Current Reimbursement Landscape of Artificial Intelligence

George Wu; Colin S Segovis; Lauren P Nicola; Melissa M Chen

doi:10.1016/j.jacr.2023.07.018

Current Reimbursement Landscape of Artificial Intelligence

J Am Coll Radiol. 2023 Oct;20(10):957-961. doi: 10.1016/j.jacr.2023.07.018. Epub 2023 Aug 19.

Authors

George Wu¹, Colin S Segovis², Lauren P Nicola³, Melissa M Chen⁴

Affiliations

¹ Department of Radiology, Baylor College of Medicine, Houston, Texas.
² Medical Director for the Revenue Cycle Operations, Director of MRI Quality and Safety, Codirector of Radiology Elective Clerkship for the Department of Radiology and Imaging Sciences, Department of Radiology, Emory University School of Medicine, Atlanta, Georgia; American Society of Neuroradiology CPT (Current Procedure Terminology) Advisor, Chair of the ASNR Economics Committee and Treasurer of the Georgia Radiological Society.
³ Chief Executive Officer, Triad Radiology Associates, Winston Salem, North Carolina; Inpatient Medical Director of Novant Forsyth Medical Center, ACR Relative Value Scale Update Committee Advisor, Chair of the ACR Reimbursement Committee, and member of the ACR Board of Chancellors as the Chair of the Ultrasound Commission.
⁴ Patient Safety Quality Officer for Diagnostic Imaging and is Associate Executive Director for the MD Anderson Cancer Network, Department of Neuroradiology, MD Anderson Cancer Center, Houston, Texas; American Society of Neuroradiology Relative Value Scale Update Committee Advisor, Chair of the American Society of Neuroradiology Health Policy Committee, ACR Council Steering Committee Member, and Treasurer for the Texas Radiological Society. Electronic address: melissa.mei.chen@gmail.com.

PMID: 37604328
DOI: 10.1016/j.jacr.2023.07.018

Abstract

One of the biggest hurdles to widespread adoption of new procedures and technology such as artificial intelligence (AI) algorithms is payment and coverage policy. Noninvasive assessment of coronary fractional flow reserve is one AI imaging algorithm that will successfully achieve reimbursement through multiple pathways of CMS payment mechanisms in 2024. CMS is the largest provider of health care in the United States. Understanding how this AI algorithm is paid through the different fee schedules will help to understand the challenges CMS has in paying for new services and innovation in the United States.

Keywords: AI; CPT; HOPPs; new technology APC; reimbursement.

MeSH terms

Artificial Intelligence*
Delivery of Health Care
Fee Schedules
Fractional Flow Reserve, Myocardial*
United States