What Is Edge Computing in Healthcare?
From bustling emergency rooms to remote patient monitoring systems, the healthcare industry is increasingly deploying edge computing infrastructure to process data locally, reducing latency and enabling split-second decision support. This shift from centralized cloud computing to distributed edge processing isn’t just a technical upgrade—it’s revolutionizing how healthcare is delivered, experienced, and optimized.
Edge computing has emerged as a transformative solution that brings computational power closer to where data originates—at the “edge” of the network, near patients and Internet of Things (IoT)–powered medical devices, including:
- Wearables: These devices can give clinicians a timely status of key patient vitals such as heart rate and blood pressure, alerting medical staff to issues before they become problems.
- Health monitors: Healthcare providers can improve remote care by using health monitors to collect patient data and trigger actions. For example, edge devices can monitor blood glucose levels and send that information to a companion device, such as a pump, to dispense insulin.
- Artificial intelligence (AI) enabled devices: AI can help detect potential concerns in medical images, prioritizing those images for radiologist or physician review.
The potential of these emerging innovations is helping enable modern smart hospitals and an overall trend toward better clinician workflows, lower costs, and improved patient care.
Benefits of Edge Computing in Healthcare
Edge computing brings data processing, analytics, and storage closer to the source of data generation—for example, an on-premises server at a hospital or a mobile device at a patient’s home. Edge computing works as a complement to the cloud, allowing IT decision-makers to choose where to best place workloads along the compute spectrum. This strategy can help healthcare IT systems optimize data collection, storage, and analysis.
Accordingly, when healthcare decision-makers and stakeholders deploy edge computing as part of an overall technology strategy, they can experience a wide array of potential benefits, including:
- More-connected care: Edge computing is making it possible for organizations to surround patients in connected, data-centric networks of care. Data at the edge can help inform near-real-time decision-making, expedite clinical processes, streamline patient journeys, and reduce network costs.
- Greater accessibility: The integration of AI, computer vision, and edge computing enables critical care to follow the patient from hospital to home, practitioners to perform more analysis with less effort, and scientists to arrive at breakthroughs sooner.
- Deeper insights: The continued evolution of data infrastructure advancements is helping transform lab and life sciences. The resulting solutions can help improve the speed of patient diagnoses, the accuracy of tests, and rate of productivity through better workflow efficiency.
Challenges of Edge Computing in Healthcare
Edge computing implementation in healthcare is growing, but decision-makers and stakeholders must overcome several inherent challenges, including interoperability, device durability, and cybersecurity.
Ensuring Interoperability across Devices and Systems
One of the most persistent challenges in edge computing within the healthcare field is getting diverse medical systems and devices to communicate effectively with each other and share data seamlessly. For example, when a patient moves from the emergency room to intensive care, their vital signs data needs to flow smoothly between different monitoring systems, integrate with their electronic health record, and connect with clinical decision support tools—all in real time. Despite this critical need, many medical device manufacturers still use their own proprietary methods for data exchange, creating significant integration challenges.
Interoperability challenges can be even more significant when data needs to be shared between different healthcare facilities or when new technologies like remote patient monitoring devices are incorporated. The healthcare industry continues to push for broader adoption of universal standards to help make edge computing deployments more attainable, practical, and efficient.
Thermal Management and Device Durability
In healthcare settings, edge computing devices must be designed for frequent sanitization and carefully balance processing power with thermal constraints. Medical facilities must maintain strict temperature and air quality controls, and cooling solutions traditionally used for data centers may be impractical or disruptive in clinical settings.
Cybersecurity
With sensitive patient data processed and stored across multiple locations rather than in a centralized data center, each edge device can become a potential entry point for cybercriminals. Accordingly, healthcare organizations must implement robust security measures while ensuring they don’t impact the real-time processing capabilities that make edge computing valuable. This includes securing physical access to devices and implementing sophisticated encryption and authentication protocols that can function with minimal latency.
The challenge is further complicated by regulatory requirements like the US Health Insurance Portability and Accountability Act (HIPAA), which mandates specific security standards for protecting patient health information. Organizations must also contend with the need to regularly update security protocols across numerous edge devices while maintaining continuous operation in critical care settings.
Edge Computing in Healthcare Use Cases
The reimagined world of healthcare is driven and enabled by a proliferation of exciting new mobile and point-of-care edge computing devices and deployments. Principle among these advances are the optimization of medical imaging and diagnostic processes and the improvement of patient outcomes through real-time monitoring and analysis.
Optimizing Medical Imaging and Diagnostics
High-performance edge computing combined with high-bandwidth private 5G connectivity can enable near-real-time processing and distributed access to data-intensive medical imaging workloads. As a result, high-resolution ultrasounds, MRIs, and other imaging files are quickly accessible to radiologists and other clinicians.
Data generated across all imaging devices can be combined into a single primary file to provide clinicians with a highly granular, comprehensive view of patient conditions. Additionally, healthcare professionals can leverage advanced AI and predictive analytics to help inform many diagnoses and treatment decisions with greater speed and accuracy.
Improving Outcomes through Remote Patient Monitoring and Analysis
In a smart hospital, patient monitors are constantly generating high volumes of data. Smart hospitals can capture patient data through sensors and devices and then apply advanced AI analytics to uncover clinical insights. Telehealth systems enable real-time communication between nurses and patients. Observation solutions and digital dashboards allow patient conditions to be monitored remotely by care teams, and dynamic alerting helps keep patients safe.
Another fast-emerging trend in smart hospitals is the use of genomics to inform test results in a practice known as precision medicine. High-performance edge computing accelerates clinical workflows, and robotics in large lab systems can help enable lab automation at scale, processing more samples faster with the help of fewer employees.
The Future of Edge Computing in Healthcare
It’s a new world for health systems and providers, one driven and enabled in part by edge computing and the proliferation of IoT devices and AI-powered analysis. As we’ve seen, the abundance of data can help professionals diagnose patients quickly and accurately while improving outcomes and operational efficiency. The impact moving forward goes beyond improvements in care; AI could result in a net savings of US$360 billion in healthcare spending per year1.
Edge computing and edge analytics will only grow in their impact as they bring new opportunities to grow operational, clinical, and financial value across the care continuum. As healthcare continues its digital transformation, understanding the strategic role of edge computing—and implementing innovations successfully—is essential for organizations aiming to deliver superior patient care while managing costs and complexity.