CrowdHEALTH: Holistic Health Records and Big Data Analytics for Health Policy Making and Personalized Health
Dimosthenis Kyriazis, Serge Autexier, Iván Brondino, Michael Boniface, Lucas Donat, Vegard Engen, Rafael Fernandez, Ricardo Jimenez-Peris, Blanca Jordan, Gregor Jurak, Athanasios Kiourtis, Thanos Kosmidis, Mitja Lustrek, Ilias Maglogiannis, John Mantas, Antonio Martinez, Argyro Mavrogiorgou, Andreas Menychtas, Lydia Montandon, Cosmin-Septimiu Nechifor, Sokratis Nifakos, Alexandra Papageorgiou, Marta Patino-Martinez, Manuel Perez, Vassilis Plagianakos, Dalibor Stanimirovic, Gregor Starc, Tanja Tomson, Francesco Torelli, Vicente Traver-Salcedo, George Vassilacopoulos, Usman Wajid
Today's rich digital information environment is characterized by the multitude of data sources providing information that has not yet reached its full potential in eHealth. The aim of the presented approach, namely CrowdHEALTH, is to introduce a new paradigm of Holistic Health Records (HHRs) that include all health determinants. HHRs are transformed into HHRs clusters capturing the clinical, social and human context of population segments and as a result collective knowledge for different factors. The proposed approach also seamlessly integrates big data technologies across the complete data path, providing of Data as a Service (DaaS) to the health ecosystem stakeholders, as well as to policy makers towards a “health in all policies” approach. Cross-domain co-creation of policies is feasible through a rich toolkit, being provided on top of the DaaS, incorporating mechanisms for causal and risk analysis, and for the compilation of predictions.
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