Analyzing Collective Knowledge Towards Public Health Policy Making

摘要

Nowadays there exists a plethora of diverse data sources producing tons of healthcare data, augmenting the size of data that finally is stored both in Electronic Health Records (EHRs) and in Personal Health Records (PHRs). Thus, the great challenge that emerges is not only to gather all this data in an efficient and effective manner, but also to extract knowledge out of it. The latter is the key factor that enables healthcare professionals to take serious clinical decisions both on individual and on collective level, finally forming representative public health policies. Towards this direction, the current paper proposes a system that supports a new paradigm of EHRs, the extended Health Records (XHRs), which include the majority of the health determinants. XHRs are then transformed into XHRs Networks that capture the clinical, social and human context of diverse population segmentations, producing the corresponding collective knowledge. By exploiting this knowledge, the proposed system is finally able to create multi-modal policies, addressing various facts and evolving risks that arise from diverse population segmentations.