Clinical data warehouses offer tremendous benefits as a foundation for data mining.
By serving as a source for comprehensive clinical and demographic information on large
patient populations, they streamline knowledge discovery efforts by providing standard
and efficient mechanisms to replace time-consuming and expensive original data collection,
organization, and processing. Building effective data warehouses requires knowledge
of and attention to key issues in database design, data acquisition and processing,
and data access and security. In this article, the authors provide an operational
and technical definition of data warehouses, present examples of data mining projects
enabled by existing data warehouses, and describe key issues and challenges related
to warehouse development and implementation.
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