Big Data Analytics are indispensable components of architectures dealing with processing and visualizing results of diverse healthcare-related information sources. In this work, we propose a versatile cloud design where the Health Analytic Tools (HATs) are decoupled from the Datastore and the User-Interface parts, still preserving the element of system trust. This design offers advantages over the process of modifying and constructing new health policy models by means of supporting many-to-many relations between HATs and Health Key Performance Indicators. Additionally, it offers independence regarding HAT providers, analytics frameworks, cloud providers and deployment environments allowing the scaling of the proposed architecture.
Where: IEEE International Conference on BigData 2018, December 2018, Seatle (USA)