Machine-learning-based cost prediction models for inpatients with mental disorders in China.

Journal: BMC psychiatry
PMID: 39789477

Abstract

BACKGROUND: Mental disorders are increasingly prevalent, leading to increased medical expenditures. To refine the reimbursement of medical costs for inpatients with mental disorders by health insurance, an accurate prediction model is essential. Per-diem payment is a common internationally implemented payment method for medical insurance of inpatients with mental disorders, necessitating the exploration of advanced machine learning methods for predicting the average daily hospitalization costs (ADHC) based on the characteristics of inpatients with mental disorders.

Authors

  • Yuxuan Ma
    School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
  • Xi Tu
    School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
  • Xiaodong Luo
    Norwegian Research Centre (NORCE), Bergen, Norway.
  • Linlin Hu
    School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China. hulinlin@sph.pumc.edu.cn.
  • Chen Wang
    Department of Cardiovascular Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.

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