Digital health: The age of (real world) evidence
By Nicolas Schmidt on Feb 8, 2018
Digital health is everyone’s favorite buzzword at the moment. Panels and presentations discussing the topic have popped up with more and more frequency at health conferences and conventions around the globe. Digital health startups are invading Silicon Valley like the chronic diseases they pledge to control (and raising a ton of money doing it). In 2016, there were 325 million connected wearable devices worldwide and that number is projected to be nearly one billion by 2022. At CES this year a visitor could barely turn their head in the main showroom without staring down yet another booth hawking tech-heavy wearables.
Despite all this, or perhaps because of it, many have come to associate the digital health revolution with mere gadgetry, a wearable wave soon to crash on the shores of irrelevancy. This view is misguided and outdated.
Research in Reverse
To prove medical relevancy, traditional drugs follow a simple path, traveling from research to third-party medical validation. This leads to medical relevancy and finally to consumers and standard of care. This process is linear and failure at any step in the process is followed either by starting over or abandoning the project altogether. We see this process in action for every new drug that comes to market. Digital health, as a consumer-oriented movement, has turned this linear process inside out.
Fitness trackers, apps and connected health devices all found their way to consumers before the healthcare industry had any say. Consumers appreciated the value these devices provided and started buying, downloading and using them far before their relevancy or even their validity was studied. The technology that has come to be known as digital health started at the final step of our linear process. Digital health has time and time again proved the accuracy of these devices and many connected health devices today even get FDA approval. This is not enough. Despite the industry’s protests, it’s clear that to become medically relevant, digital health will need to close the loop. It’s time to move connected health towards standard of care, and to do this we don’t just need validity- we need medical relevancy.
The Pathway of PGHD
There are two main problems with our current healthcare system that digital health solves. First, hospitals still act as gatekeepers between patients and their health records. In the age of instant answers, patients demand responsibility and empowerment, and that means owning their data. Digital health opens the floor for more advanced remote patient monitoring systems, so patients and doctors can manage illness together like never before. Second, medicine lacks personalization. That healthcare remains a one size fits all industry contradicts the basic reality of biological diversity of both humans and diseases. This was okay when doctors had so little information about patients.
Digital health is more than just selling cool devices to end users- it’s also allowing us to deliver this new type of Patient Generated Health Data (PGHD) and allowing this data to flow directly into the hands of healthcare providers who need it the most. Most doctors have no idea what their patients do at home. As long as there was no way to know, this was simply a fact of the business. With connected health, not knowing is now akin to being a guilty bystander. Caregivers are now potentially faced with new responsibilities, and anybody who has been working in a certain way for the past century would obviously resist change and undermine its necessity. Those not participating in this revolution, however, risk being left behind.
The precision medicine movement, fueled by the ubiquity of sensors, genome sequencing and data storage and analytics is fostering a grape of innovations in personalized solutions. People have different phenotypes, genotypes and behaviors and their treatments should be able to reflect that.
Silencing the Skeptics with Personalized Research
To design treatments that take our individualities into account, the personalization will need to start right at the treatment design phase. Connected health allows the personalization of research. If we can personalize research, we can personalize treatment plans. This is why clinical and drug development research needs to start factoring in PGHD.
The path connected health is walking is the same path walked by life sciences decades ago- gain medical support, build evidence, identify where there is medical value and push adoption. According to a 2014 Pew Research Center study, adoption rates for new technologies have never been higher. Consumers have already started making these devices part of their lives but healthcare lags behind for lack of a proof point. It’s usually the research that should be ahead in terms of adoption.
Research involving connected health devices is already moving the industry forward. A recent study published in the American Journal of Hypertension looked to discover if there were any trends in the day-to-day fluctuations of blood pressure in study participants. As the study notes, Blood Pressure Variability describes the fluctuations in a person’s basal BP, and although long thought to be random and inconvenient to clinicians attempting to take accurate BP measurements, is actually somewhat predictable. While the results of the study were quite intriguing (BPV increases with age, is higher in females and higher in the winter months and on Mondays), perhaps the most interesting thing here is the way the study was conducted. The process to measure BPV in the past was arduous and expensive- sample sizes were small and data was almost always for personal use only. New technology, including the Nokia BPM blood pressure monitor cuff used in the study, allowed researchers to include nearly 17 million measurements from over 56,000 participants to identify trends in BPV that have never been studied before. And the best part? Thanks to the omnipotence of smartphones, a large portion of the cost of the study was already covered by the participants.
From Research to Standard of Care
Patient-generated health data is not just a research opportunity, it is bound to transform patient pathways and will soon be widely adopted. Barriers to adoption are lower than ever- there’s no connectivity cost, it’s easy to retrieve data and patients are eager to embrace the tech. Major health systems are already on the PGHD frontlines, including Mayo Clinic, the American Heart Association, Beth Israel Deaconess Medical Center and many, many more. This group of determined technologists, doctors and ethicists set out to prove the ancient healthcare industry wrong. PGHD is a source of new knowledge and provides real world evidence. To prove its worth, connected health needs to undergo medical validation or contribute to research with new data, more data and more trends.
Today, the data to validate drugs and treatments flows in a linear direction, from studies, to research, to clinical trials, to adoption. But as connected health approaches the medical validation tipping point, the healthcare industry will begin to ask: what’s next? Care is headed to smartphones, because that linear flow doesn’t exist in the information age. To maximize the use of PGHD, data must flow freely and at the patient’s sole discretion. The patient controls information as it goes to pharmacies, hospitals and their own electronic medical record (EMR). Digital health is accelerating not just the process of treatment development, but also the feedback loops between patients and their caretakers. Now, real world evidence data is set to conquer the world, and the transition from research to standard of care is bearing down on the horizon.