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Year:: 2014
Contributor:: Bill, Robert (author); Pakhomov, Serguei (author); Chen, Elizabeth S. (author); Winden, Tamara J. (author); Carter, Elizabeth W. (author); Melton, Genevieve B. (author)
Genre:: papers (documents)
Subject:: Family history

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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 (NL) 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.
Notes:: Source: Electronic Health Record; Method: Natural Language Processing; The National Institutes of Health (1 R01 LM011364-01 NIH-NLM, 1 R01 GM102282-01 A1 NIH-NIGMS, U54 RR 02066-01A2 NIH-NCRR) and Clinical and Translational Science Award (8UL1TR000114-02) supported this work.; Paper presented at the 2014 AMIA Annual Symposium

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Use and Reproduction: This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Citation

Bill, Robert, Pakhomov, Serguei, Chen, Elizabeth S., et al., "Automated extraction of family history information from clinical notes" (2014). SFHERE Publications and Presentations. Brown Digital Repository. Brown University Library. https://repository.library.brown.edu/studio/item/bdr:697490/

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SFHERE Publications and Presentations

This collection houses journal articles, conference papers and presentations, and abstracts and posters authored by members of the SFHERE team.
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Automated extraction of family history information from clinical notes