Dive Brief:

• As more clinical studies incorporate wearables and other digital health technologies, the Food and Drug Administration shared best practices on Thursday. 
• Digital health technologies may be beneficial because they capture information about a person’s health during their everyday life, Rick Abramson, director of the FDA’s Digital Health Center of Excellence, wrote in a blog post. However, these technologies need to be validated, and researchers also must ask if what they’re measuring matters to patients. 
• The discussion on digital health technologies corresponds with efforts on real-world evidence and patient generated data at the FDA’s device center. The agency published final guidance in December on the use of real-world data for regulatory decision-making in medical devices.

Dive Insight:

Digital health technologies can provide insight into sleep, mobility, cardiovascular function or other aspects of a person’s health in their day-to-day life. In some cases, the technologies can enable earlier detection of treatment effects or other safety signals, and can support decentralized clinical trials, Abramson wrote.

The best digital measurements should focus on what aspect of health researchers are looking to understand. Abramson emphasized the importance of direct input from patients to help identify the aspects of health that matter most.

Technologies should also be evaluated to ensure that they provide precise and accurate measurements, and that the results reflect meaningful changes in a person’s health. 

The FDA’s medical product centers, including those focused on medical devices, biologics, drugs and oncology, jointly published a white paper explaining these principles. 

For example, researchers may want to measure walking in people with cardiovascular disease. First, they would need to determine what aspects of walking, such as walking bout length or step count, would best capture a person’s ability to move.

The technologies used to capture these measurements also need to go through analytical and clinical validation. An example of analytical validation would be ensuring an accelerometer accurately captures values that are converted to step count. Clinical validation would be confirming that walking bout length captures changes in mobility for people with different degrees of cardiovascular disease.

The FDA’s device center has emphasized real-world evidence in its recent medical device user fee amendments, which set the center’s priorities and how much funding it can receive from industry over a five-year period. The device center committed to training stakeholders on real-world evidence and patient generated health data, and expanding its expertise and staff capacity to respond to submissions with this data.