ARTIFICIAL INTELLIGENCE IN MEDICAL DEVICES- REGULATORY AND REIMBURSEMENT LANDSCAPE IN THE UNITED STATES
Author(s)
Cheung LH1, Kodjamanova P2, Evans A3, Mesana L1
1Amaris, Jersey City, NJ, USA, 2Amaris, Sofia, Bulgaria, 3Amaris, Barcelona, Spain
OBJECTIVES: Artificial intelligence (AI) in medical devices can decrease inefficiencies, provide greater access, and minimize costs. We aimed to determine the current regulatory and reimbursement landscape of AI medical devices in the United States (US) and the challenges payers may face with integrating these devices into their coverage policies. METHODS: Guidance developed by the Food and Drug Administration (FDA) was reviewed to determine the efforts put in place to govern the use of AI medical devices. A search was then conducted for devices that were currently approved or in the process of being approved to better define an AI medical device. Lastly, a targeted review of the literature was conducted in EMBASE and Pubmed. Studies of interest evaluated payer perspectives on AI medical devices in the US. Information extracted included payer type, type of AI medical device, reimbursement status, coverage evaluation criteria, and challenges encountered. RESULTS: Our initial review revealed limited guidance on regulation and reimbursement for AI medical devices. However, there has been an increase in the number of working groups, and initiatives developed by the FDA. Review of the guidance highlighted the FDA’s main concern with data protection and cybersecurity. As of January 2019, the FDA has approved two AI medical devices; one for detecting acute inter-cranial cases, and another for spotting wrist fractures. Four others are undergoing pre-market approval. The literature search on payer perspectives yielded 122 results; 22 abstracts were included with four studies meeting the inclusion criteria. No studies highlighted the use of objective evaluation criteria by payers. CONCLUSIONS: Unlike the rapidly evolving nature of AI, the regulation and reimbursement that supports it lags behind in its development. With the advancements in AI, there is a need for further research on payer perspective to standardize coverage policy for AI medical devices.
Conference/Value in Health Info
2019-05, ISPOR 2019, New Orleans, LA, USA
Value in Health, Volume 22, Issue S1 (2019 May)
Code
PNS77
Topic
Health Policy & Regulatory, Medical Technologies, Methodological & Statistical Research
Topic Subcategory
Artificial Intelligence, Machine Learning, Predictive Analytics, Insurance Systems & National Health Care, Medical Devices, Reimbursement & Access Policy
Disease
No Specific Disease