Abstract: As in many places, Memorial Sloan Kettering Cancer Center has a need to provide researchers high quality data extracted from the clinical notes. Despite the advances in natural language processing and other types of machine learning, many researchers at MSK manually abstract data from clinical notes and store them in spreadsheets. This presents many problems since spreadsheets are often lost. Data entered in those files often using no standard terminology, making it very hard to share and reuse them. MSK EXTRACT is a three-tiered approach to luring researchers away from spreadsheets into REDCap. The first tier is a custom web application that uses the “shopping cart” motif to help people create their own REDCap databases. The shopping cart presents a list of data elements and permissible values mapped to various ontologies. Users search for, select and add these standard terms to their project. This functionality enables REDcap projects built with this application to use standard terminology and ultimately allows data reuse and facilitate data sharing.

Learning Objective: By the end of this demonstation, the learner should be able to:
1. Understand how Shopping Cart helps disseminate standard terminology
2. Understand how Shopping Cart enables a bottom up approach to building a libary of standard terms
3. Understand how Shopping Cart enables building REDCap projects using templates
4. Understand how Shopping Cart enables building REDCap projects using standard terms.


John Philip (Presenter)
Memorial Sloan Kettering

Rimma Belenkaya, Memorial Sloan Kettering
Pete Stetson, Memorial Sloan Kettering

Presentation Materials: