Medical Language Processing: Applications to Patient Data Representation and Automatic Encoding

Abstract:

A linguistic approach is presented to develop a representation of patient data. Semantic categories developed for computer processing of narrative clinical reports are shown to be similar to the Medical Concepts used manually to extract data from narrative in Exercises of the Computer-based Patient Record Institute. Clinical statement types composed of these categories are used in the Linguistic String Project (LSP) medical language processing (MLP) system to convert narrative information into relational database tables of patient information. A procedure for mapping the output of the LSP MLP system into SNOMED International codes was developed. Preliminary results and further requirements are discussed.

Keywords:

Natural Language Processing - Automatic Encoding - SNOMED - Clinical Data Representation

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