Data warehousing methodologies share a common set of tasks, including business requirements analysis, data design, architectural design, implementation and deployment. Clinical data warehouses are complex and time consuming to review a series of patient records however it is one of the efficient data repository existing to deliver quality patient care. Data integration tasks of medical data store are challenging scenarios when designing clinical data warehouse architecture. The presented data warehouse architectures are practicable solutions to tackle data integration issues and could be adopted by small to large clinical data warehouse applications.
|Cite as: Sahama, T.R. and Croll, P.R. (2007). A Data Warehouse Architecture for Clinical Data Warehousing. In Proc. Australasian Workshop on Health Knowledge Management and Discovery (HKMD 2007), Ballarat, Australia. CRPIT, 68. Roddick, J. F. and Warren, J. R., Eds. ACS. 227-232. |
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