Generality and reuse in a common type system for clinical natural language processing

Authors:
Stephen T. Wu;Vinod C. Kaggal;Guergana K. Savova;Hongfang Liu;Jiaping Zheng;Wendy W. Chapman;Christopher G. Chute;Dmitriy Dligach
Affiliations:
Mayo Clinic, Rochester, MN, USA;Mayo Clinic, Rochester, MN, USA;Childrens Hospital Boston and Harvard Medical School, Boston, MA, USA;University of Colorado at Boulder, Boulder, CO, USA;Childrens Hospital Boston and Harvard Medical School, Boston, MA, USA;University of California, San Diego, San Diego, CA, USA;Mayo Clinic, Rochester, MN, USA;University of Colorado at Boulder, Boulder, CO, USA
Venue:
Proceedings of the first international workshop on Managing interoperability and complexity in health systems
Year:
2011

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Abstract

The aim of Area 4 of the Strategic Healthcare IT Advanced Research Project (SHARP 4) is to facilitate secondary use of data stored in Electronic Medical Records (EMR) through high throughput phenotyping. Clinical Natural Language Processing (NLP) plays an important role in transforming information in clinical text to standard representation that is comparable and interoperable. To meet the NLP requirement of different secondary use cases of EMR, accommodate different NLP approaches, enable the interoperability between structured and unstructured data generated in different clinical settings, we define a common type system for clinical NLP that integrates a comprehensive model of clinical semantics with language processing types for SHARP 4. The type system has been implemented in UIMA (Unstructured Information Management Architecture), which allows for flexible passing of input and output data types among NLP components, and is available at the SHARP 4 website.