Research data warehouses integrate research and patient data from one or more sources into a single data model that is designed for research. Typically, institutions update their warehouse by fully reloading it periodically. The alternative is to update the warehouse incrementally with new, changed and/or deleted data. Full reloads avoid having to correct and add to a live system, but they can render the data outdated for clinical trial accrual. They place a substantial burden on source systems, involve intermittent work that is challenging to resource, and may involve tight coordination across IT and informatics units. We have implemented daily incremental updating for our i2b2 data warehouse. Incremental updating requires substantial up-front development, and it can expose provisional data to investigators. However, it may support more use cases, it may be a better fit for academic healthcare IT organizational structures, and ongoing support needs appear to be similar or lower.
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