Assessment of utilization efficiency using machine learning techniques: A study of heterogeneity in preoperative healthcare utilization among super-utilizers.

Journal: American journal of surgery
Published Date: Sep 1, 2020

Abstract

INTRODUCTION: In the United States, 5% of patients represent up to 55% of all health care costs. This study sought to define healthcare utilization patterns among super-utilizers, as well as assess possible variation in patient outcomes.

Authors

  • J Madison Hyer
    Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Cancer Hospital and Solove Research Institute, Columbus, OH.
  • Anghela Z Paredes
    Department of Surgery, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
  • Susan White
    Department of Financial Services, The Ohio State University Wexner Medical Center and James Cancer Hospital and Solove Research Institute, Columbus, OH.
  • Aslam Ejaz
    Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Cancer Hospital and Solove Research Institute, Columbus, OH. Electronic address: aslam.ejaz@osumc.edu.
  • Timothy M Pawlik
    Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Cancer Hospital and Solove Research Institute, Columbus, OH.

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