scholarly journals Trans-national health insurance coverage in Eurasian Economic Union

2017 ◽  
Vol 27 (suppl_3) ◽  
Author(s):  
VG Polushkin ◽  
RA Halfin ◽  
VV Madyanova ◽  
SV Axelrod
2021 ◽  
Vol 64 (10) ◽  
pp. 648-653
Author(s):  
Seong Ho Park ◽  
Chang Min Park ◽  
Joon-Il Choi

Background: Interest in health insurance coverage for artificial intelligence (AI)–based medical technologies is growing. This article provides a review of the current developments in the sphere and provides future perspectives, focusing on AI application in radiology.Current Concepts: In December 2019, the Health Insurance Review and Assessment Service under the Korean Ministry of Health and Welfare released its first guidelines for determining the National Health Insurance coverage for AI–based medical technologies. Additionally, in 2020, the largest US health insurance provider, the Centers for Medicare and Medicaid Services, approved payment for AI technologies using two different systems. First, in September 2020, it granted New Technology Add-on Payments for AI algorithms that facilitate the diagnosis and treatment of large vessel occlusion strokes. Second, in December 2020, the Centers for Medicare and Medicaid Services finalized the provision of reimbursements for IDx-DR through a Current Procedural Terminology code. The AI system screens for more than mild diabetic retinopathy, which requires further evaluation by an ophthalmologist.Discussion and Conclusion: An in-depth look at the three events suggests the importance of demonstrating the added clinical value of AI technologies through improved patient outcomes in enabling insurance coverage. Therefore, it is critical to create clinically meaningful collaboration between healthcare professionals and AI by understanding and combining their unique strengths, thus actualizing new forms of patient care instead of having AI merely copy the professionals. Furthermore, if National Health Insurance coverage is granted for AI technologies in radiology, add-on payments would be the most appropriate method.


2015 ◽  
Vol 15 (3) ◽  
pp. 287-294 ◽  
Author(s):  
Yun-Min Heo ◽  
Hyoung-Joo Kim ◽  
Mi-Na Kim ◽  
Hee Jung Lim ◽  
Myoung-Hee Kim ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document