for the integration of healthcare data with Big-data to perform analytical processing, that has the potential to deliver smart and efficient health care and reveal hidden correlation patterns which can contribute to earlier and more accurate diseases diagnosis, which in some cases could perform better than human specialists.

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