How the Internet of Things could make healthcare more proactive
Internet of Things

How the Internet of Things could make healthcare more proactive

It’s widely accepted that living healthy means eating well and getting plenty of exercise, but quantifying the effects can be a challenge and even dealing with many health issues requires a visit to the doctor. Recent advances in the Internet of Things (IoT) are beginning to change that, however.

We can now use data — including numbers, charts, and analytics — that lend insights into people’s general health, fitness, and well being. Those insights, in turn, could guide us to improved health outcomes.

It’s a shift that needs to happen. Healthcare spending in the US is projected to increase from around $3.4 trillion in 2016 to $5.5 trillion by 2025, with yearly increases outpacing GDP growth by around 1.2 percentage points.

Deloitte’s 2017 global health sector outlook projects similar increases around the world, triggered by ageing populations, higher cancer and diabetes rates, increased prevalence of dementia, and continued threats from viruses like AIDS and Zika in developing countries.

Healthcare today is too expensive. But IoT devices could help reverse the trend and improve health outcomes across the board — both in terms of helping sick and injured people recover, as well as preventing illness.

“At the moment we are doing sick care,” explains health-as-a-service IT company ALMA.care‘s founder Kris Sienaert, whose background includes 14 years of work as a medical doctor. “We are waiting until we are sick and then we do something.”

With growth in the number of sick people outpacing increases in the number of medical professionals, he believes this trend is unsustainable.

“Instead of helping people one by one, I want to prevent people getting sick so they don’t need a doctor,” Sienaert continues. “We don’t need more doctors; we need fewer patients. We don’t need more care; we need fewer chronic diseases.” He adds that more than 75 percent of diseases are preventable, but only if we act in time.

Sienaert and many others in the health industry believe the trick is to make healthcare less reactive and more proactive — i.e., to continuously monitor people’s health with wearable and environmental sensors and to analyze the resulting data for patterns or changes that could indicate future or undiagnosed problems in healthy people.

To do so would mean improving health outcomes for people who are already dealing with health ailments. This trend is already taking shape in a variety of forms.

Some devices and services target easier self-medication and better data for doctors to base ongoing treatments and dosages on. Glooko, for example, helps track and manage blood glucose levels in diabetics by syncing readings from insulin pumps, blood glucose meters, and/or continuous glucose monitors with a smartphone app.

The company recently got approval from the U.S. Food and Drug Administration to take this a step further: to continuously measure and adjust the balance of long-acting insulin using a device called a Mobile Insulin Dosing System.

Meanwhile, medical research is yielding new sensors that could be useful for diagnosing and monitoring diseases, such as a wristband developed at Stanford University that measures and analyzes the molecular constituents of sweat.

Much of the research and development in health IoT starts in the lucrative sports and fitness market, where professionals and amateurs alike seek insights that could help them improve their performance and reduce injury.

Athos, for instance, embeds sensors in clothing that monitor heart rate, muscle activity, and other biometrics for athletes wanting to maximize their training time.

BSX Athletics’ LVL repurposes and builds on red light sensor technology from the medical devices industry to monitor hydration and heart rate in real-time and alert users when they are becoming dehydrated, which affects both physical and mental performance.

And HeadsafeIP’s low-cost Concussionometer device shines light into its wearer’s eyes while electrodes on the back of the head send EEG signal changes to a smartphone for analysis, which can be used to quickly determine if someone has undergone a concussion as a result of head trauma.

But while sport and running may drive much of the innovation, the resulting technology is often broadly applicable — with potential uses in corporate health and well being programs, injury rehabilitation, and perhaps even medical diagnosis.

Another company, SMG, started out in the early 2000s with a product designed to manage injuries in the New Zealand rugby union team. That technology was further developed and refined for more than a decade to power two sports science products, SportsMed Elite and Baseline. Now the company provides the foundation of a full suite of predictive data analytics products and services targeted at insurers and workplaces.

Many devices and companies are trying to turn popular wristband wearable technology into useful health monitors, but Sienaert notes that they’ve been largely unsuccessful because of the unreliability of the technology. The wrist, it turns out, is not a great place to measure key biometrics like heart rate or blood pressure at medical-grade accuracy.

“The best hardware for us would be a chest strap,” explains Sienaert, “because we really need the time between different heart rates in milliseconds. And it has to be accurate, because if you start working with inaccurate input then the output will be nonsense.”

He argues that it also must be continuous — i.e., 24 hours a day — because our bodies are constantly sending signals. A snapshot in the form of a blood or urine test might find something… “But after the snapshots, life continues, and you’re going to miss a lot of things,” Sienaert said.

Once the hardware problem is solved, however, two big roadblocks remain before proactive healthcare can take off. Firstly, there’s the motivation problem. If someone’s health is to benefit from IoT data, they must actually use the device. That is a significant hurdle for the general population, considering 2016 data that indicated low retention rates for smartclothes, smartwatches, and fitness wearables.

Sienaert thinks motivation will come from combining improved visualization of useful IoT data with regular notifications that summarize a person’s current health. Meanwhile, companies in the connected health space are borrowing ideas from fitness trainers like social motivation and goal setting.

Then there’s the issue of analyzing this accurate IoT data to not only identify short-term problems like high stress or poor sleep, which numerous companies can already do, but also to predict long-term deterioration. Doing so could be used to identify patterns that clearly and accurately correlate a change in the data to a future negative outcome —like a heart attack or diabetes — and then give personalized and actionable advice to prevent that outcome.

Only then could healthcare shift from being overwhelmingly reactive to largely proactive, with lower costs, healthier populations, and more effective care for those who do still get sick.

Related Stories