Edge computing is a way to process data close to where it is created, like medical devices or local servers, instead of sending it to big cloud centers far away. In healthcare, this means data from devices like pacemakers, insulin pumps, heart monitors, wearable sensors, and remote health checks can be looked at quickly near the patient’s location.
Right now, there are around 10 billion medical Internet of Things (IoT) devices used in healthcare systems across the United States. These devices make a lot of data that needs to be processed fast so doctors can make quick decisions. For example, emergency medical workers can use 5G devices in ambulances to check patient data fast. This lets them share important health details and treatment advice before they get to the hospital. Processing data near the source cuts down delays, so patient care can be faster.
Besides speed, edge computing helps healthcare workers do their jobs more easily. It can give better test results by looking at data faster, lower costs by needing less big computer power in one place, and help keep patient information more private by sending less data over public internet networks.
The healthcare field has very private data, like health records and biometric details. Protecting this data keeps patients safe and follows laws like HIPAA. But using edge computing also brings new security challenges.
Old IT security methods trust everything inside a network. This means if a hacker gets in, they can move around inside the system and reach a lot of data. This is not enough for today’s spread-out computing systems.
The zero trust security model is important here. Its rule is “never trust, always check.” It means no user or device gets automatic access, whether inside or outside the network. Each access request must be checked carefully every time.
Zero trust security includes:
The National Institute of Standards and Technology (NIST) offers guidance on following zero trust rules through its Zero Trust Architecture (SP 800-207). This helps organizations lower risks while meeting healthcare rules.
Medical practice leaders and IT managers in the U.S. can get these benefits by using zero trust with edge computing:
Modern edge computing uses SD-WAN (software-defined wide area networking) to make network connections between edge devices and central health systems better. SD-WAN helps manage wide network areas securely and quickly. This is critical for sharing health information safely.
SD-WAN helps keep patient data secure by choosing safe network paths and avoiding delays or risky transmissions. Technologies like Secure Access Service Edge (SASE) combine SD-WAN with security tools to make defenses stronger.
Artificial intelligence (AI) and automation help zero trust work better in healthcare. AI can watch network traffic and user actions all the time to find unusual behavior that might be a threat. Automation can apply security rules quickly without people needing to do it by hand. This makes IT work easier.
For example, AI systems can guess network problems or spot threats early based on data from edge devices. Automation can handle tasks like updating policies or checking that devices meet security rules. Using AI and automation makes healthcare systems safer and less likely to have mistakes.
With services like Simbo AI that automate front-office phone calls, zero trust helps keep patient information safe during chats. AI can check who is calling in real time and make sure only the right people get health details.
AI helps healthcare workers handle patient data faster, cut down waiting times, and lower risks from manual mistakes or security problems. Smart AI can also warn if someone tries to get access in a strange way during calls. IT managers can act fast to stop possible breaches.
Automation also applies security rules across devices in hospitals and clinics. This ensures only authorized people can see clinical data or use medical IoT devices. AI can also help predict when parts of the network might fail and fix issues before they cause harm.
Healthcare in the U.S. has its own challenges for keeping data safe, made harder by large systems with many parts. Big medical groups, hospitals with many locations, and clinics use different IT setups, making security more complex.
Medical leaders and IT managers in the U.S. must handle:
Using zero trust with edge computing and AI tools helps meet these challenges and can improve patient care.
Healthcare leaders in the U.S. should think about these steps when using zero trust security with edge computing:
As edge computing grows in healthcare, zero trust security is a must to protect patient privacy, meet laws, and keep systems running. U.S. healthcare groups that use zero trust with AI and automation will be ready to handle the changing needs of protecting healthcare data in the future.
Edge computing in healthcare refers to the practice of processing and analyzing medical data closer to the source of collection, such as on local devices or edge servers, rather than relying on centralized data centers or the cloud to reduce latency and improve real-time decision-making.
Edge computing enables near-real-time data analysis from wearable sensors and remote health devices, allowing healthcare providers to respond quickly to potential health issues before they escalate into emergencies.
Key benefits include improved remote patient care, enhanced speed and performance, increased workload efficiency, better security, diagnostic accuracy, and reduced costs.
By processing data locally on the same local area network (LAN), edge computing minimizes transmission times, allowing for faster data interactions and real-time responses.
SD-WAN allows for more efficient management of wide area networks, enabling secure and reliable data transmission between edge devices and central networks without the latency associated with traditional VPNs.
Although edge computing reduces some security risks, issues persist such as potential data interception and the necessity for robust security protocols to ensure compliance with regulations like HIPAA.
Zero trust security is a model that operates on the principle of ‘never trust, always verify,’ using strict access controls and continuous re-evaluation of trust for user accounts accessing sensitive data.
Automation can streamline the management of complex edge computing networks, reduce human error, and utilize AI and machine learning for predictive maintenance and operational efficiency.
Vendor-neutral platforms simplify management by unifying system operations, reducing complexity, and improving reliability across the extended network architecture while allowing for flexibility in deployments.
Nodegrid provides a vendor-neutral platform to manage edge computing solutions, enabling mobile SD-WAN access, remote monitoring, and integration of third-party applications to simplify edge deployments in healthcare.