Insurance payment for artificial intelligence technology: Methods used by a stroke artificial intelligence system and strategies to qualify for the new technology add-on payment

Author:

Murray Nick M1ORCID,Phan Phillip23,Hager Greg4,Menard Andrew5,Chin David6,Liu Alvin7,Hui Ferdinand K5

Affiliation:

1. Department of Neurology, Intermountain Medical Center, Murray, UT, USA

2. Carey Business School, Johns Hopkins University, Baltimore, MD, USA

3. Department of Medicine, The Johns Hopkins Hospital, Baltimore, MD, USA

4. Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA

5. Department of Radiology, The Johns Hopkins Hospital, Baltimore, MD, USA

6. Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA

7. Department of Ophthalmology, The Johns Hopkins Hospital, Baltimore, MD, USA

Abstract

The first ever insurance reimbursement for an artificial intelligence (AI) system, which expedites triage of acute stroke, occurred in 2020 when the Centers for Medicare and Medicaid Services (CMS) granted approval for a New Technology Add-on Payment (NTAP). Key aspects of the AI system that led to its approval by the CMS included its unique mechanism of action, use of robotic process automation, and clear linkage of the system’s output to clinical outcomes. The specific strategies employed encompass a first-case scenario of proving reimbursable value for improved stroke outcomes using AI. Given the rapid change in utilization of AI technology in stroke care, we describe the economic drivers of stroke AI systems in healthcare, focusing on concepts of reimbursement for value added by AI to the stroke care system. This report reviews (1) the successful approach used by the first NTAP-approved AI system, (2) economic variables in insurance reimbursement for AI, and (3) resultant strategies that may be utilized to facilitate qualification for NTAP reimbursement, which may be adopted by other AI systems used in stroke care.

Publisher

SAGE Publications

Subject

Neurology (clinical),Radiology, Nuclear Medicine and imaging,General Medicine

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