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The Economic Impact of AI on Breast Imaging.
Smetherman, Dana; Golding, Lauren; Moy, Linda; Rubin, Eric.
Afiliação
  • Smetherman D; Ochsner Health, Department of Radiology, New Orleans, LA, USA.
  • Golding L; Triad Radiology Associates, PLLC, Winston-Salem, NC, USA.
  • Moy L; NYU Langone Health, New York, NY, USA.
  • Rubin E; Southeast Radiology Limited, Philadelphia, PA,USA.
J Breast Imaging ; 4(3): 302-308, 2022 Jun 07.
Article em En | MEDLINE | ID: mdl-38416968
ABSTRACT
This article explores the development of computer-aided detection (CAD) and artificial or augmented intelligence (AI) for breast radiology examinations and describes the current applications of AI in breast imaging. Although radiologists in other subspecialties may be less familiar with the use of these technologies in their practices, CAD has been used in breast imaging for more than two decades, as mammography CAD programs have been commercially available in the United States since the late 1990s. Likewise, breast radiologists have seen payment for CAD in mammography and breast MRI evolve over time. With the rapid expansion of AI products in radiology in recent years, many new applications for these technologies in breast imaging have emerged. This article outlines the current state of reimbursement for breast radiology AI algorithms within the traditional fee-for-service model used by Medicare and commercial insurers as well as potential future payment pathways. In addition, the inherent challenges of employing the existing payment framework in the United States to AI programs in radiology are detailed for the reader. This article aims to give breast radiologists a better understanding of how AI will be reimbursed as they seek to further incorporate these emerging technologies into their practices to advance patient care and improve workflow efficiency.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: J Breast Imaging Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: J Breast Imaging Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos