The Regulation of Medical AI: Policy Approaches, Data, and Innovation Incentives / Ariel Dora Stern.

Format:

Book

Author/Creator:

Stern, Ariel Dora.

Contributor:

National Bureau of Economic Research.

Series:

Working Paper Series (National Bureau of Economic Research) no. w30639.

NBER working paper series no. w30639

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2022.

Summary:

For those who follow health and technology news, it is difficult to go more than a few days without reading about a compelling new application of Artificial Intelligence (AI) to health care. AI has myriad applications in medicine and its adjacent industries, with AI-driven tools already in use in basic science, translational medicine, and numerous corners of health care delivery, including administrative work, diagnosis, and treatment. In diagnosis and treatment, a large and growing number of AI tools meet the statutory definition of a medical device or that of an in-vitro diagnostic. Those that do are subject to regulation by local authorities, resulting in both practical and strategic implications for manufacturers, along with a more complex set of innovation incentives. This chapter presents background on medical device regulation--especially as it relates to software products--and quantitatively describes the emergence of AI among FDA-regulated products. The empirical section of this chapter explores characteristics of AI-supported/driven medical devices ("AI devices") in the United States. It presents data on their origins (by firm type and country), their safety profiles (as measured by associated adverse events and recalls), and concludes with a discussion of the implications of regulation for innovation incentives in medical AI.

Notes:

Print version record

December 2022.