Digital-health infrastructure benefits from cloud-to-edge architecture

During COVID-19, digital health took off as physical distancing requirements became paramount.

Some providers saw increases in virtual visits in the tens of thousands, other components, including remote patient monitoring  and wearable technology, were becoming more commonplace.

Prior to the advent of the pandemic, 88% of healthcare providers had invested in a remote patient monitoring (RPM) system, which could include blood glucose monitors or oximeters. And by 2022, the number of wearable devices in the U.S. is expected to top 67 million.

But, to make digital health accessible to patients and useful for providers, the right infrastructure and integration with electronic health records (EHRs) are required.

Currently, the digital divide is closing; 83% of U.S. residents in rural areas now have access to broadband service. Less than 10% do not have access to mobile broadband. Edge computing can further bring digital health services to patients by decentralizing data into smaller data centers tailored for specific purposes or populations.

In the Cloud or at the Edge for Digital Health Infrastructure?

Cloud infrastructure is critical for developing apps and connecting patient devices with EHRs. “The traditional source of truth for hospitals are medical records, but that’s an extremely small segment of the data versus what the RPM apps and devices are collecting,” said Mike McSherry, CEO of Xealth.

But when it comes to the wearables and sensors themselves, edge computing can make it easier to transmit data from wearables and sensors like connected blood glucose monitors, oximeters, weight scales, blood pressure cuffs, or other monitors used by diabetic patients.

According to the Journal of Diabetes Science and Technology, these devices upload to smartphones and tablets, which serve as edge computing hubs. The data is processed on one of these mobile devices, then uploaded to either an edge data center or to a centralized cloud repository for analysis. The disadvantage is that data isn’t uploaded in real time if the patient’s smartphone or tablet is offline.

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