Technologies such as low-latency 5G wireless capability and robotics are bringing innovation and cost reduction to healthcare.
As consumers and patients, it’s easy to see: The healthcare industry is challenged by high costs and limited access. But advances in 5G, the next generation of wireless connectivity, are poised to help address both issues.
In the U.S., 18% of gross domestic product is dedicated to healthcare. Even for those who can afford healthcare, finding medical providers may be challenging. The Association of American Medical Colleges predicts that by 2030 the U.S. will face a shortage of between 40,800 to 104,900 physicians.
The new 5G wireless standard, in tandem with advances in artificial intelligence (AI) and edge computing architectures, can reduce healthcare costs while broadening access to more patients. This will come from the adoption of telemedicine, telesurgery and expanded home healthcare.
In the U.S., 18% of gross domestic product is dedicated to healthcare.
The new 5G wireless standard, in tandem with advances in AI and edge computing, can reduce healthcare costs.
Imagine a patient with a chronic neurological disease that is difficult to diagnose. The patient has undergone several tests, including a variety of imaging diagnostics, but is too sick to travel to meet an expert diagnostician thousands of miles away. Physicians consult over the phone, but without the ability to see the diagnostic images, experts cannot identify the root cause of the pathology. Fortunately in these scenarios, 5G network infrastructureprovides the bandwidth and low latency needed to transmit large image and video files, while participants collaborate via videoconferencing.
This is just one example of telemedicine, which enables remote healthcare providers to enlist telecommunication technologies in patient care. With the ability to share imaging data in real time, medical professionals can consult with geographically dispersed patients and peers. 5G network infrastructure is essential for long-distance telemedicine; but within a campus, physicians could take advantage of Wi-Fi 6, which provides almost 10 Gbps speeds and improved support for multiple devices using the same network.
Another advantage of multi-person collaboration via telecommunications is that a diverse healthcare team can participate in medical consultations. Complicated medical issues often benefit from multiple medical specialists, case workers, translators, medical advocates and others to formulate a healthcare plan for a patient.
Rural areas could especially benefit from telemedicine, but 5G is most efficiently deployed in high-density areas because 5G base stations need to be in close proximity to one another as compared with previous generation base stations. One option for rural areas is to deploy frequency-divided (FDD) spectrum 5G, which has low latency but less capacity than standard 5G.
In addition to collaborative telemedicine between professionals, 5G enables advances in telesurgery.
The combination of low-latency 5G network infrastructure and advances in robotics also enables important developments in surgical procedures, whereby a surgeon can remotely control robotic devices that perform procedures on patients. Telesurgery is in early stages of development, but surgeries have been performed this way.
A surgeon performed telesurgery on an animal with these technologies, according to the U.K.-based Independent. The surgery to remove the liver of a laboratory test animal was performed using a robotic arm in a surgery unit 30 miles from the surgeon. Telesurgery has also been used on humans. China Daily reports the first telesurgery on a human brain was performed in Beijing by a surgeon 3,000 kilometers away in Sanya City. The surgeon placed deep brain stimulation implants into a patient with Parkinson's disease.
Telesurgery requires a highly reliable network, especially when surgeons receive haptic, or touch-based, feedback. Researchers note that “the performance of robotic telesurgery largely depends on the network performance in terms of latency, jitter and packet loss, especially when the telesurgical system is equipped with haptic feedback. This imposes significant challenges to design a reliable and secure but cost-effective communication solution.”
5G is enabling new ways of delivering healthcare outside medical facilities, too.
Healthcare for the elderly, children, and the chronically ill are well suited to wireless technology. 5G-enabled devices allow healthcare providers and aides to monitor daily activities, track location and detect falls as well as monitor medication intake and detect changes in medical status.
This kind of in-home healthcare depends on collecting data from personalized medical devices, including wearables. By 2023, 5 million individuals will use health-monitoring devices, according to some estimates. While improving the health of individuals, this growing market segment may help drive down the cost of healthcare. “The ‘consumerization’ of healthcare and rising data availability could be on the cusp of reducing healthcare spending,” predicts Mary Meeker, partner at venture capital firm Kleiner Perkins. Both consumerization and data collection benefit from 5G’s high bandwidth and low latency networking.
In-home healthcare monitoring can use edge computing architectures, such as having an intermediate data collection, storage and pre-processing device on site. This kind of configuration, known as fog architecture, reduces the amount of data that must be sent to the cloud or an on-premises data center. For example, an edge device might collect data from multiple wearables as well as in-home smart speakers or video monitors. AI on the edge devices can analyze the raw data and send summary information to the cloud along with information on anomalous events, such as a sudden change in heart rate or a drop in blood sugar levels.
As promising as telemedicine, telesurgery and in-home monitoring are, their full potential may not be realized without addressing regulation and implementation issues.
One of the challenges with telemedicine is that existing regulations are not structured to support it. “Problems remain for telehealth and telemedicine adoption, because of existing state regulations regarding the patient–doctor relationship and licensing. This has limited the use of telemedicine, particularly in multistate scenarios that involve a patient at home or in a nonoffice situation, when a patient may be using a mobile device.”
Advances in FDD 5G and related adaptations to improve rural access to 5G are important to support healthcare delivery to rural areas. Healthcare trends indicate “rural healthcare providers and hospitals will continue to turn to leveraging new technology as they experience population loss. Technologies, such as telehealth and telemedicine, and consumer health wearables or smartphones, can enable rural-based care systems to consolidate specialty care services and referrals as ways to survive and grow in an evolving market.”
Another area that requires the attention of governments is the protection of personal healthcare data while enabling advances in AI and home healthcare. The most significant advances in AI in the past decade are due, in part, to training machine learning models with large amounts of data. Finding the right balance of protecting privacy with allowing machine learning engineers to use medical data to improve the quality of diagnostic AI will likely require deliberation and debate.
5G network infrastructure enables advances in healthcare delivery, including the way surgeries are performed and it will directly affect millions of individuals who will use home healthcare monitoring in the near future. As with many disruptive technologies, governments and medical professionals will need to consider appropriate regulations to promote technology while protecting the interests of patients.
Dan Sullivan is a software architect specializing in streaming analytics, machine learning and cloud computing. Sullivan is the author of NoSQL for Mere Mortals and several LinkedIn Learning courses on databases, data science and machine learning.