Towards a Privacy, Secured and Distributed Clinical Data Warehouse Architecture

Reputed organisations are always prompting Data Warehouses (DWs), which are essential for storing and mining their historical datasets. When it comes to the healthcare industry, DWs are becoming ever so imperative, as efficient storage for medical data is vital for one's health while mining it and seeking new insights. While clinical datasets are very complex, their timely integration and analysis are crucial to providing excellent care for patients. This research aims to provide an efficient data warehousing solution with multiple privacy and security measures integrated by design. Securing the data at all stages: during data input, exploration, pre-processing, selection, analysis, and presentation, is very challenging. This research explores data security from a holistic perspective and possible distributed analysis mechanisms while streamlining data sharing between healthcare centres to increase efficiency and better patient treatments. This study also considers security and privacy issues at all stages of the data warehousing process (data lifecycle) to ensure its correct handling and use. We focus on distributed clinical data warehouse architectures. We also describe the main requirements of a clinical data warehouse for the whole data lifecycle, Data Capture, Acquisition Management, Archiving, Sharing, Reporting, Analysis, and Privacy and Security. The proposed architecture is evaluated considering existing state-of-the-art concerning data analysis and sharing capabilities while ensuring data security and privacy.

Automated summary

This research aims to provide an efficient data warehousing solution with multiple privacy and security measures integrated by design. It explores data security from a holistic perspective and possible distributed analysis mechanisms while streamlining data sharing between healthcare centres to increase efficiency and better patient treatments.