A Preliminary Study of Clinical Abbreviation Disambiguation in Real Time.

Journal: Applied clinical informatics
Published Date: Jun 3, 2015

Abstract

OBJECTIVE: To save time, healthcare providers frequently use abbreviations while authoring clinical documents. Nevertheless, abbreviations that authors deem unambiguous often confuse other readers, including clinicians, patients, and natural language processing (NLP) systems. Most current clinical NLP systems "post-process" notes long after clinicians enter them into electronic health record systems (EHRs). Such post-processing cannot guarantee 100% accuracy in abbreviation identification and disambiguation, since multiple alternative interpretations exist.

Authors

  • Y Wu
    School of Biomedical Informatics, The University of Texas Health Science Center at Houston , Houston, Texas, USA.
  • J C Denny
    Department of Biomedical Informatics Camridge, Vanderbilt University , Nashville, Tennessee, USA.
  • S T Rosenbloom
    Department of Biomedical Informatics Camridge, Vanderbilt University , Nashville, Tennessee, USA.
  • R A Miller
    Department of Biomedical Informatics Camridge, Vanderbilt University , Nashville, Tennessee, USA.
  • D A Giuse
    Department of Biomedical Informatics Camridge, Vanderbilt University , Nashville, Tennessee, USA.
  • M Song
    Department of Library and Information Science, Yonsei University , Seoul, Korea.
  • H Xu
    School of Biomedical Informatics, The University of Texas Health Science Center at Houston , Houston, Texas, USA.

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