How Edge Computing is Driving Advancements in Healthcare Analytics

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Cloudticity, L.L.C.

New technologies are not just transforming healthcare, they are completely revolutionizing it. The last few decades have seen amazing innovations that are improving patient care.

These include genetically targeted medication, robotically assisted surgery, machine learning, artificial intelligence (AI), and a movement of computing workloads to the cloud.

New trends like the Internet of Things and remote patient monitoring are promising to improve patient outcomes even more.

More recent healthcare innovation is called “edge technology.” It’s related to cloud services, and the aim is to improve healthcare delivery by improving the speed of processing data. To put it simply, edge computing brings data processing close to the place where the data originates.

Let’s investigate some of how edge computing is allowing healthcare providers to develop a highly intelligent system with advanced analytics that can vastly improve patient care.

What is Edge Computing?

The term “edge computing” is often unfamiliar to many, including those that are fairly familiar with computer science. This new technology is an outgrowth of the cloud.

The rapid growth of the cloud gave rise to major concerns related to losing the ability to process data locally. Let’s look deeper into how we arrived at this point.

Development of the Cloud

The evolution of computing has been rapid and dynamic. In the early days, where all computing power needed to be located directly within the computing device. Then, organizations used clusters of powerful servers that were linked to individual workstations.

For many years, there was a mix of locally powerful devices and even more capable servers that could be a distance away.

Finally, we arrived at cloud computing. While computers themselves are capable of running vital local operations, immensely powerful applications run in data centers throughout the world. 

Benefits of the Cloud for Healthcare Professionals

Cloud computing revolutionized the healthcare industry by allowing huge amounts of records to be stored and highly advanced technologies to become available to organizations of all different sizes. These resources can be scaled larger or smaller as demands change.

Cloud Growing Pains: Data Transmission Speeds

While the cloud can accomplish amazing feats for healthcare facilities, the rapid growth gave rise to a few problems. These mostly relate to the fact that usually, a cloud data center is located often far away from the actual place where the data is being used.

This is because, to make them economical, they must be built in areas where land and electricity are fairly cheap, and that’s not usually deep within major urban areas.


This gives rise to the problem of latency. Even at the relatively high speed that’s been able to be achieved in the modern internet, there is still a fairly large lag time between the time that data is transmitted to and received at the data center, and vice versa.

While some non-intensive uses of the cloud may result in a mere annoyance, for others, they can have an impact on the ability to provide healthcare at a quality level, while still taking advantage of these innovations.


As the number of devices used increases, so does the amount of bandwidth used, which compounds the latency problem. Bandwidth limitations may cause medical devices to become disconnected from the network, which can cause a major interruption in care.


On top of the issues of latency and bandwidth, there’s the problem of network congestion. The sheer amount of patient data that’s being collected by healthcare organizations and processed in the cloud is staggering. Transmitting and receiving large amounts of data causes issues in reliability and resiliency.

Solution: Edge Computing

Cloud providers such as Amazon Web Services (AWS), Google Cloud Platform (GCP) and Microsoft Azure developed a solution to this problem: distributing system elements much closer to where the data is being used and generated.

Edge Computing Capabilities

By bringing servers and processing power closer to the data, latency problems are heavily mitigated. Bandwidth and congestion are also eased due to the multiple avenues for connection that may not exist when data needs to travel a longer distance.

Edge computing is a broad concept, and the ways that a system can be built are numerous indeed. This gives modern health systems the flexibility to set up a system that works for them from the exam room to the operating room and even beyond to wherever the patient is at any given time.

How does Edge Computing Work?

This broad term encompasses several different components. Let’s break down what some of these are, and how they fit together to form healthcare edge computing.

Edge Devices

At the local end are small edge devices that connect to an organization’s network or the internet. These are things such as:

  • Wearable devices like watches, glucose monitors, heart rate monitors, and more.
  • Wireless or connected diagnostic devices like blood oxygen sensors, thermometers, scales, and others
  • Lab equipment for testing blood, fluid, and tissues
  • Cameras - diagnostic and for security
  • Specialized equipment for carrying out procedures like colonoscopy, endoscopy, and more.
  • Tablet computers for making patient observations and issuing instructions to nurses
  • Smartphones for professional use
  • Door sensors for security and preservation of sterile environments
  • Environmental controls for heating, ventilation, and air conditioning (HVAC) and pathogen detection
  • A host of other devices that exist and are currently being developed


These servers enable network communication. They also handle some processing. They are also essential for security, by providing a firewall to unwanted intrusions.


Devices that connect networks like the LAN or WAN, or to the internet.


Central processing units (CPUs), graphics processing units (GPUs), and memory. These are the workhorses of the computing workload. 


When you have an edge location, you’ll need clusters of servers to run all the applications.


