3 challenges to the regulation of digital health

Regulatory bodies across the globe have struggled to keep up with the rapid transformation of healthcare: By the time they established a framework governing the development and deployment of medical devices, the sector had evolved to encompass even more advanced digital health solutions.

A new report from the PHG Foundation, a nonprofit health policy think tank affiliated with the University of Cambridge, describes three major challenges associated with the regulation of digital health across the US and UK. The report also offers recommendations to address these issues and considerations for regulatory bodies.

The mere fact that digital health is included under the medical device umbrella presents the first major challenge outlined in the report. Not only are both medical devices and algorithm-based digital health tools growing exponentially, but they also require vastly different regulatory tests and analyses. As a result, regulatory agencies will need to equip employees with the expertise required to assess machine learning and other advanced technologies, while developers will need to be informed of any new or evolving regulations.

Secondly, with the expansion of consumer-facing digital health solutions, the line between medical devices and those that merely manage lifestyle factors and overall well-being has blurred. More explicit definitions are needed: "What qualifies as a medical device must be sufficiently flexible for regulators to regulate risky devices but also rigid enough for manufacturers to be given some degree of certainty over whether their device will qualify as a medical device or not," per the report.

Finally, machine learning poses its own set of regulatory issues. Though some artificial intelligence tools operate within transparent, easily understandable methods, others are uninterpretable "black boxes." Those, as well as AI algorithms that constantly self-update, present safety concerns that have yet to be addressed by any regulatory framework, but could potentially fit into existing medical device regulations. Therefore, the report's authors wrote, "We urge caution when regulating machine learning, [as] it would be unwise to regulate the entire field according to an exceptional subset of machine learning tools."

View the full report here.

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