Real-time automated billing for tobacco treatment: developing and validating a scalable machine learning approach.

Journal: JAMIA open
Published Date: Jun 12, 2025

Abstract

OBJECTIVES: To develop CigStopper, a real-time, automated medical billing prototype designed to identify eligible tobacco cessation care codes, thereby reducing administrative workload while improving billing accuracy.

Authors

  • Derek J Baughman
    Barksdale Air Force Base, Bossier Parish, Louisiana.
  • Layth Qassem
    Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
  • Lina Sulieman
    Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA. Electronic address: lina.m.sulieman@vanderbilt.edu.
  • Michael E Matheny
    Vanderbilt University School of Medicine, Nashville, TN.
  • Daniel Fabbri
    Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
  • Hilary A Tindle
    Division of General Internal Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
  • Aubrey Cole Goodman
    Louisiana State University Health Shreveport, School of Medicine, Shreveport, LA 71103, United States.
  • Scott D Nelson
    George E. Whalen Department of Veterans Affairs Medical Center, Salt Lake City, UT, USA; University of Utah, Salt Lake City, UT, USA.
  • Adam Wright
    Harvard Medical School, Boston, MA; Brigham and Women's Hospital, Boston, MA.

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