Analysis of risk factor domains in psychosis patient health records.

Journal: Journal of biomedical semantics
Published Date: Oct 31, 2019

Abstract

BACKGROUND: Readmission after discharge from a hospital is disruptive and costly, regardless of the reason. However, it can be particularly problematic for psychiatric patients, so predicting which patients may be readmitted is critically important but also very difficult. Clinical narratives in psychiatric electronic health records (EHRs) span a wide range of topics and vocabulary; therefore, a psychiatric readmission prediction model must begin with a robust and interpretable topic extraction component.

Authors

  • Eben Holderness
    Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Mill St, Belmont, MA, USA.
  • Nicholas Miller
    Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Mill St, Belmont, MA, USA.
  • Philip Cawkwell
    Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Mill St, Belmont, MA, USA.
  • Kirsten Bolton
    Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Mill St, Belmont, MA, USA.
  • Marie Meteer
    Brandeis University Department of Computer Science, South St, Waltham, MA, USA.
  • James Pustejovsky
    Brandeis University Department of Computer Science, South St, Waltham, MA, USA.
  • Mei-Hua Hall
    Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Mill St, Belmont, MA, USA. mhall@mclean.harvard.edu.

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