Deep Learning Preoperatively Predicts Value Metrics for Primary Total Knee Arthroplasty: Development and Validation of an Artificial Neural Network Model.

Journal: The Journal of arthroplasty
Published Date: Jun 20, 2019

Abstract

BACKGROUND: The objective is to develop and validate an artificial neural network (ANN) that learns and predicts length of stay (LOS), inpatient charges, and discharge disposition before primary total knee arthroplasty (TKA). The secondary objective applied the ANN to propose a risk-based, patient-specific payment model (PSPM) commensurate with case complexity.

Authors

  • Prem N Ramkumar
    Department of Orthopedic Surgery, Cleveland Clinic, Cleveland, OH.
  • Jaret M Karnuta
    Department of Orthopedic Surgery, Cleveland Clinic, Cleveland, OH.
  • Sergio M Navarro
    Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, Said Business School, University of Oxford, Oxford, United Kingdom.
  • Heather S Haeberle
    Department of Orthopaedic Surgery, Baylor College of Medicine, Houston, TX.
  • Giles R Scuderi
    Department of Orthopaedic Surgery, Lenox Hill, New York, NY.
  • Michael A Mont
    Department of Orthopaedic Surgery, Lenox Hill Hospital of Northwell Health, New York, NY.
  • Viktor E Krebs
    Department of Orthopedic Surgery, Cleveland Clinic, Cleveland, OH.
  • Brendan M Patterson
    Department of Orthopedic Surgery, Cleveland Clinic, Cleveland, OH.

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