{"id":34325,"date":"2023-03-23T13:32:15","date_gmt":"2023-03-23T13:32:15","guid":{"rendered":"https:\/\/zpesystems.com\/?page_id=34325"},"modified":"2023-04-28T21:30:45","modified_gmt":"2023-04-28T21:30:45","slug":"edge-computing-in-healthcare-zs","status":"publish","type":"page","link":"https:\/\/zpesystems.com\/resources\/edge-computing-in-healthcare-zs\/","title":{"rendered":"Edge Computing in Healthcare: Benefits and Best Practices"},"content":{"rendered":"

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Edge Computing in Healthcare: Benefits and Best Practices<\/h1>\n

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Modern healthcare is powered by data. There are roughly 10 billion<\/a> IoT (internet of things) medical devices used in healthcare today, such as pacemakers, insulin pumps, and heart rate monitors. These devices generate a lot of data, which is processed and analyzed by software applications to help clinicians provide better care. Typically, the data collected from these remote devices must be sent somewhere else to be processed \u2013 often to an application hosted in a centralized data center or the cloud. However, this is proving too inefficient for the real-time data processing needed in the healthcare industry, where doctors and patients need fast, accurate care solutions. Edge computing in healthcare is the practice of moving computing power and data processing systems closer to the sources of medical data so it can be analyzed at the speed needed to save lives and improve patient outcomes.<\/p>\n

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Table of Contents<\/strong><\/td>\n<\/tr>\n
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  1. Cloud computing vs. edge computing in healthcare<\/a><\/li>\n
  2. The benefits of edge computing in healthcare<\/a><\/li>\n
  3. Best practices for edge computing in healthcare<\/a>
    \u00a0\u00a0\u00a0\u00a0 a.     SD-WAN<\/a>
    \u00a0\u00a0\u00a0\u00a0 b.     Security<\/a>
    \u00a0\u00a0\u00a0\u00a0 c.     Automation<\/a>
    \u00a0\u00a0\u00a0\u00a0 d.     Vendor-neutral platforms<\/a><\/li>\n
  4. Simplifying edge computing in healthcare with Nodegrid<\/a><\/li>\n<\/ol>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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    To learn more about implementing edge computing in your healthcare organization, reach out to the experts at ZPE Systems.<\/b><\/p>\n

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    Cloud computing vs. edge computing in healthcare<\/h2>\n

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    There are a large number of sensors used in a healthcare setting to monitor patient health, including in pacemakers, MRI machines, insulin pumps, and ultrasound imaging devices. These sensors generate large quantities of data that must be processed and analyzed, which requires a lot of computing power. Many organizations have moved away from on-premises data centers and offloaded their computing requirements to the cloud, which saves them from needing to purchase and maintain their own hardware.<\/p>\n

    However, in a cloud computing model, patient data must be transmitted to and from the cloud for processing, which adds latency and presents additional security challenges. For example, mobile EMS devices and wearable sensors often use cellular networks to connect to cloud computing resources on the internet. However, transmitting patient data over the public internet creates security risks, which is why many healthcare organizations use VPNs to pass that data through the central firewall before it\u2019s sent to the cloud. The firewall turns into a bottleneck that adds additional latency to data transmissions, which prevents real-time data transformation or computation and creates potentially harmful delays.<\/p>\n

    In contrast, the edge computing model processes patient data using computing resources that are on the same LAN, which significantly reduces transmission time. For example, a clinic may have edge computers in the same rack as their networking equipment, or an ambulance may have an all-in-one cellular edge router with data processing capabilities stowed in a small compartment. In some cases, edge computing processors are built into the medical devices themselves, so data collection and data processing happen virtually simultaneously.<\/p>\n

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    Processing health data at the edge reduces latency, which improves the performance and accuracy of the applications using that data. In addition, keeping the data on the local network decreases the risk that it will be intercepted in transit, making security and HIPAA compliance easier. Plus, using SD-WAN (software-defined wide area networking) technology, clinicians can securely monitor and access remote patient health data without the use of VPNs, which means they\u2019re alerted to urgent issues much faster.<\/p>\n

    In contrast, the edge computing model processes patient data using computing resources that are on the same LAN, which significantly reduces transmission time. For example, a clinic may have edge computers in the same rack as their networking equipment, or an ambulance may have an all-in-one cellular edge router with data processing capabilities stowed in a small compartment. In some cases, edge computing processors are built into the medical devices themselves, so data collection and data processing happen virtually simultaneously.<\/p>\n

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    To learn more, watch our<\/b> Avoiding Downtime with a Better Edge Infrastructure<\/b><\/a> video.<\/b><\/p>\n

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    The benefits of edge computing in healthcare<\/h2>\n