title: Automated extraction of family history information from clinical notes.
abstract: Despite increased functionality for obtaining family history in a structured format within electronic health record systems, clinical notes often still contain this information. We developed and evaluated an Unstructured Information Management Application (UIMA)-based natural language processing (NLP) module for automated extraction of family history information with functionality for identifying statements, observations (e.g., disease or procedure), relative or side of family with attributes (i.e., vital status, age of diagnosis, certainty, and negation), and predication ("indicator phrases"), the latter of which was used to establish relationships between observations and family member. The family history NLP system demonstrated F-scores of 66.9, 92.4, 82.9, 57.3, 97.7, and 61.9 for detection of family history statements, family member identification, observation identification, negation identification, vital status, and overall extraction of the predications between family members and observations, respectively. While the system performed well for detection of family history statements and predication constituents, further work is needed to improve extraction of certainty and temporal modifications.
authors.affiliation: Institute for Health Informatics, University of Minnesota, Minneapolis, MN.
authors.forename: Robert
authors.initials: R
authors.lastname: Bill
authors.affiliation: Institute for Health Informatics, University of Minnesota, Minneapolis, MN ; College of Pharmacy, University of Minnesota, Minneapolis, MN.
authors.forename: Serguei
authors.initials: S
authors.lastname: Pakhomov
authors.affiliation: Center for Clinical & Translational Science, University of Vermont, Burlington, VT ; Department of Medicine, University of Vermont, Burlington, VT.
authors.forename: Elizabeth S
authors.initials: ES
authors.lastname: Chen
authors.affiliation: Institute for Health Informatics, University of Minnesota, Minneapolis, MN ; Division of Applied Research, Allina Health, Minneapolis, MN.
authors.forename: Tamara J
authors.initials: TJ
authors.lastname: Winden
authors.affiliation: Center for Clinical & Translational Science, University of Vermont, Burlington, VT.
authors.forename: Elizabeth W
authors.initials: EW
authors.lastname: Carter
authors.affiliation: Institute for Health Informatics, University of Minnesota, Minneapolis, MN ; Department of Surgery, University of Minnesota, Minneapolis, MN.
authors.forename: Genevieve B
authors.initials: GB
authors.lastname: Melton
mesh_terms: D057286:Electronic Health Records; D005192:Family Health; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D008487:Medical History Taking / Q000379:methods*; D009323:Natural Language Processing