Research Patient Data Warehousing

Abstract

Recent years have seen a push to increase the adoption of electronic health records and other clinical information systems in the United States. This has led to a corresponding increase in the volume and breadth of data that are generated during the course of clinical care. Institutions have a strong desire to analyze and mine this information for quality improvement and research purposes. To accomplish this, they are turning to systems that allow them to integrate data from several systems and synthesize it into a coherent view. These systems, commonly called data warehouses or integrated data repositories, are now serving as the basis for much of the clinical and translational research that occurs in medicine today. Here we describe the different components of a research patient data warehouse, including data models and terminologies, extract, transform and load (ETL) procedures used to populate the warehouse and steps institutions need to take to ensure patient privacy. We also provide an overview of one of the more popular open-source warehousing technologies, the Informatics for Integrating Biology and the Bedside (i2b2) platform.