Identification of Patients in Need of Advanced Care for Depression Using Data Extracted From a Statewide Health Information Exchange: A Machine Learning Approach.

Journal: Journal of medical Internet research
Published Date:

Abstract

BACKGROUND: As the most commonly occurring form of mental illness worldwide, depression poses significant health and economic burdens to both the individual and community. Different types of depression pose different levels of risk. Individuals who suffer from mild forms of depression may recover without any assistance or be effectively managed by primary care or family practitioners. However, other forms of depression are far more severe and require advanced care by certified mental health providers. However, identifying cases of depression that require advanced care may be challenging to primary care providers and health care team members whose skill sets run broad rather than deep.

Authors

  • Suranga N Kasthurirathne
    Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, United States.
  • Paul G Biondich
    Regenstrief Institute, Inc., 410 West 10th Street, Suite 2000, Indianapolis, IN 46202-3012, USA; Children's Health Services Research, Indiana University, 410 West 10th Street, Suite 1000, Indianapolis, IN 46202-3012, USA.
  • Shaun J Grannis
    Regenstrief Institute, Indianapolis, IN, USA.
  • Saptarshi Purkayastha
    Indiana University School of Informatics and Computing, Indianapolis, IN, United States.
  • Joshua R Vest
    Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, United States.
  • Josette F Jones
    Indiana University School of Informatics and Computing, Indianapolis, IN, United States.