JMIR Publications

ABSTRACT

Background:

Artificial Intelligence/Machine Learning (AI/ML) has revolutionized the healthcare industry, particularly in the development and use of medical devices. The FDA has authorized over 878 AI/ML-enabled medical devices, reflecting a growing trend in both quantity and application scope. Understanding the distinct challenges, they present in terms of FDA regulation violations is crucial for avoiding recalls effectively. This is particularly pertinent for proactive measures regarding medical devices.

Objective:

This study explores the impact of AI/ML on medical device recalls, focusing on the distinct causes associated with AI/ML-enabled devices compared to other device types. Recall information associated with 510k-cleared devices was obtained from OpenFDA. Three recall cohorts were established: "All 510K devices recall", "software-related devices recall", and "AI/ML devices recall".

Methods:

Recall information for 510k-cleared devices was obtained from OpenFDA. AI/ML-enabled medical devices were identified based on FDA listings. Three cohorts were established: "All 510K devices recall," "software-related devices recall," and "AI/ML devices recall." Root cause analysis was conducted for each recall event.

Results:

The results indicate that while the top five recall root causes are relatively similar across the three control groups, the proportions vary, with AI/ML devices showing a higher impact. Design and development-related factors contribute significantly to recalls in AI/ML devices, emphasizing the importance of thorough planning, user feedback incorporation, and validation during the development process to reduce the probability of recalls. In addition, changes in software, including design changes and control change, also contribute substantially to recalls in AI/ML devices.

Conclusions:

In conclusion, this study provides valuable insights into the unique challenges and considerations associated with AI/ML-enabled medical device recalls, offering guidance for manufacturers to enhance verification plans and mitigate risks in this rapidly evolving technological landscape.