Each node is an essential part of edge computing. When people talk about nodes, they refer to any of these components: devices, gateways, servers, etc. 

Edge Hardware: Rugged and Dependable

A data center is specially located in a location that ensures stable operations. There might be multiple power sources, such as electricity from the grid; solar, solar storage batteries; and a diesel or gas-powered emergency generator.

Data centers are hardened against cyber and physical attacks. They also have advanced fire suppression systems. They are housed in buildings made to stand up against all the elements.

Edge computing is a bit different. The whole point of the endeavor is to bring advanced processing closer to the point of data origin. This may mean that the clusters of servers and processors need to be placed in more vulnerable locations. For this reason, edge computing hardware is built for the task.

Here are a few ways that your edge cluster differs from a cloud data center:

Smaller Form Factor

Data centers for the cloud may be enormous facilities located in areas where land is extremely cheap. Edge clusters will often need to fit in small areas that were not purpose-built to house servers. 

Resistance to the Elements

Edge computing brings extreme levels of analytics to remote locations. This may mean that they need to be located in a harsh environment like a battlefield hospital, a first aid station at an oil platform at sea, or a wilderness aid station. These environments can be dusty, dirty, and subject to extreme temperatures or moisture.

Many edge platforms are built for these specific applications. Some applications have even seen them placed in watertight compartments under water. Recently, a proof-of-concept edge device was placed on the International Space Station for testing. Some day, edge computing may help power a clinic on mars!

Multiple Power Sources

In remote locations, edge platforms need to be able to be powered in multiple ways. They may need to perform intense workloads powered by batteries, the sun, or the grid. The delicate electronics inside need protection from voltage irregularities or surges.

Vibration and Shock Resistance

As we’ll explore below, one use case for edge computing is onboard an ambulance. Healthcare organizations like the Orbis Flying Eye Hospital may someday use edge computing to treat their most difficult cases of eye disease and damage as they fly globally. 

Computing components are often extremely delicate, so the physical architecture of edge components needs to build in shock and vibration dampening to ensure continued error-free operation.

Physical and Cybersecurity

Dealing with Protected health information is a serious undertaking. The benefits of edge computing would be quickly negated if they were easy targets of security breaches.

Even if an edge computing location lacks the fortress-like security of a data center, it still needs to resist and alarm in the event of a physical attack. It also needs to be equipped with the latest in virus, malware, and intrusion detection.

Edge Computing: Healthcare-Specific Applications and Benefits

The possibilities of edge computing in healthcare are seemingly limitless. These support faster diagnosis and vastly improved clinical decision support. Let’s look at some of these exciting innovations that are being found worldwide as healthcare systems adopt edge computing.

Connected Ambulances

5G mobile connectivity has helped to fuel some of the innovations of edge computing. An ambulance can be equipped with a 5G data link that can be set up to communicate directly with the emergency department at a local hospital. 

Currently, EMTs are often limited to calling out data over a radio, which limits the scope of what can be transmitted. It usually concerns easy-to-spot vitals like blood oxygen levels, respiration rates, blood pressure or general observations.

A connected ambulance could help EMTs begin care faster, potentially saving lives in the process.

Miniature and Wearable Devices

It’s no secret that most of us procrastinate or avoid our health monitoring altogether. Doctors have long depended on patients with hypertension to monitor their blood pressure and communicate results. Or, they need diabetic patients to routinely check their blood glucose levels and report back trends in results.

The fact is that most people get busy, distracted, and anxious about their condition, and avoid checking these metrics. This can be avoided by encouraging the patient to wear a tiny, unobtrusive mobile device that can not only monitor, but treat as well.

This has become a reality with devices from companies like Dexcom, which are simply applied to the arm, and can record glucose levels throughout the day without any effort on the part of the patient.

Recent developments have even included insulin pumps that can automatically administer the exact beneficial dose tailored to the patient's predicted glucose levels at various times.

Hypertension checks still require some action on the part of the patient for now, as integration into wearables like watches hasn’t been successful as of yet. However, it’s extremely easy for results to be transmitted with connected devices that can automatically send this information to the patient’s doctor.

In turn, automated routines can be set up to alert the patient to trends and recommend corrective action like a change in medication or diet.

There are many more forms of devices that are currently being developed to aid in chronic disease management. Some of these include monitors for:

  • Sleep
  • Falls
  • Excretory abnormalities
  • Body Temperature
  • Medication compliance
  • And many more

Hospital Monitoring

The average hospital bed and all the other systems found in a patient room can now monitor patients with a level of precision and thoroughness never before possible. All of these minute changes and trends in patient data can often give clues into the effectiveness of treatment, or even the cause of systems.

This is a primary example of the sheer volume of data potentially causing issues in latency, bandwidth, and congestion. Edge computing enables accurate diagnosis by sending all of this data to a closer point at a faster speed, with no loss.

