Text data extraction for a prospective, research-focused data mart: implementation and validation
Translational research typically requires data abstracted from medical records as well as data collected specifically for research. Unfortunately, many data within electronic health records are represented as text that is not amenable to aggregation for analyses. We present a scalable open source SQL Server Integration Services package, called Regextractor, for including regular expression parsers into a classic extract, transform, and load workflow. We have used Regextractor to abstract discrete data from textual reports from a number of machine generated sources. To validate this package, we created a pulmonary function test data mart and analyzed the quality of the data mart versus manual chart review.
electronic health records medical informatics information storage and retrieval information systems automatic data processing