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By Jeffrey L. Sturchio
Over the past few years, our interactions with the healthcare system in the U.S. have become increasingly based on digital tools and technologies. Just consider that in less than a year, from 2019 to 2020, the percentage of U.S. patients who used telehealth increased from 11 percent to 46 percent, driven in large part by the spread of the COVID-19 pandemic. In many ways, these systems of digital monitoring and electronic records have become so widespread that they are almost unremarkable. And yet, despite the ubiquity of these technological processes, many, both in and out of the industry, are still asking themselves: what exactly qualifies as “digital health”?
Indeed, as scientists and innovators around the world continue to re-imagine existing medical processes with digital in mind, it can be difficult to see the “forest for the trees” when it comes to digital health and its implications for our society. With this in mind, let’s explore a few key insights about the role of this term in today’s rapidly evolving healthcare landscape – underscoring why it deserves our attention.
What exactly is digital health?
A few months ago, I came across a definition of digital health, coined by the Digital Therapeutics Alliance and their partners, that I believe does an effective job at explaining what encapsulates digital health and how it plays a role in our society today.
“Digital health includes technologies, platforms, and systems that engage consumers for lifestyle, wellness, and health-related purposes; capture, store or transmit health data; and/or support life science and clinical operations.”
Admittedly, this is a lengthy definition with a laundry list of different topic areas; however, it does effectively showcase one important fact about digital health: its applications are boundless. Just consider a few notable examples: recently, MIT scientists in artificial intelligence found that they could detect asymptomatic COVID-19 infections through cellphone-recorded coughs. Additionally, using GPS data, a team at Washington University in St. Louis found that they could predict preclinical Alzheimer’s disease 88 percent of the time – all by measuring study participants’ driving habits.
These are just two examples among many that showcase both the potential and the heightened attention surrounding digital health. In fact, one estimate is that there are nearly 450 start-ups in neurotech alone (at the intersection of neuroscience and new digital technologies), with U.S. investment in digital health start-ups reaching nearly $15 billion in the first half of 2021, surpassing the annual total for 2020. At the same time, large tech companies like Amazon, Apple, Facebook, Google, and Microsoft have all begun to explore ambitious plans to bring their skills and resources to bear on the possibilities for digital health.
As evidenced from the above, it’s clear that digital health solutions aren’t going anywhere, anytime soon. Faced with this exciting new arena, it’s important that we in the healthcare community leverage these innovations wisely, putting time and energy behind the technologies that can positively affect individuals around the world and empower them to take charge of their own health.
Digital health – enabling a revolution in neuroscience
Recently, I had an opportunity to speak with Martin Dubuc, who leads Biogen Digital Health, and his colleague, Belgian neurologist Dr. Shibeshih Belachew, who leads Biogen Digital Health Sciences, to gain additional insights for the rapid evolution of digital technologies – particularly related to neuroscience. According to Belachew and Dubuc, neurological conditions, like Alzheimer’s disease, Parkinson’s disease, or amyotrophic lateral sclerosis (Lou Gehrig’s disease), provide an interesting case study to this effect. For far too long, these debilitating disease areas have been difficult to diagnose and monitor. Despite the ultimately life-threatening nature of these conditions, the typical markers used to diagnose and measure them are often subjective and infrequent – leaving neurologists unable to pick up small changes that could help them to treat individuals sooner.
Let’s take Parkinson’s disease, as one example. Because signs and symptoms for this degenerative nervous system disorder often develop slowly, it can be difficult for physicians to pick up disease progression at an early stage. Typically, neurologists will simply ask patients to perform motor tasks and walk across their office to observe symptoms of subtle motion slowness or gait difficulties – which hardly provides enough data to be definitive.
However, by using quantifiable physiological and behavioral data (also known as digital biomarkers), neurologists can capture months’ worth of data in minutes, showcasing how an individual’s gait can develop over time. When combined with artificial intelligence-enabled pattern detection, neurologists can gain access to a wide array of clinical patient insights – potentially allowing them to spot signs and symptoms of Parkinson’s disease at an earlier stage.
“Currently, clinicians have limited data to guide their judgments. Using digital tools combined with artificial intelligence and machine learning, however, we can enable a revolution in the instruments we use to investigate the brain,” says Biogen’s Dr. Belachew.
Just as Laennec’s use of the stethoscope and auscultation and percussion techniques became a new standard in medical diagnosis more than 200 years ago, the use of new digital “instruments” may make it possible for clinical researchers to move to objective measures done in real-world settings. “Doctors see the infinitely complex organism of the patient,” says Belachew, “yet, we must fight against the simplification of our conventional decision-making models and the scarcity of information at hand about the reality of the diseases we are studying. Digital biomarkers may eventually enable us to think about data-driven metrics in a more precise and individualized way.”
Martin Dubuc agrees, offering an intriguing analogy about the growth of digital health technologies: “as Formula One race cars began to incorporate digital technologies, the early models had only eight channels of data. Now they have some 16,000 channels of data that provide continuous monitoring of nearly every aspect of the car’s operation, which has made possible continuous improvements in performance. The hope is that we will ultimately see similar advances in neurology, as verified, validated digital biomarkers come into use to improve health outcomes and bring personalized medicine to neuroscience.”
In pursuit of this effort, however, Dubuc notes that new technology platforms will need to be blended with deep knowledge of the diseases under study. What’s more, companies will need to build teams with diverse, tech-forward skills, as well as to embark on new partnerships that bring these emerging fields together quickly and with the needs of patients at the center. “This convergence is beginning to occur,” as Dubuc observes, “and will soon (if not already) enable us to pioneer a new era of medicine built upon a foundation of accessibility and precision.”
The future is now
As the power of new computing platforms increases, and the effectiveness of electronic monitoring tools improves, it’s more important than ever that we acknowledge the potential of digital health to transform patient care. Today, we’re rapidly entering a period of profound healthcare disruption that will no doubt permanently transform the way that patients are diagnosed, treated, and monitored. As healthcare companies around the world embark on a race to realize the promise of a patient-focused and digitally enhanced future, one thing’s for certain: it’s no longer a question of if digital health and neurotech will play a role in the future of healthcare, but how.