FDA Releases Guidance on AI-Driven Clinical Decision Support Tools

The Food and Drug Administration (FDA) has released new guidance stating that some artificial intelligence (AI) tools should be regulated as medical devices as part of the agency’s oversight of clinical decision support (CDS) software.

The new guidance includes a list of AI tools that should be regulated as medical devices, including devices to predict sepsis, identify patient deterioration, forecast heart failure hospitalizations, and flag patients who may be addicted to opioids, among others.

In recent years, AI and machine learning (ML) have been increasingly incorporated into medical devices because these algorithms are capable of “learning” from experience and improving performance over time.

As a result, the FDA Center for Devices and Radiological Health (CDRH) is considering “a total product lifecycle-based regulatory framework for these technologies that would allow for modifications to be made from real-world learning and adaptation, while ensuring that the safety and effectiveness of the software as a medical device are maintained.”

The FDA traditionally reviews medical devices through an “appropriate premarket pathway,” but the agency recognizes that this regulatory framework was not designed for adaptive technologies such as AI and ML. Regulators have noted that these technologies may require premarket review under the existing agency approach to software modifications.

In 2019, the agency published a discussion paper outlining a potential approach to premarket review for AI and ML software. As part of its Artificial Intelligence and Machine Learning (AI/ML) Software as a Medical Device Action Plan, the CDRH’s Digital Health Center of Excellence took feedback on the 2019 paper and formulated a response outlining actions the FDA intends to take in this area.

The new guidance is the latest step the agency has taken toward AI/ML regulation. It is the final guidance based on earlier draft guidance from 2019, which was designed to further define the scope of the FDA’s CDS oversight and encourage health IT innovation.

The final guidance follows requests from stakeholders, such as the American Medical Informatics Association (AMIA), to provide further clarification around the use and development of CDS tools. In 2018, the AMIA argued that the existing guidance did not adequately account for the rapid growth of machine learning. Following the release of updated draft guidance, AMIA responded with similar criticisms again in 2020.

Guidance around CDS tools and medical device regulation was developed originally in compliance with the 21st Century Cures Act, which was signed into law in 2016 to streamline drug approval processes at the FDA, provide medical research funding, encourage more effective EHR and health IT use, and support health data interoperability.