eHealth Activity

Our R&D priorities in this area are focusing around the issues related to the creation of an integrated electronic health record (I-EHR) for every citizen, by addressing key challenges related to the provision of a framework for the integration of a diverse set of heterogeneous and distributed information sources into what appears to be a uniform collection of data and knowledge, so as to increase the availability of previously inaccessible information. We are also focusing on the requirement of transforming such an I-EHR from a passive into an active record, so as to support a patient-centered, clinically driven healthcare system. Towards this end Computational Medicine Laboratory is focusing on issues related to (a) linking the I-EHR to external knowledge sources such as clinical guidelines/protocols and genetic information; and (b) the development of predictive models for diseases/treatments. The objective being to improve medical knowledge through the elicitation of currently unknown correlations ("non-hypothesis based medicine") between an individuals' clinical history and the risk of developing new pathologies and between medical treatments and unwanted side effects. Additional R&D efforts are related to the important requirement for significantly improving the care delivery processes through coordination of multiple human and other resources that are spread over multiple organisations in an enterprise as well as across multiple enterprises. To this end, Computational Medicine Laboratory's R&D efforts focus on the development of new, innovative ambient intelligence service platforms for automatic, context sensitive offering and contracting of eHealth and mobile Health (mHealth) services across heterogeneous networks.

eHealth Activity Leader: Dr. Manolis Tsiknakis