Predicting the risk of acute care readmissions among rehabilitation inpatients: A machine learning approach.

Journal: Journal of biomedical informatics
Published Date: Oct 1, 2018

Abstract

INTRODUCTION: Readmission from inpatient rehabilitation facilities to acute care hospitals is a serious problem. This study aims to develop a predictive model based on machine learning algorithms to identify patients at high risk of readmission.

Authors

  • Yajiong Xue
    Department of Management Information Systems, College of Business, East Carolina University, USA.
  • Huigang Liang
    Department of Management Information Systems, College of Business, East Carolina University, USA; Center for Healthcare Management Systems, College of Business, East Carolina University, USA; Big Data and Analytics Research Cluster, East Carolina University, USA. Electronic address: liangh@ecu.edu.
  • John Norbury
    Department of Physical Medicine & Rehabilitation, Brody School of Medicine, East Carolina University, USA.
  • Rita Gillis
    Vidant Health, USA.
  • Brenda Killingworth
    Department of Management Information Systems, College of Business, East Carolina University, USA.

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