title: HPARSER: extracting formal patient data from free text history and physical reports using natural language processing software.
abstract: A prototype, HPARSER, processes a patient history and physical report such that specific data are obtained and stored in a patient data record. HPARSER is a recursive transition network (RTN) parser, and includes English and medical grammar rules, lexicon, and database constraints. Medical grammar rules augment the grammar rule base and specify common phrases seen in patient reports (e.g., "pupils are equal and reactive"). Each database constraint associates a grammar rule with a database table and attribute. Constraint behavior is such that if a rule is satisfied, data is extracted from the parse tree and stored into the database. Control reports guided construction of grammar and constraint rules. Test reports were processed with the control rules. 85% of test report sentences parsed and a 60% data capture rate, compared to controls, was achieved. HPARSER demonstrates use of an RTN to parse patient reports, and database constraints to transfer formal data from parse trees into a database.
authors.forename: J L
authors.initials: JL
authors.lastname: Sponsler
mesh_terms: D006801:Humans; D016247:Information Storage and Retrieval; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing