We have previously written about the security implications of the Internet of Things on healthcare applications and how Apple's desire to avoid FDA healthcare regulations has resulted in a somewhat underwhelming rollout of Apple's HealthBook apps.
We have also looked at Apple's ResearchKitand some of the implications it has on how clinical trials can be enrolled and managed.
Now comes news that FitBit has been sued for overstating the accuracy of its sleep measurement. One way to look at this is that the USA is overly litigious society. We would suggest that there is another way to look at this. Namely that part of how the USA's regulatory system works is through the power of CrowdSourced enforcement. Empowering citizen lawsuits against violators was critical to how the EPA was able to enforce environmental cleanup far broader than it could accomplish as a single governmental agency. And the current FTC laws similarly enable such CrowdSourced enforcement.
This is important to understand as the Internet Of Things (IoT) explodes into the Connected Healthcare. The future of medicine is this concept of Connected Healthcare that includes Internet Of Things based sensors and mobile end devices, connected through mobile mHealth devices into Big Data (also known as Machine Learning) analytics. But much of this Connected Healthcare world still needs to be developed to the robustness we have come to expect in our Medical Devices.
The promise is that lower cost devices that can measure vital signs and track various physiological activity will offer us insights both at the Personal Medicine level (enabling customization to each of our particular cases) as well as that the aggregated data of more detailed and accurate symptoms will lead to analytic and even preventative detection processes.
There are multiple challenges with this.
One is the question of accuracy and reliability of the data. This is what we are seeing in the FitBit lawsuit, and it is also why solutions like the mySugr Diabetes Logbook tend to opt for the protection of FDA certification. Had FitBit taken even the rudimentary steps of running a small trial the way the Mio Alpha 2 did they would likely have insulated themselves from a lawsuit.
So even something as straightforward as a Diabetes Logbook that ties into a blood glucose monitoring system needs to weigh what sort of claims it wants to make and what evidence it needs to collect to support the claims. Simply invoking the FDA's Fitness and Wellness exemption is not enough to provide full risk protection.
Unfortunately finding this information is not straightforward. Not only do you have some dozen different FDA databases to look at, but many of the underlying documents are simply scans and hence not searchable. Nor is the FDA dataset well integrated with the crucial ClinicalTrials.gov from NIH, or the CMS coverage guidances. Enter https://ClearRoadmap.com. We have built an app that enables searching not only the metadata across all these sources from a single interface, but our Patent Pending Natural Language Processing of the underlying documents enables you to search for keywords in context . For example Diabetes as an "indication of use" for an assay, is very different than Diabetes as an "Adverse Event" for a drug eluting stent.
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How to Effectively Find mHealth, Wellness and Mobile Medical Regulatory Data