Detecting clinically relevant new information in clinical notes across specialties and settings.

Journal: BMC medical informatics and decision making
Published Date: Jul 5, 2017

Abstract

BACKGROUND: Automated methods for identifying clinically relevant new versus redundant information in electronic health record (EHR) clinical notes is useful for clinicians and researchers involved in patient care and clinical research, respectively. We evaluated methods to automatically identify clinically relevant new information in clinical notes, and compared the quantity of redundant information across specialties and clinical settings.

Authors

  • Rui Zhang
    Department of Cardiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Serguei V S Pakhomov
    Institute for Health Informatics; College of Pharmacy University of Minnesota, Minneapolis, MN.
  • Elliot G Arsoniadis
    Institute for Health Informatics; Department of Surgery.
  • Janet T Lee
    Department of Surgery, University of Minnesota, Minneapolis, MN, USA.
  • Yan Wang
    College of Animal Science and Technology, Beijing University of Agriculture, Beijing, China.
  • Genevieve B Melton
    Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, USA.

Keywords

External Resources

Popular Topics
Recent Journals