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Edge Computing Uses IoT Devices for Fast Health IT Analytics

Edge computing is becoming more prominent in health IT infrastructure as organizations adopt more Internet of Things devices for analytics.

Edge computing is rising in health IT infrastructure as organizations embrace IoT and analytics

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- Healthcare organizations are rapidly adopting analytics solutions as part of their HIT infrastructures to offer better patient care. As the number of analytics solutions and internet of things (IoT) devices introduced into healthcare networks grows, more advanced ways of handling data are needed to ensure clinicians receive data quickly.

Edge computing is becoming more popular in healthcare as organizations introduce more connected medical devices into their health IT ecosystem.

IoT and connected medical devices produce data at the edge of the network. Traditionally, data is produced at the edge of the network and transported back to the datacenter. Edge computing processes the data at the source or the edge of the network.

According to a report published by the IEEE Internet of Things Journal, cloud computing is not an efficient way to process data when the data is produced at the edge of the network.

Report authors defined edge computing as “enabling technologies allowing computation to be performed at the edge of the network, on downstream data on behalf of cloud services and upstream data on behalf of IoT services. The ‘edge’ is as any computing and network resources along the path between data sources and cloud data centers.”

A clinician’s mobile device is the edge between the patient who is the data source and the cloud. A clinician treating a patient with a tablet will be able to enter patient data into the analytics platform at the edge where it is processed and displayed in near real-time. Patients no longer need to wait for analytics results, which may reduce their number of visits.

Edge computing is needed in enterprises with a substantial amount of IoT devices, including the push from cloud services, pull from IoT, and the change from data consumer to producer, the report explained.  

The push from cloud services comes from organizations putting most commuting tasks into the cloud. While this method is efficient because of the computing power offered by the cloud, data is being produced at the edge in quantities that are too large to be passed to the cloud due to bandwidth restrictions.

The volume of IoT devices, along with the volume of data they constantly produce, causes a bottleneck for cloud-based computing. Cloud-based computing is more efficient than edge computing, but bandwidth restrictions actually make edge computing the better choice for near real-time analytics. 

Report authors stated that almost all types of electrical devices will eventually be part of the IoT. The pull from IoT indicates that all IoT devices will produce and consume data. The number of IoT devices is expected to reach the billions in the near future making the volume of data produced by them much too large for conventional cloud computing.

Report authors also cited the change of connected devices from data consumers to producers as a driving factor behind edge computing. Users are not only consuming data on their smart devices (documents, charts, etc.), but those devices are now producing data as well. This paradigm shift means that more functionality is needed at the edge.

Clinicians are not just referring to a patient’s EHR anymore, and they are actively recording data and sharing it with the network via the cloud. A health IT network needs to support more than just the basic mobile functionalities. It also needs to support the exchange of data at the edge.

One of the healthcare specific benefits edge computing offers healthcare is the collaborative edge.

“The demand of geographically distributed data processing applications, i.e., healthcare, requires data sharing and collaboration among enterprises in multiple domains,” report authors explained. “To attack this challenge, collaborative edge can fuse geographically distributed data by creating virtual shared data views. The virtual shared data is exposed to end users via a predefined service interface.”

“An application will leverage this public interface to compose complex services for end users,” report authors continued. “These public services are provided by participants of collaborative edge, and the computation only occurs in the participant’s data facility such that the data privacy and integrity can be ensured.”

Healthcare organizations are currently dealing with high volumes of IoT devices as more connected medical devices are utilized in everyday hospital settings.

“An average hospital room will have between 15 and 20 medical devices, and almost all of them will be networked,”  Aruba Networks Product Marketing Manager Rick Reid told HITInfrastructure.com. “That’s a pretty high density if you think about the size of an ICU room, which is usually about 15’x15’ with 20 devices in it - and the room next door has 20 devices in it. A ward typically has 20 beds, so that’s quite a lot of devices in a relatively small area.”

A large hospital can have as many as 85,000 connected medical and IoT devices putting massive strain on the healthcare network.

Large healthcare organizations with current or future big data analytics prospects need to look into edge computing to ensure that clinicians and patients will get the best response times from the data they produce. As the number of IoT devices continues to grow, edge computing may become a standard in health IT infrastructure.