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Fog and Health Care at Home

By Mark Watts

Mark WattsHealth Care can be stressful! “Hey Bob, can you come to my office please?” Bob was not just my employee, but a trusted friend. When Bob arrived, I told/asked him to drive me to the hospital, I was having chest pain! After the emergency room visit, (labs came back negative) the doctor said I should consider leaving that place of work to lower my stress level. I was sent home with a Halter 24-hour heart monitor and a documentation device to track my heart rhythm. I thought to myself, “Is this 12-pound system hanging around my neck the best we can do?” I resigned from that position as my doctor said, “No job is worth dying for.” Bob stayed.

“The future of health care is in the home, we are building the hospital of the future, less inpatient beds and more reaching IoT (Internet of Things) monitoring from home.” This was the proclamation made by a CIO of a large health care system at a health information conference. The logic and compassion of providing care at home as appropriate could control cost and improve patient satisfaction.

I understood some features of system design and the application of new technology in health care, but what magic combination would it take to make this vision a reality. Can we build this much trust?!

  1. Secure data transfer
  2. Trusted IoT monitors and communication systems
  3. Bandwidth (5G)
  4. System training of doctors and nurses (Electric ICU)
  5. Edge (Fog) computing

The term “Edge computing” refers to computing as a distributed paradigm. It brings data storage and compute power closer to the monitoring device or data source where it is most needed. Information is not processed on the cloud filtered through distant data centers; instead, the cloud comes to you. This distribution eliminates lag-time and saves bandwidth.

For example, if an echocardiogram machine in the home is collecting a stream of real time data and notes an abnormal heart rhythm. A report is sent stating an elevated ST wave form based on data received directly from the sensors. The computer performing that action is called an Edge computing device or simply an “edge device.” The product “Report” is the meaningful edge result for the health care organization. Because of this change in data sourcing and management, we will compare the two technologies and examine the benefits each has to offer.

Edge Computing and Real-Time Data Processing

What is edge computing, exactly? To find out, we first need to look at the growth of the Internet of Things (IoT) and IoT devices. Cloud computing revolves around large, centralized servers stored in data centers. After data is created on an end device, that data travels to that central server for processing. This architecture becomes cumbersome for processes that require intensive computations. Latency becomes the main problem here.

Edge computing allows computing resources and application services to be distributed along the communication path, via decentralized computing infrastructure.

Computational needs are more efficiently met when using edge computing. Wherever there is a requirement of collecting data or where a user performs a particular action, it can be completed in real-time. Typically, the two main benefits associated with edge computing are improved performance and reduced operational costs, which are described in brief below.

Improved Performance:

Besides collecting data for transmission to the cloud, edge computing also processes, analyses and performs necessary actions on the collected data locally. Since these processes are completed in milliseconds, it has become essential in optimizing technical data, no matter what the operations may be.

Transferring large quantities of data in real-time in a cost-effective way can be a challenge, primarily when conducted from remote health care sites. This problem is remedied by adding intelligence to devices present at the edge of the network. Edge computing brings analytics capabilities closer to the machine, which cuts out the middleman. This setup provides for less expensive options for optimizing asset performance.

Reducing Operational Costs:

In the cloud computing model, connectivity, data migration, bandwidth, and latency features are expensive. This inefficiency is remedied by edge computing, which has a significantly lower bandwidth requirement and less latency. By applying edge computing, a valuable continuum from the device to the cloud is created, which can handle the massive amounts of data generated. Costly bandwidth additions are no longer required as there is no need to transfer gigabytes of data to the cloud. It also analyses sensitive IoT data within a private network, thereby protecting sensitive data. Enterprises now tend to prefer edge computing. This is because of its optimizable operational performance, address compliance and security protocols, alongside lower costs.

Building Trust: Examples of Edge Computing

The best way to demonstrate the use of this method is through some key edge computing examples. Here are a few scenarios where edge computing is most useful:

Autonomous Vehicles:

Self-driven or AI-powered cars and other vehicles require a massive volume of data from their surroundings to work correctly in real-time. A delay would occur if cloud computing were used.

Streaming Services:

Services like Netflix, Hulu, Amazon Prime, and Disney+ all create a heavy load on network infrastructure. Edge computing helps create a smoother experience via edge caching. This is when popular content is cached in facilities located closer to end-users for easier and quicker access.

Smart Homes:

Like streaming services, the growing popularity of smart homes poses a problem. It is now too much of a network load to rely on conventional cloud computing alone. Processing information closer to the source means less latency and quicker response times in emergency scenarios. Examples include medical teams, fire or police deployment.

Accepting change in health care is not easy. To understand the health care of tomorrow we must teach our doctors and nurses to trust the information they are using to make decisions. To trust the data, they must have confidence that the reports are accurate and timely. To lift the fog of doubt in these remotely generated reports, we may need to explain the source and method of collection. IoT, 5G and edge computing will be the new fax machine.

Bob called me recently to let me know that my replacement at that large for-profit health care provider died of a heart attack in my old office. Health care can be stressful.

Mark Watts is the enterprise imaging director at Fountain Hills Medical Center.

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