This paper structures empirical and practical implementation
methodologies for clinical integration of eHealth IoT smart device
technology embedded in Cloud service architecture. The results and
findings of this two-year research program are summarized from
mathematical, system architectural and software engineering perspective.
The research takes place in the European Union, in Hungary. The program
is the manifestation of the trilateral industry-university
collaboration of the University of Debrecen Faculty of Informatics,
T-Systems Healthcare Competence Center Central and Eastern Europe and
Semmelweis University 2nd Pediatric Clinic Department of Pulmonology.
The paper presents the mathematical model for the system architecture
optimization. Selected system-architectural solution plans are mapped
into directed graphs and converted into adjacency and availability
matrices for optimization. Adequate technologies are collected and
identified for the research based on industry megatrends. The experiment
establishes multidirectional interoperability among eHealth smart
devices, telemedicine instruments and clinical information systems. The
Open Telemedicine Interoperability Hub, interoperability core module,
was developed and embedded into Cloud service architecture. This module
transposes and transmits the captured bio-sensory data stream from the
eHealth IoT smart-devices and from the telemedicine instrument into the
clinical information system. Dominant international healthcare
interoperability standards are reviewed and selected for the research.
The research program defined different interoperability levels and
mapped these against the open systems interconnection model layers. The
international interoperability standard, Health Level Seven, was
selected for the research. The research explicitly tested
interoperability among eHealth consumer electronic sensor-enabled
smart-device, spirometer telemedicine instrument and cloud-based
hospital information test system. The research proved that universal
interoperability between IoT eHealth smart devices and clinical
information system technology is from technical perspective absolutely
possible. The paper describes the lessons learned, drawbacks and
achievements of this research program. An insight is also given into the
forthcoming research phase.
The paper contributes the first logical analysis for clinical
integration of the eHealth IoT technology. This study uses new
determination method for mathematically optimized healthcare service
architecture. The research originates new mathematic formula for
healthcare systems integration. The paper’s primary contribution is
validating the empirical results in real clinical environment.
Biosensor technology, eHealth, Telemedicine, Hospital information system, HL7, Internet of things.
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This study received no specific financial support.
The author declares that there are no conflicts of interests regarding the publication of this paper.