Predicting Readmission Among High-Risk Discharged Patients Using a Machine Learning Model With Nursing Data: Retrospective Study.

Journal: JMIR medical informatics
PMID:

Abstract

BACKGROUND: Unplanned readmissions increase unnecessary health care costs and reduce the quality of care. It is essential to plan the discharge care from the beginning of hospitalization to reduce the risk of readmission. Machine learning-based readmission prediction models can support patients' preemptive discharge care services with improved predictive power.

Authors

  • Eui Geum Oh
    College of Nursing, Yonsei University, Seoul, Republic of Korea.
  • Sunyoung Oh
    School of Nursing, Yale University, New Haven, CT, United States.
  • Seunghyeon Cho
    Digital & Technology Group, CJ CheilJedang, Suwon, Republic of Korea.
  • Mir Moon
    Institute for Innovation in Digital Healthcare, Yonsei University, Seoul, Republic of Korea.