Dimosthenis Kyriazis, Technical Coordinator
University Of Piraeus Research Center


The multitude of data sources in the healthcare domain highlights a unique opportunity: data to be exploited for effective and targeted policy making, development of personalised medicine, prevention of diseases and health promotion in general. Additional factors are health determinants and should also be considered, as highlighted by the World Health Organization, including the physical, social and economic environment, genetics, as well as relationships with friends and family. However, today’s health records (Electronic - EHRs and Personal - PHRs) are far from being what the citizens consider as of value to their health. This is consistent with the beliefs of the public regarding health as more than being disease-free and includes a variety of everyday living aspects, such as the environment, the active and fit lifestyle, the nutrition, the mental and emotional health. Capturing this information, as well as linking it with other data in EHRs and PHRs would be of benefit for learning about outcomes of prevention strategies and health policies, diseases, efficiency of patient pathway management.

The Health Information Technology for Economic and Clinical Health Act (HITECH) and the Patient Protection and Affordable Care Act (PPACA) considered the incorporation of such information into EHRs of major importance, as well as the widespread adoption and meaningful use of these enhanced records, so as to emerge into placeholders of all types of multi-* information: emerging from multiple sources, incorporating multi-discipline knowledge, facilitating multi-stakeholder collaboration and capturing multi-morbidity cases. An additional aspect in integrated care is the added value emerging from the collective community knowledge, with respect to policy making, disease prevention and health life support. Collective community knowledge could play a significant dual goal: (i) collect, fuse and analyse information from different entities in order to extract valuable knowledge towards the provision of actionable insights at the point of care, and (ii) provide the ground for targeted and efficient policy making at all levels.

CrowdHEALTH addresses the aforementioned challenges by allowing the evolution of health records in two stages as depicted in the figure below: (i) Towards Holistic Health Records (HHRs) to provide an integrated view of the patient including all health determinants. HHRs capture both health-related facts (such as clinical data, diagnoses, medication, genomics, etc.) and additionally the multi-* information such as nutrition, lifestyle choices (e.g. physical activities), environmental conditions, sensors information (home or wearables), or social information. (ii) Towards Clusters of HHRs to extract collective knowledge. The clustered HHRs act as living entities in a social space, thus enabling information sharing in an automated and continuous way. HHRs include properties such as their experience (reflecting the experiences of patients), their relationship with other HHRs (reflecting both their social relationships with friends and family but also their “classification” of relationships in terms for example patients with the same disease), their reputation, as well as events and trends that affect the patient or similar patients. The latter means that HHRs could form networks in an automated way based on a variety of criteria (such as lifestyle choices or disease symptoms) and exchange information as experiences.

Join us in MIE2018 to learn and experience the Holistic Health Records!