An unsupervised learning approach to identify immunoglobulin utilization patterns using electronic health records.

Journal: Transfusion
PMID: 37861272

Abstract

BACKGROUND: Managing Canada's immunoglobulin (Ig) product resource allocation is challenging due to increasing demand, high expenditure, and global shortages. Detection of groups with high utilization rates can help with resource planning for Ig products. This study aims to uncover utilization subgroups among the Ig recipients using electronic health records (EHRs).

Authors

  • Kiarash Riazi
    Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
  • Mark Ly
    Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Canada.
  • Rebecca Barty
    Ontario Regional Blood Coordinating Network, Hamilton, Ontario, Canada.
  • Jeannie Callum
    Department of Pathology and Molecular Medicine, Kingston Health Sciences Centre and Queen's University, Kingston, Ontario, Canada.
  • Donald M Arnold
    Michael G. DeGroote Centre for Transfusion Research, Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
  • Nancy M Heddle
    Michael G. DeGroote Centre for Transfusion Research, Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
  • Douglas G Down
    Department of Computing and Software, McMaster University, Hamilton, Ontario, Canada.
  • Davinder Sidhu
    Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
  • Na Li
    School of Nursing, Fujian University of Traditional Chinese Medicine, Fuzhou, China.

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