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This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review's editorial staff.

Transforming health care at the edge

Edge computing is reshaping health care by bringing big data processing and storage closer to the source, to support game-changing technologies such as the internet of things, artificial intelligence, and robotics.

Before 2020, digital transformation in health care was frustratingly slow, even as providers dreamed of boosting efficiency, increasing flexibility, and reining in spiraling costs. In a risk-averse industry known for lagging behind technology trends, doctors still had not fully adopted electronic health records, for example. And the use of digital tools for diagnosis, tracking, and treatment was emerging but limited. Yet, health-care data often needs to be accessed by collaborative teams across institutions, sometimes around the globe. System downtime or slow app performance is not an option.

These challenges were highlighted during the covid-19 pandemic. Not surprisingly, the health-care industry has accelerated its efforts to embrace digital over the past year, as well as experiment with exploding trends including telehealth, patient-generated health data, and remote surgery. These efforts, in turn, have evolved and expanded thanks to improvements in advanced technologies, including the internet of things, artificial intelligence, and robotics. The global market for connected medical devices, for instance, is expected to swell to $158 billion in 2022, up from $41 billion in 2017.

“The real-time feedback loop required for things like remote monitoring of a patient’s heart and respiratory metrics is only possible with something like edge computing.”
Arun Mirchandani, Executive Advisor on Health-Care Digital Transformation

To scale virtual patient services, manage medical devices, and support smart hospital applications, modern health systems must handle massive data sets closer to the data-gathering devices—to reduce the delay in the transfer of data, called latency, and enable real-time decision-making, says Arun Mirchandani, an advisor on health-care digital transformation. Whether it's on a health worker’s tablet, a wearable device, an ingestible sensor, or a mobile app, computing at the “edge” of the network is essential for speed, scale, and performance.

Medical data growth: A snapshot
10 to 15
connected devices are in use per US hospital bed.
3 million
data points are generated by the average clinical trial.
of all global stored data is from health care and life sciences.
of data will be generated at the edge by 2025.
Source: Dell Technologies’ Infographic “Edge and IoT Solutions”

Edge computing, through on-site sensors and devices, as well as last-mile edge equipment that connects to those devices, allows data processing and analysis to happen close to the digital interaction. Rather than using centralized cloud or on-premises infrastructure, these distributed tools at the edge offer the same quality of data processing but without latency issues or massive bandwidth use.

“The real-time feedback loop required for things like remote monitoring of a patient’s heart and respiratory metrics is only possible with something like edge computing,” Mirchandani says. “If all that information took several seconds or a minute to get processed somewhere else, it’s useless.”

Opportunities and challenges at the health-care edge

The sky’s the limit when it comes to the opportunities to use edge computing in health care, says Paul Savill, senior vice president of product management and services at technology company Lumen, especially as health systems work to reduce costs by shifting testing and treatment out of hospitals and into clinics, retail locations, and homes.

“A lot of patient care now happens at retail drugstores, whether it is blood work, scans, or other assessments,” Savill says. “With edge computing capabilities and tools, that can now take place on-site, on a real-time basis, so you don’t have to send things to a lab and wait a day or week to get results back.”

The arrival of 5G technology, the new standard for broadband cellular networks, will also drive opportunities, as it works with edge computing tools to support the internet of things and machine learning, adds Mirchandani. “It’s the combination of this super-low-latency network and computing at the edge that will help these powerful new applications take flight,” he says. Take robotic surgeries—it’s crucial for the surgeon to have nearly instant, sub-millisecond sensory feedback. “That’s not possible in any other way than through technologies such as edge computing and 5G,” he says.

“A lot of patient care now happens at retail drugstores. With edge computing capabilities and tools, that can now take place on-site, on a real-time basis, so you don’t have to send things to a lab and wait a day or week to get results back.”
Paul Savill, Senior Vice President, Product Management and Services, Lumen

Data security, however, is a particular challenge for any health-care-related technology because of HIPAA, the US health information privacy law, and other regulations. The real-time data transmission edge computing provides will be under significant scrutiny, Mirchandani explains, which may affect widespread adoption. “There needs to be an almost 100% guarantee that the information you generate from a heart monitor, pulse oximeter, blood glucose monitor, or any other device will not be intercepted or disrupted in any way,” he says.

Still, edge computing technologies, paired with the right security standards and tools, are often more secure and reliable than the on-premises environment a business could implement on its own, Savill points out. “It’s about understanding the entire threat landscape down to the network level.”

Expected benefits from edge computing
The biggest boons for health-care professionals are strengthened cybersecurity, better-running operations, and improved experiences for customers.
Source: IDC’s “Edge Computing: Transforming Healthcare by Increasing Resilience,” sponsored by Lumen, based on a survey that included 101 professionals from health-care organizations

The health-care edge: Not just hype

There is no doubt that health-care is drowning in data: A 2020 Dell survey found that health-care and life sciences data grew almost 900% over the previous two years, with 10 to 15 connected devices at the typical hospital bedside. Big data sets can quickly become overwhelming to manage, label, and share efficiently. To be useful in the form of wearable devices and streamlined services, the data needs to be processed and analyzed with real-time insights, closer to the edge, and transferred to the cloud or an on-premises network if necessary.

That is not simply buzzword-driven hype: covid-19, for example, has laid bare the need for health-care options outside the doctor’s office or hospital. There are hundreds of health-care uses that rely on low-latency, remote, real-time results, from pop-up clinics and cancer-screening centers to patient-monitoring systems including pacemakers and insulin pumps. While some technology applications are still in their early stages, edge computing will ultimately help solve problems that cloud computing cannot.

“In the short term, edge computing will solve thorny health-care challenges around real-time data analytics and speech recognition applications,” says Mirchandani. “But while it is early days, many of the other exciting edge computing use cases and applications are coming as well, especially as systems become more interoperable.”