Detection of probable dementia cases in undiagnosed patients using structured and unstructured electronic health records.

Journal: BMC medical informatics and decision making
PMID: 31288818

Abstract

BACKGROUND: Dementia is underdiagnosed in both the general population and among Veterans. This underdiagnosis decreases quality of life, reduces opportunities for interventions, and increases health-care costs. New approaches are therefore necessary to facilitate the timely detection of dementia. This study seeks to identify cases of undiagnosed dementia by developing and validating a weakly supervised machine-learning approach that incorporates the analysis of both structured and unstructured electronic health record (EHR) data.

Authors

  • Yijun Shao
    Veterans Affairs Medical Center, Washington, DC; George Washington University, Washington, DC.
  • Qing T Zeng
    George Washington University, 800 22nd St. NW, Science and Engineering Hall, Ste. #8390, Washington, DC, 20052, USA.
  • Kathryn K Chen
    Geriatric Research, Education, and Clinical Center, S182 GRECC, VA Puget Sound Health Care System, 1660 S. Columbian Way, Seattle, WA, 98108, USA.
  • Andrew Shutes-David
    Geriatric Research, Education, and Clinical Center, S182 GRECC, VA Puget Sound Health Care System, 1660 S. Columbian Way, Seattle, WA, 98108, USA.
  • Stephen M Thielke
    Geriatric Research, Education, and Clinical Center, S182 GRECC, VA Puget Sound Health Care System, 1660 S. Columbian Way, Seattle, WA, 98108, USA.
  • Debby W Tsuang
    Geriatric Research, Education, and Clinical Center, S182 GRECC, VA Puget Sound Health Care System, 1660 S. Columbian Way, Seattle, WA, 98108, USA. dwt1@uw.edu.

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