Automatic Extraction of Risk Factors for Dialysis Patients from Clinical Notes Using Natural Language Processing Techniques.

Journal: Studies in health technology and informatics
Published Date:

Abstract

Studies have shown that mental health and comorbidities such as dementia, diabetes and cardiovascular diseases are risk factors for dialysis patients. Extracting accurate and timely information associated with these risk factors in the patient health records is not only important for dialysis patient management, but also for real-world evidence generation. We presented HERALD, an natural language processing (NLP) system for extracting information related to risk factors of dialysis patients from free-text progress notes in an electronic dialysis patient management system. By converting semi-structured notes into complete sentences before feeding them into the NLP module, the HERALD system was able achieved 99%, 83% and 80% accuracy in identifying dementia, diabetes and infarction, respectively.

Authors

  • George Michalopoulos
    University of Waterloo.
  • Hammad Qazi
    School of Public Health and Health Systems, University of Waterloo, Waterloo, N2L 3G1, Canada.
  • Alexander Wong
    Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada.
  • Zahid Butt
    University of Waterloo.
  • Helen Chen
    University of Waterloo.