Svitlana Golovnia Nov 3, 2021 12:02:15 PM 10 min read

3 Technologies Dictating Healthcare Trends of Tomorrow

Healthcare trends are strongly impacted by technology trends. Each year, Gartner reveals its predictions for the top twelve most influential technologies. Here, we'll look at three of those and examine their implications for preventative and diagnostic healthcare.


Internet of Behaviors

 

As the Internet of Things makes its way through the Trough of Disillusionment, Garter has identified a new technology trend that’s influencing the healthcare industry: the Internet of Behaviors (IoB). The idea was first introduced in 2012 by Göte Nyman, a Professor at University of Helsinki, who worked on Psychology of Evolving Media and Technology. The IoB captures what Gartner calls the “digital dust” of our lives and attempts to understand the data collected from users’ online activity from a behavioral psychology perspective “to see intentions and to know better what is about to happen in the connected world”.

 

Going a step further, the IoB is not only about analyzing behavior to predict what will follow, but also about detecting which psychological variables to influence to change the IoB’s projected outcome.

 

 conceptual_idea as a concept of technologies dictating healthcare trends

 

As we move from hospital treatment to sickness prevention, personalized intervention and preventative care (here is a great conversation about it with Mark Wehde, the Chair of the Mayo Clinic division of engineering) will be more and more powered by the IoB. Gartner predicts that 40% of people globally (more than three billion people) will have their behavior tracked through the IoB by 2023, and that by the end of 2025, more than half of the world’s population will be subject to at least one IoB program, whether it be commercial or governmental. Already in 2018, according to the Government & Academic Omnibus Survey assessing wearable use, 47.7% of adults were willing to share their data with a health insurer, and 76.3% - with their healthcare provider.


John Hancock became the first U.S. life insurance company to fully embrace behavioral-based wellness. Their Vitality PLUS program lets members save up to 25% off their premium for making healthy choices, and earn rewards for exercising, buying healthy foods and meditating. Today, organizations ranging from Blue Cross Blue Shield, to Aetna, to Kaiser Permanente partner with fitness tracker companies to encourage more active lifestyles among their members.

According to MunichRE, with wearables, insurers can play a pivotal role in motivating and nudging their policyholders in the right direction. For example, showing personalized messages on the wearable device can assist individuals with staying on top of their health goals and alert the customer and insurer if there are potential adverse signs. Another flavor of this approach is  the nudge engine we built for Humana, which smartly reminds people to get regular checkups and preventative treatments by email, text message, or however they prefer to communicate.

 

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We “quantify” ourselves with sleep and fitness trackers out of both curiosity and desire to make a manageable but meaningful impact on our health, but we never think about our health more  than when it fails us (or we fail it for way too long - depending on how you think about it). So let’s talk about what’s changing in the realm of diagnostics and care delivery.

 

Related: Transforming The Healthcare Construct

 

Distributed Cloud and Edge Computing as healthcare trends

cloud_files as a concept of healthcare trends

The more data we generate, the more acute the problem of processing becomes. When it comes to health data––say, a patient’s heart and respiratory metrics in a context of remote care ––the standard for precision is high. Seconds (let alone a whole minute) it might take to process data somewhere else before displaying it to a doctor can be the difference in saving a patient’s life. Speed becomes the name of the game.

 

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.

To be useful in the form of wearable devices and streamlined services, either in the hospital wards or as a form of remote care, data needs to be processed and analyzed with real-time insights, closer to the location of its generation, and transferred to the cloud or an on-premises network if necessary.

The pandemic sped up many developments in the healthcare industry, and moving health data to the cloud is one of them. Cloud-based solutions for healthcare data storage allow individuals to own and control the single source of truth for their health and medical data, collected from doctors’ offices, hospitals, pharmacies and even wearable devices, which they may choose to share with providers—even granting them permission to add or retrieve data as needed.

Cloud computing is not a new thing for the healthcare industry, but distributed cloud is. Distributed cloud is a public cloud computing service that lets you run public cloud infrastructure in multiple different locations - not only on your cloud provider's infrastructure but on premises, in other cloud providers’ data centers, or in third-party data centers or colocation centers - and manage everything from a single control plane. Distributed cloud is also defined as a tech trend by Gartner for 2021. It helps deliver “multiexperience” to patients - a frictionless customer experience across websites, apps, and modalities of voice, touch, and text, regardless of the channel. Gartner predicts that by 2023, more than 25% of mobile apps, progressive web apps, and conversational apps at large enterprises will be built and/or run through a multiexperience platform.

Distributed cloud provides the ideal foundation for edge computing - running servers and applications closer to where data is created: wearables, medical equipment, and the patients themselves. 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 edge also provides for greater security. For example, sending data to an edge device will give any potential attackers less time to launch an attack (compared to the cloud) simply because the latency is lower. This also means that edge networks are much more reliable as they do not have a single point of failure. It supports telehealth, from real-time respiratory metrics to the next level of complexity of remote surgeries.

Edge computing creates a fertile environment to deploy federated learning for IoMT (Internet of Medical Things). Federated learning is a method for training neural networks across many devices where the data stays protected at its location while anonymously contributing to machine learning algorithms. It allows medical institutions to collaborate on training models without sharing patient data so that they can meet the requirements of data privacy protection and the Health Insurance Portability and Accountability Act (HIPAA). For example, Dr Ittai Dayan, a Co-Founder of our client, Rhino Health, recently co-authored a research published in Nature Medicine that used federated learning to predict how much extra oxygen a Covid-19 patient may need in the first days of hospital care, using data from 20 hospitals across four continents.

 

Healthcare Trends · Conclusions

 

medicine as a concept of healthcare trends

 

As we produce more health-related data, its processing and contribution to training models for machine learning in the healthcare domain starts to happen closer to the point of data generation. A big part of this tendency reflects the demand for health data privacy & ownership, as well as the bigger trend for personal data ownership that is already causing an upheaval in the digital advertising industry. The ones who have access to our health data (providers, insurers, etc) can do progressively more with it, like nudging us into behaviors that are better for our health, on more platforms than ever by leveraging multiexperience. While it sounds idyllic, it also amplifies the concerns about whether our data is being used safely and ethically. We will likely see more use cases for blockchain technology dealing with healthcare data and, hopefully, solutions designed to respond to the threat of quantum computing cracking the encryptions that protect so much of our personal information today. 

 

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Svitlana Golovnia

Rapid Prototyping of emerging technology at SF AppWorks, Svitlana Golovnia connects battle-tested product people and technologists with forward-thinking entrepreneurs. She’s interested in biotech and digital health care and likes working with builders who believe in the role of technology in improving people's lives.

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