Gartner defines Edge Computing as a part of a distributed computing topology where information processing is located close to the edge, where things and people produce or consume that information. 

Simply put, edge computing brings computation and data storage closer to the devices which collect the data, rather than relying on a centralized location or on the cloud, both of which risk latency issues. 

Edge Computing was developed to cater to the needs of the exponential growth of IOT devices. And the trend is only going upwards, especially in the healthcare sector. Research shows that IOT in the healthcare market will be worth $534 billion in the next four years alone. 

With the advantages it brings to the table including faster processing time for data, non-reliance on bandwidth availability, and network reliability – all of which can save a life in this field where every second of response time counts, edge computing has proven to have the power to completely transform the way the healthcare industry functions.  

What is driving adoption in the Healthcare Industry? 

Real-time data monitoring to control chronic diseases has proven to be highly effective – combinations of remote monitoring, mobile platforms, and analytics have cut the rate of readmissions of patients suffering from congestive heart failure, diabetes, and blood pressure significantly. This success is propelling the usage of IoT devices and networks in healthcare institutions.  

One of the key benefits of edge computing is that data can be analyzed and collected with the same speed as while on the cloud, but without the latency issues. This decreases the costs, increases the efficiency and makes for a far better patient experience – bringing healthcare closer to autonomous care, as opposed to automated care, which is what the industry has been aiming for until now.  

Other attractive benefits that are driving the industry to invest in edge computing include the ease of burden to health practitioners, who can stop manually collecting and managing patient data; make healthcare affordable and accessible to people who live in rural areas and act as a catalyst for technological advancement in healthcare by making data more accessible than ever before. 

Use cases for edge computing in Healthcare  

  1. Uplifting the Rural Healthcare Sector 

While telemedicine has often been seen as the savior of rural areas where healthcare is often inaccessible, poor connectivity usually makes it just as difficult for patients in these areas to receive the care they need. With the right combination of IOT devices and edge computing, this can be overcome. 

Edge computing companies have developed portable IOT healthcare equipment with the ability to gather, store, generate, and analyze critical patient data without needing to be in constant contact with the internet. Thus, patients with wearable IOT devices can be diagnosed quickly, and the data can be fed into the systems at a later point, when connectivity is re-established. 

  1. Critical Care  

Wearable IOT devices and edge computing will enhance the level of care available for patients with diabetes or congestive heart failure, as they will allow for them to be monitored constantly in real-time. 

Intensive Care Unit sensors detect changes in a person’s condition that must be acted upon immediately, such as closed-loop systems that maintain physiologic homeostasis – the data generated from these systems requires instant analysis and action, with no time for the data to be transferred to the cloud. 

When handling emergencies too, this instantaneous relay of information becomes crucial and edge computing can help transfer information from the ambulance to the hospital in real-time, saving time and providing healthcare workers with the information they need to save lives. 

  1. Supply Chain Management 

Every hospital is a complex web of hardware and software working together to keep people healthy – from the parts of the robots used to perform surgeries to the needles used in immunizing babies, every piece of medical equipment comes down a complicated supply chain, and a disruption in that system would be catastrophic, causing disruption to medical outcomes.  

Sensor-equipped IoT edge devices have the potential to completely change the way this system works to ensure zero errors or glitches. These devices can gather data on usage patterns and use predictive analysis to help determine when the hardware of a certain system might fail, or when stock of a certain crucial medication might run low. Inventory management can become smart RFID tag-based, eliminating time-consuming paperwork and manual ordering. Another example would be the ability to track fleet vehicles equipped with GPS and other sensors so the location of critical shipments can be inferred in real-time.   

  1. Cost-Savings for Healthcare Organizations 

The widespread adoption of IoT devices will enable healthcare facilities to significantly cut their costs in several ways. “Applications like Office Security/Video Surveillance, Smart Building Controls and Financial and Healthcare Analytics can help businesses cut costs by 25% to 35% depending on individual use cases and help organizations to derive greater business value from their data assets,” says Laura Didio, Strategy Analytics Director of Enterprise Research and Consulting. 

Challenges to implementation & the way forward  

Some of the key barriers to the implementation of edge computing include the lack of a proper 5G wireless network system, the interoperability of devices with EHRs, the vast amounts of data that need to be stored at the edge and acceptance by healthcare practitioners. One of the hardest problems to address is selecting the appropriate edge computing tools for different healthcare scenarios – thanks to privacy concerns, it is difficult to deploy open-source software directly into healthcare systems. 

Healthcare professionals need to be informed and encouraged to embrace innovation. Organizations need to bring all their stakeholders to the table to work with experts and make sure the systems can actually play out in real life, based on their specific needs and requirements.