Machine learning for improving high-dimensional proxy confounder adjustment in healthcare database studies: An overview of the current literature.

Journal: Pharmacoepidemiology and drug safety
PMID: 35729705

Abstract

PURPOSE: Supplementing investigator-specified variables with large numbers of empirically identified features that collectively serve as 'proxies' for unspecified or unmeasured factors can often improve confounding control in studies utilizing administrative healthcare databases. Consequently, there has been a recent focus on the development of data-driven methods for high-dimensional proxy confounder adjustment in pharmacoepidemiologic research. In this paper, we survey current approaches and recent advancements for high-dimensional proxy confounder adjustment in healthcare database studies.

Authors

  • Richard Wyss
    Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • Chen Yanover
    KI Research Institute, Kfar Malal, Israel.
  • Tal El-Hay
    KI Research Institute, Kfar Malal, Israel.
  • Dimitri Bennett
    Global Evidence and Outcomes, Takeda Pharmaceutical Company Ltd., Cambridge, Massachusetts, USA.
  • Robert W Platt
  • Andrew R Zullo
    Department of Health Services, Policy, and Practice, Brown University School of Public Health and Center of Innovation in Long-Term Services and Supports, Providence Veterans Affairs Medical Center, Providence, Rhode Island, USA.
  • Grammati Sari
    Real World Evidence Strategy Lead, Visible Analytics Ltd, Oxford, UK.
  • Xuerong Wen
    Health Outcomes, Pharmacy Practice, College of Pharmacy, University of Rhode Island, Kingston, Rhode Island, USA.
  • Yizhou Ye
    Global Epidemiology, AbbVie Inc., Illinois, USA.
  • Hongbo Yuan
    Canadian Agency for Drugs and Technologies in Health, Ottawa, Canada.
  • Mugdha Gokhale
    Pharmacoepidemiology, Center for Observational and Real-world Evidence, Merck, Pennsylvania, USA.
  • Elisabetta Patorno
    Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • Kueiyu Joshua Lin
    Division of Pharmacoepidemiology and Pharmacoeconomics Department of Medicine Brigham and Women's Hospital Harvard Medical School Boston MA.

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