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.”

For more information:

Related Content

Partners HealthCare Chooses Visage 7 for Enterprise Imaging
News | Enterprise Imaging | January 18, 2019
Visage Imaging Inc. announced the signing of Partners HealthCare, the largest health system in Massachusetts, for...
Novel Technique May Significantly Reduce Breast Biopsies
News | Breast Biopsy Systems | January 17, 2019
A novel technique that uses mammography to determine the biological tissue composition of a tumor could help reduce...
Seamless Interoperability – Fact or Fiction? This webinar will show how Nemours Children’s Health System adoption of ScImage’s PICOM365 Enterprise PACS  improved workflow. The product will be highlighted at HIMSS 2019.
Sponsored Content | Webinar | PACS | January 17, 2019
This ScImage-sponsored ITN/DAIC webinar will be held at 2 p.m. Eastern time, Wednesday, Feb. 6, 2019.
NewYork-Presbyterian Hospital Partners With Philips for Health IT and Clinical Informatics
News | Enterprise Imaging | January 16, 2019
Philips announced that NewYork-Presbyterian Hospital has chosen to implement the company’s IntelliSpace Enterprise...
Artificial Intelligence Used in Clinical Practice to Measure Breast Density
News | Artificial Intelligence | January 15, 2019
An artificial intelligence (AI) algorithm measures breast density at the level of an experienced mammographer,...
Sponsored Content | Videos | Artificial Intelligence | January 15, 2019
ITN Contributing Editor Greg Freiherr offers an overview of...
Machine Learning Uncovers New Insights Into Human Brain Through fMRI
News | Neuro Imaging | January 11, 2019
An interdisciplinary research team led by scientists from the National University of Singapore (NUS) has successfully...
Videos | Interventional Radiology | January 11, 2019
Julius Chapiro, M.D., research faculty member and an...
AI Approach Outperformed Human Experts in Identifying Cervical Precancer
News | Digital Pathology | January 10, 2019
January 10, 2019 — A research team led by investigators from the National Institutes of Health and Global Good has de
Artificial intelligence, also called deep learning and machine learning, was the hottest topic at the 2018 Radiological Society of North America (RSNA)) meeting.

Artificial intelligence was the hottest topic at the 2018 Radiological Society of North America (RSNA)) meeting, which included a large area with its own presentation therater set asside for AI vendors.

Feature | Artificial Intelligence | January 10, 2019 | Dave Fornell, Editor
Hands down, the hottest topic in radiology the past two years has been the implementation of...