Medical tech trends accelerated by COVID-19
M3 Global Newsdesk Aug 02, 2020
The year 2020 is already halfway gone—and most of us will be glad to see it go altogether. Still, while COVID-19 has killed many people, put millions out of work, and affected the economy, it has also forced upon us innovations and processes that will make things better in the future.
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What innovations and processes, you ask? Here are five emerging healthcare technology trends that may arrive sooner rather than later, thanks in part to coronavirus.
You’ve probably read or heard the word “blockchain” before...but what is it exactly? Simply put, it’s a technology that provides a secure way to track transactions. “More specifically, blockchain is a shared, immutable record of peer-to-peer transactions built from linked transaction blocks and stored in a digital ledger,” according to a white paper by Deloitte Consulting LLP.
“Blockchain is excellent at tracking the chain of custody of an item from manufacturer to the hospital and then eventually to its end use—the patient. It gives visibility into item usage and movement,” John Kupice, CEO of H-Source, explained to Supply & Demand Chain Executive magazine. “Blockchain has the potential to streamline the supply chain and facilitate FDA recall and drug track-and-trace requirements, as well as increase efficiency, reduce waste and reduce risk profiles.”
Besides keeping close track of supplies, blockchain can provide a number of other important functions in healthcare—notably, a secure, reliable database of patient health information that’s commonly shared by a wide range of entities, such as physician practices, hospital systems, insurers, government agencies, and others. There are still a number of barriers to this, but if (or rather when) it is implemented, it would save everyone enormous amounts of time and prevent a host of errors.
In addition, a portion of this data could be made available to provide a rich set of standardised, non-patient identifiable information for use in widescale clinical studies.
While blockchain would provide one mechanism for data sharing, the process of data sharing itself is a powerful health tech trend. In fact, data sharing is government-mandated by the 21st Century Cures Act, which was passed in December 2016 and stipulated new data-sharing rules for electronic health records (EHR) systems.
These rules, which have only recently been finalised, “promote standardised language and application programming interfaces (APIs) that encourage technical interoperability across EHR systems,” according to a 2020 health trends report from Stanford Medicine. The rules also widely expand patients’ access to their own medical records and limit information-blocking practices.
“For an industry that has long struggled with low levels of information sharing and poor interoperability across its technology systems, in 2020 we expect to see the final rules create a seismic shift in how health care stakeholders share and interact with digital medical records,” wrote the authors of the Stanford report.
Another use of data sharing is for creating “Big Data,” which can help predict specific illnesses both in individuals and in large populations. Here’s just one example: Researchers used EHR data to predict the early risk of chronic kidney disease in patients with diabetes. “The predictive power of our real world data-based model for diabetes-related chronic kidney disease outperforms published algorithms, which were derived from clinical study data,” the study authors wrote.
Artificial intelligence (AI) is already being used in medicine. During the COVID-19 pandemic, one of the things that has helped, in a small way, to reduce demands on the healthcare workforce is the use of chatbots. Now found on health insurance company websites (as well as shopping sites, fast-food sites, and many others), chatbots are AI-powered applications that can simulate a natural human conversation to provide patient (or customer) assistance.
Besides simple chatbots, AI applications have been developed to perform all sorts of high-level tasks, such as scanning medical images to identify potential cancers and tumors. AI is also being used for analysing data in pathology, lab tests, genetics, and other clinical areas to accelerate processing and help facilitate decision-making and diagnoses.
It’s important to note that AI itself doesn’t make the diagnosis. Rather, it helps the clinician to make a more informed diagnosis. To underscore this point, some authors from the National Academy of Medicine suggested the term “augmented intelligence” in a publication about AI in healthcare.
“The opportunity for augmenting human cognition is vast, from supporting clinicians with less training in performing tasks currently limited to specialists to filtering out normal or low-acuity clinical cases so specialists can work at the top of their licensure,” wrote the National Academy of Medicine authors. “Additionally, AI could help humans reduce medical error due to cognitive limits, inattention, micro-aggression, or fatigue. In the case of surgery, it might offer capabilities that are not humanly possible.”
Still, many questions must still be answered about the implementation of artificial intelligence, “including what role AI should have in the patient-doctor relationship, ethical considerations, and, more practically, how it can best alleviate clinical practice burdens,” noted the authors of the Stanford Medicine report.
FitBit and Apple Watch are two well-known wearable healthcare monitors (“wearables”) that can tell you your activity level, your heart rate, or (in the Apple Watch) warn you of signs of atrial fibrillation.
But, many other wearables and biosensors are now available or coming soon, like a contact lens that monitors blood glucose levels in people with diabetes or a “smart” ring that can detect COVID-19 symptoms up to 3 days in advance. Wearables could be used by physicians to remotely monitor patients’ health, helping to provide more data on a patient’s condition or earlier detection of illness or health emergency.
Physicians themselves are early adopters to this technology and many use the data from their devices to make personal healthcare decisions. These findings suggest that physicians are on their way to implementing wearables on a larger scale with their patients.
All this technology comes at a cost—and not just the cost of developing and implementing it, but the data demands on bandwidth. The answer to better data communication: 5G. What exactly is 5G? It’s fifth-generation wireless network technology that’s up to 10 times faster than the existing 4G LTE network. 5G can also handle more connected devices at the same time, and can make connecting with servers and cloud platforms faster and easier.
As doctors around the country have now experienced, telemedicine works best with fast and reliable internet service. 5G will deliver on the long-awaited promise of more effective, reliable, and user-friendly telemedicine.
On 5G, you can better send and receive large image files—like a high-def 3D MRI scan—to easily share with a specialist for a remote consultation. 5G will also facilitate the delivery of treatments through virtual reality, and make remote patient monitoring easier and more reliable.
Although it will take several years for a nationwide 5G infrastructure to be established in the United States, 5G networks are now being rolled out in a number of cities and regions. Already in 2020, several Android smartphone manufacturers have released 5G-enabled devices, and Apple is expected to release a 5G iPhone in the fall.
This story is contributed by John Murphy and is a part of our Global Content Initiative, where we feature selected stories from our Global network which we believe would be most useful and informative to our doctor members.
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