Predicting diabetes self-management education engagement: machine learning algorithms and models.

Journal: BMJ open diabetes research & care
PMID: 39965870

Abstract

INTRODUCTION: Diabetes self-management education (DSME) is endorsed by the American Diabetes Association (ADA) as an essential component of diabetes management. However, the utilization of DSME remains limited in the USA. This study aimed to investigate current DSME participation among the older population and to identify comprehensive factors of DSME engagement through employing various machine learning (ML) models based on a US nationally representative survey linked to claims data.

Authors

  • Xiangxiang Jiang
    Department of Clinical Pharmacy and Outcomes Sciences, University of South Carolina College of Pharmacy, Columbia, South Carolina, USA.
  • Gang Lv
    Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200000, China.
  • Minghui Li
    MOE Key Laboratory of Geriatric Diseases and Immunology, School of Biology and Basic Medical Sciences, Suzhou Medical College of Soochow University, Suzhou, Jiangsu Province 215123, China.
  • Jing Yuan
    School of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
  • Z Kevin Lu
    Department of Clinical Pharmacy and Outcomes Sciences, University of South Carolina College of Pharmacy, Columbia, South Carolina, USA lu32@mailbox.sc.edu.

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