Utility of Machine Learning, Natural Language Processing, and Artificial Intelligence in Predicting Hospital Readmissions After Orthopaedic Surgery: A Systematic Review and Meta-Analysis.

Journal: JBJS reviews
Published Date: Aug 22, 2024

Abstract

BACKGROUND: Numerous applications and strategies have been utilized to help assess the trends and patterns of readmissions after orthopaedic surgery in an attempt to extrapolate possible risk factors and causative agents. The aim of this work is to systematically summarize the available literature on the extent to which natural language processing, machine learning, and artificial intelligence (AI) can help improve the predictability of hospital readmissions after orthopaedic and spine surgeries.

Authors

  • Mohamad Y Fares
    Division of Shoulder and Elbow Surgery, Rothman Orthopaedic Institute, Philadelphia, PA 19107, USA.
  • Harry H Liu
    RAND Corporation, 20 Park Plaza, Suite 920, Boston, MA, 02116, USA. hliu@rand.org.
  • Ana Paula Beck da Silva Etges
    Avant-garde Health, Boston, Massachusetts.
  • Benjamin Zhang
    Brigham and Women's Hospital, Boston, Massachusetts.
  • Jon J P Warner
    Department of Orthopaedic Surgery, Harvard Medical School, Boston Shoulder Institute, Massachusetts General Hospital, Boston, Massachusetts.
  • Jeffrey J Olson
    Hartford Healthcare, Hartford, Connecticut.
  • Catherine J Fedorka
    Cooper Bone and Joint Institute, Cooper University Hospital, Camden, New Jersey.
  • Adam Z Khan
    Southern Permanente Medical Group, Pasadena, CA 91188, USA.
  • Matthew J Best
    Department of Orthopaedic Surgery, Johns Hopkins Hospital, Johns Hopkins University School of Medicine, Baltimore, Maryland.
  • Jacob M Kirsch
    Department of Orthopaedic Surgery, New England Baptist Hospital, Tufts University School of Medicine, Boston, Massachusetts.
  • Jason E Simon
    Department of Orthopaedic Surgery, Massachusetts General Hospital/Newton-Wellesley Hospital, Boston, Massachusetts.
  • Brett Sanders
    Center for Sports Medicine and Orthopaedics, Chattanooga, Tennessee.
  • John G Costouros
    Institute for Joint Restoration and Research, California Shoulder Center, Menlo Park, California.
  • Xiaoran Zhang
    Department of Electrical and Computer Engineering, University of California, Los Angeles, United States; Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Canada; Servier Virtual Cardiac Centre, Mazankowski Alberta Heart Institute, Edmonton, Canada. Electronic address: xiaoran108@ucla.edu.
  • Porter Jones
    Avant-garde Health, Boston, Massachusetts.
  • Derek A Haas
    Avant-garde Health, Boston, Massachusetts.
  • Joseph A Abboud
    Division of Shoulder and Elbow Surgery, Rothman Orthopaedic Institute, Philadelphia, PA 19107, USA.

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