News | Artificial Intelligence | May 15, 2018

Joint ACR-SIIM Summit to Examine Economics of AI in Healthcare

Summit will explore opportunities and challenges of integrating artificial intelligence into the economics of radiology

Joint ACR-SIIM Summit to Examine Economics of AI in Healthcare

May 15, 2018 — On May 30, 2018, the American College of Radiology (ACR) Data Science Institute (DSI) and the Society for Imaging Informatics in Medicine (SIIM) will hold the Spring 2018 Data Science Summit: Economics of Artificial Intelligence (AI) in Health Care. The summit will be hosted at the SIIM 2018 Annual Meeting, May 31-June 2 in National Harbor, Md.

“Moving AI algorithms into routine clinical practice will require that our healthcare system supports fair compensation for their development. However, there is no simple one-size-fits-all payment scheme for reimbursing the use of AI in healthcare. In fact, the medical community will have to demonstrate the value and cost savings to patients before reimbursement will be considered,” said Bibb Allen, M.D., FACR, chief medical officer of the ACR Data Science Institute.

By exploring the opportunities and challenges associated with integrating AI into the economics of heathcare, expert facilitators will help AI algorithms developers consider the reimbursement, regulatory and implementation issues which will influence payment. The program will also:

  • Outline the current and future systems for Medicare and commercial healthcare reimbursement in the United States;
  • Define the mechanisms and challenges for reimbursement of AI software algorithms within the traditional U.S. fee-for-service (FFS) payment system;
  • Describe the shift in U.S. payment policy from the traditional FFS payment system to value-based reimbursement models defined in the Medicare Quality Payment Program;
  • Define the role of AI in value-based reimbursement models and the development of quality metrics for radiology; and
  • Define the opportunities and challenges for reimbursement of AI software algorithms within value-based payment models.

“Machine learning and deep learning are emerging technologies with great potential that enable novel business models to translate these discoveries to improve patient care,” said Paul G. Nagy, Ph.D., FSIIM, CIIP, chair of SIIM. “SIIM is excited to partner with the ACR on putting together a workshop to discuss the economics of machine learning in medical imaging right before the SIIM annual meeting this year in Washington, D.C.”

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