Barriers to Edge Computing

While the promise of edge computing enabling healthcare innovation is a positive development, it won’t come overnight. There are a few barriers to widespread adoption. In the coming decade, it’s reasonable to expect that some of these will begin to give way to wider and wider use of edge computing in medical services.

Cost of Implementation:

As we discussed earlier, there are many different components of an edge computing system that need to be built, moved, or purchased to make the system work. Some esoteric applications may require custom solutions that can’t be simply purchased off the shelf.

The cost of building an edge computing system is sometimes beyond the reach of even larger organizations. It’s often an idea that is placed on the back burner to revisit at a future time. 

The good news is that the larger cloud providers are beginning to integrate edge computing capability into their offerings. It’s advisable for healthcare systems to at least discuss the topic with their sales and business representatives.

There may be ways of bringing the benefits of edge computing to bear on their data processing that the IT team hadn’t considered, all at a lower cost than they predicted.

Security Concerns

As cloud adoption has increased, so too have security concerns. The reality is that major cloud providers like Azure or AWS are highly secure, as long as they are configured properly. While the edge should share many of these secure traits, there are some issues to consider.

One is the sheer number of devices that might be connected to an edge computing remote patient monitoring solution like a blood pressure cuff, a wearable meter to measure blood glucose levels, and many more. The proliferation of devices can introduce vulnerabilities that didn’t previously exist.

What are the Analytics Made Possible by Edge Computing?

The medical data points that are generated by patient care and monitoring are now more numerous than ever. It’s only through advanced life science technologies like artificial intelligence and machine learning that the data can actually be anal

Speed matters

Achieving an accurate diagnosis as quickly as possible is key to facilitating the best possible outcomes. Edge computing allows powerful technologies like artificial intelligence and machine learning to bear on complex data from CT scans, MRIs, X-rays, and more.

While radiologists still play an important role in care, AI can potentially compare a patient’s scans with millions of others in seconds, helping to spot problems faster than ever.

It’s not just X-Rays and CT scans. Wearable devices and advanced measurement tools can help detect illnesses earlier

Bringing High-tech Care to Rural Areas

How edge computing combines the power of the cloud with the speed and low-latency of on-premises computing is bringing the latest innovations to places that are far from major medical centers.

Even locations with unreliable internet can still leverage the massive power of AI and machine learning through edge computing. This is because as data is collected, some of it is processed locally, and when the connection allows it, it can be sent to the cloud for more powerful actions to be taken.

Powering Telemedicine

The COVID-19 pandemic accelerated the use of telemedicine. Practitioners and healthcare companies saw the benefit of providing patient care remotely during the pandemic, but beyond that as well. 

Edge computing can enable better care and decision-making when the patient isn’t directly in the examination room. Whether it is through simple devices like smartwatches, or complex remote care platforms, the ability to perform workloads with low latency is essential to making telemedicine just as good as in-person medicine.

Healthcare analytics are at the heart of raising the standard of care that’s found in telemedicine.

Doctors need data to drive care decisions, and edge computing helps to provide that through machine learning and artificial intelligence.

The Potential Advantages of Edge Computing

The healthcare industry is just beginning to see some of the benefits that can be reaped by bringing data processing closer. Here are just a few of the benefits.

Cost Savings

Healthcare costs have ballooned over the last several decades. Obviously, there are many reasons for this. However, one of the drivers is the availability of advanced technologies.

A recent study by the McKinsey consulting group published in the New England Journal of Medicine found that $300 in healthcare expenses could be saved through the kind of advanced analytics made practical through edge computing.


Regulatory compliance has been a huge issue with the growth of the cloud. In some instances, sensitive and private health information (PHI) must be kept locally to comply with regulations.

An example of this can be found in Germany, where certain data must stay within the country’s borders.

With edge products, the data that needs to stay local remains on-premises, but can still be acted upon with edge-connected servers and processors.


While it is true that there are concerns about the security at the edge due to a large number of devices, there is a flip side to this coin as well. The shortened time and distance that data needs to travel can reduce the possibility of interception and hacking by cybercriminals. 

It’s not just the travel time and distance that are improved from a security standpoint. When sensitive data is stored locally, the risk is greatly reduced as it’s not being transmitted over the network at all.

Edge solutions from the major Cloud providers take advantage of the most current encryption methods. They also invest vast sums in IT Cybersecurity teams to monitor the evolving threat matrix and issue patches and advisories as necessary

Edge Computing: Bringing Advanced Healthcare Analytics To Every Corner of the World

While healthcare technology has advanced by leaps and bounds, many of the advances aren’t available everywhere due to the limitations of cloud technology.

As edge computing continues to be adopted and developed, we may soon be able to receive the care of the leading medical centers of the world, without ever leaving home.

Want to learn how Cloudticity can help you adopt edge computing? Schedule a free consultation today.


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