Health Law Advisor

Most people have seen the growth in artificial intelligence/ machine learning (AI/ML)-based medical devices being cleared by FDA.  FDA updates that data once a year at the close of its fiscal year.  Clearly the trend is up. But that's a bit backward looking, in the sense that we are only learning after the fact about FDA clearances for therapeutic applications of AI/ML.  I want to look forward.  I want a leading indicator, not a laggard.

I also want to focus on uses of AI/ML that are truly therapeutic or diagnostic, as opposed to the wide variety of lifestyle and wellness AI/ML products and the applications used on the administrative side of healthcare.  As a result, in this post I explore the information on clinicaltrials.gov because not only are those data focused on the truly health related, they are also forward-looking. The more recent clinical trials involve products still under investigation and not yet commercially available or even submitted to FDA.

Introduction

Hardly a day goes by when we don’t see some media report of health care providers experimenting with machine learning, and more recently with generative AI, in the context of patient care. The allure is obvious. But the question is, to what extent do health care providers need to worry about FDA requirements as they use AI?

In the absence of a federal law directly aimed at regulating artificial intelligence (AI), the Federal Trade Commission (FTC) is seeking to position itself as one of the primary regulators of this emergent technology through existing laws under the FTC’s ambit. As we recently wrote, the FTC announced the establishment of an Office of Technology, designed to provide technology expertise and support the FTC in enforcement actions. In a May 3, 2023 opinion piece published in the New York Times entitled “We Must Regulate A.I. Here’s How,” Lina Khan, the Chairperson of the FTC, outlined at least three potential avenues for FTC enforcement and oversight of artificial intelligence technology.

The application of artificial intelligence technologies to health care delivery, coding and population management may profoundly alter the manner in which clinicians and others interact with patients, and seek reimbursement. While on one hand, AI may promote better treatment decisions and streamline onerous coding and claims submission, there are risks associated with unintended bias that may be lurking in the algorithms. AI is trained on data. To the extent that data encodes historical bias, that bias may cause unintended errors when applied to new patients. This can result in ...

After a Congressional override of a Presidential veto, the National Defense Authorization Act became law on January 1, 2021 (NDAA). Notably, the NDAA not only provides appropriations for military and defense purposes but, under Division E, it also includes the most significant U.S. legislation concerning artificial intelligence (AI) to date: The National Artificial Intelligence Initiative Act of 2020 (NAIIA).

The NAIIA sets forth a multi-pronged national strategy and funding approach to spur AI research, development and innovation within the U.S., train and prepare an ...