Ever hear of edge computing? If you’re in healthcare, you will soon if you haven’t already, according to experts.
The reason is IoT.
IoT devices such as fitness wearables, glucose monitors, telehealth tools and other sensors are poised to revolutionize health. But there are some barriers that are keeping IoT from realizing its full potential in the healthcare space.
The trouble with these products is the data are messy. Information is unstandardized and poorly-defined. When clinicians are confronted with such data, they become overwhelmed and are unlikely to use the products.
Even more troubling, Health IT managers, data integrity experts and EHR designers have long predicted that the volume of data contained in these devices could easily overtax existing systems.
Finally, right now, big data can take days, weeks or even months to make the journey from its source to its end-user. If data cannot be analyzed quickly enough, the value, particularly in healthcare, is reduced.
Even for real-time analytics, healthcare currently uses cloud solutions to store data once it is collected from the device. Cloud middleware takes the data and pulls relevant material into an analytics system. That message is then delivered to the user interface. The process can take a few seconds, or several minutes, belying the “real-time” promise.