- The more data organizations collect from connected medical, Internet of Things (IoT), mobile, and medical monitoring devices, the more difficult it is for them to justify a centralized data repository for all healthcare data. Healthcare edge computing is emerging as a way for entities to embrace near real-time results by processing data at the edge of the network at the data source.
A recent Research and Markets report predicted that the edge computing market will grow at a CAGR of 35 percent through 2022. This increase will be in response to the growth in data generated from multiple sources across different applications, the rise of real-time applications, and the increase of dependence on cloud infrastructure, according to the report.
An IEEE report also came to a similar conclusion, stating that cloud computing is not an efficient way to process data when the data is produced at the edge of the network.
IEEE 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.
The increase of IoT devices and organizations putting more computing tasks into the cloud are the two major catalysts for edge computing in healthcare.
Medical IoT devices are constantly collecting data and communicating with the network. If an IoT or monitoring device is used to collect patient data at the point of care, the patient still has to wait for results and often has to make another appointment to come back once the clinician gets the data and can make an assessment.
If a clinician is able to gather and process the data at the edge of the network, she can be presented with actionable data in near real-time. Actionable data in near real-time allows clinicians to make a more accurate diagnosis at the point of care, which can lead to a reduced number of return visits and save entities money.
The increase in healthcare cloud services also calls for the relief of edge computing. Organizations are putting more computing tasks into the cloud because of the cloud’s flexibility. Organizations don’t need to invest in additional on-premises resources to expand their IT infrastructure solutions and tools. However, when too many different devices are all communicating with the same cloud repository and the same cloud-based tools, that communication overload can cause slower data processing times.
Clinicians are not just referring to a patient’s EHR. 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 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,” IEEE 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.”
Edge computing is becoming a more useful tool as healthcare organizations continue to expand their IoT and cloud IT infrastructure environments. The future of healthcare will involve more data and entities need to adjust their infrastructure to accommodate the influx of data.