Conceptual Framework for Semantic Interoperability in Sensor-enhanced Health Information Systems (SIOp4Se-HIS)

Ajigboye, Olamidipupo Solomon (2018) Conceptual Framework for Semantic Interoperability in Sensor-enhanced Health Information Systems (SIOp4Se-HIS). (PhD thesis), Kingston University, .


Transducer integration into different accessories such as eyeglasses, wristbands, vest, wristwatches, among others, has brought myriads of physiological data that could be of help in making patients health monitoring easier. However, this myriad of data are generated from different devices with different formats and uncoordinated data types which ultimately compromises the data integrity and renders it medically less importance. Furthermore, several wearables do operate as data island as they cannot incorporate their captured data into the Health Information Systems (HIS) for easy accessibility by the health-care professionals for further processing, interpretation and actions on the patients’ health. Therefore, to enable the flow of data that will be useful to both patient and health-care professional, the existing HIS should be transducer enhanced / enabled, and they should operate at the same semantic interoperability level to allow for exchange of meaningful data from transducers to HIS. In bid to achieve this, several attempts have been made using standards, and archetypes, which goes a long way in providing interoperability at the technical and syntactic level. However, repositories of heterogeneous transducer data as provided by health monitoring systems, requires actionable knowledge of context (environment) from which the data is collected for it to be medically useful and interoperate at the semantic level with the HIS. There are three approaches: the model-driven; standard based and archetype approach but only the ontology driven guarantees making the applications smarter, or make the data smarter. The study propose the latter option using a dual model approach to leverage semantic technologies in order to provide and apply more meaningful health monitoring data representation between transducers and HIS. We approached this study using the design science research methodology and developed a hybrid methodology by combining two methods to develop our ontologies that are based on standards in the domains, with this unique method we achieved a novel approach to solve the obstacle of semantic interoperability through our proposed framework for Semantic Interoperability for Sensor-enhanced Health Information Systems (se-HIS) and bridged the gaps in systems’ interoperability between monitoring units and HIS. The outcome is a robust, explicit conceptual framework for sensor-enhanced health information systems Interoperability (IOp) at the semantic level. This semantically enabled our HIS, to interoperate with Transducers that are compliant with the Institute of Electrical and Electronics Engineers (IEEE) 21451 family of standards, and it provides the ability to query high-level knowledge of the data context as well as low-level raw data accessibility in a multi-transducer enable HIS.

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