What health parameters can the most affordable smart devices and the most advanced and expensive consumer technologies measure?
Wearable technology has made significant progress in the last few years. The average amount of sensors per device tripled in less than a decade, which tremendously grew the data coverage of mass-market devices. All off-the-shelf wearables now enable a holistic view of their wearer’s health, covering activities and sleep, as well as heart rate specifics.
While these metrics already provide tremendous value to most prevention and non-communicable diseases services, as they allow for 24/7 health status monitoring over long periods, we’re only at the beginning of a healthcare revolution. A new generation of devices delivers medical-grade information on blood pressure, body temperature, ECG-grade heart rate variability and blood oxygenation, unlocking many new use-cases. And there is much more to come.
How fast is the progress in this field and what breakthroughs do you expect? Some rumours suggest, for example, non-invasive glucose measurement in smartwatches.
As wearable technology evolves from a lifestyle-focused second screen for smartphones to a more mature companion to track and improve consumers’ health, consumer electronics companies are digging into the territories of traditional medical product manufacturers. As a result, more and more medical sensors make it into consumer devices and hit vast adoption rates fast, far beyond niche audiences.
Non-invasive blood glucose monitoring is definitely one of the most anticipated technologies in our industry. Several companies have already made substantial advancements in the last months and years.
But it’s not just individual technological advancements driving the market. It’s more the industry-wide mindset change we experienced in the past months. People started to understand the importance of objective, passively collected data for truly digital and experience-driven products. The shift from a one-treatment-fits-all system reacting on symptoms towards an individualized care model focused on proactive prevention won’t work if we keep digitizing existing paper forms.
Some data can be derived from smartphones, some from wearables, and some from other smart devices. From your perspective, as a startup that focuses on data integration, what is the next step we have to make to synchronize all the data from different sources to deliver personalized experience and advice to individuals instead of raw numbers?
Silicon Valley has coined the term “healthcare has left the building”. Digital services provide care for an increasing set of use-cases, while the tools to measure health at home grew tremendously. From connected scales and glucometers to blood & urine tests to swab-based DNA tests, you can now measure virtually every important health metric at home.
Most users and patients collect health data every day. But the critical part has been missing for a long: combining all of this information and enabling easy access for relevant stakeholders.
In Silicon Valley, it is said that healthcare has left the building
Let’s break it down to a few examples: Knowing that you’re stressed is as much of a value for your mental health app as it is for your fertility and contraception planning. Likewise, knowing that your hormone level is off with your urine test is as valuable for your migraine care program as for your diabetes treatment.
In this world of abundant but dispersed health metrics, each additional sensor provides exponential value. So the most important next step for health services? Integrate the different data silos and inform your care with better data.
Big tech has also recognized the trend towards individual health management. iOS and Android systems for smartphones have integrated health apps. Will they monopolize the digital well-being trend as smartphones are the most widespread digital device with a still unlocked potential to measure vital signs derived from voice, daily activities, selfies?
We definitely see that big tech exploring the healthcare industry. While it’s not yet 100% clear how Facebook, Amazon and Microsoft define their role in disrupting healthcare – besides the latter providing the cloud infrastructure needed – Apple and Google follow a pretty clear strategy.
Apple Health and Google Fit want to become the central hub for mobile healthcare. It is already visible that their strategy strongly tends towards building their next “walled garden” to manifest their monopoly-like position in the mobile segment. This is an indeed worrying trend if you are – like me – rooting for interoperability and a diverse market. They’re replicating the practices from the smartphone market, barring access and avoiding data sharing.
Luckily, there is one fundamental difference – the capabilities of smartphone-based 24/7 health monitoring are ultimately limited. Most readings will still require specific sensors and this heterogeneity is a big chance to create a healthy market ecosystem instead of monopolies.
Thryve has recently stepped into the digital clinical trials market. How has this area of medical sciences changed recently, also due to the COVID-19 pandemic, and what is the next thing in clinical trials?
Clinical trials are used to exhibit all flaws of the healthcare system at once – they’re bureaucratic and take ages to start, while information is gathered only in person and on paper. So COVID-19 was quite a shock for the industry, with almost 90% of trials halted in April 2020 due to contact restrictions.
In 2021, trials are built back better. Previous trends have accelerated and digital tools are now abundant to recruit patients and generate the right data throughout the trial. This is also a vast opportunity for Phase IV trials in real-world settings – digital tools enable much more convenient data generation and thus affect transparency than ever before.
With Thryve’s new study infrastructure, we help unlock those potentials by combining questionnaire and sensor data generation in a simple, unified app. As traditional health monitoring methods in doctors’ offices and clinics miss more than 90% of the data needed to understand treatment effects, we support access to continuous, passive data.
Data from digital devices can also be used for Big Data analysis for population health management and epidemiological surveillance. What opportunities do you see in this area?
We’ve seen first proofs of population-level insights within the pandemic in projects worldwide, including the “Corona Datenspende” (eng.: Corona Data Donation) app, which we have launched in partnership with the German Centre for Disease Control in the very early days of the pandemic. Citizens were asked to “donate” their wearable data so that we could analyse it for infectious diseases.
And the results are pretty impressive: Although this kind of technology was deployed for the first time on such a scale, we could quickly help detect systematic deviations of infections on population-level data that could help inform medical authorities.
More opportunities will arise – which will hopefully not be pandemics – with the ongoing diffusion of more powerful sensors to identify, e.g. the spread of flu and other diseases with the need of monitoring on a population level. However, ensuring that data is shared voluntarily and analysed according to good scientific practice and strict data protection laws is essential to maintaining trust.
If there are such promising benefits, what must be done to make a step forwards in integrating data for secondary use?
I think it’s often overlooked that there already is a vast global market in secondary data. My main concern – the data is patchy. It’s easy to draw wrong conclusions from a clinical data set that misses information about the 90% of healthcare determinants that happen outside the doctor’s office (e.g. lifestyle, nutrition, environment etc.).
When we talk about data, we have to address the topic of data security, privacy, and trust. For example, how safe are the most popular wearables like fitness trackers? And what are your observations regarding trust? Are people willing to give their data in exchange for better prevention?
All manufacturers we work with take security and privacy very seriously and follow industry standards, as everybody working in healthcare should. And users care about this as well and are interested in understanding the security mechanisms.
If you have gained that trust, there is, in our experience, little to no extrinsic motivation needed for users to share data. With the “Corona Datenspende” App, more than 500.000 users shared their data without gaining any personal benefit or value. While extrinsic motivation is not always needed, users feel the need to understand why this data is critical and exactly how it is used.
When looking at specific services in prevention or care, the motivation is a better and more individualized service.
What must be done so that the concept of “connected health” becomes real?
Interoperability between health records and service providers needs to be and is a top regulatory priority. Digital services are set to provide a significant amount of NCD-care in the future. And medical devices that used to be dumb, like scales or blood pressure cuffs, become connected. So once all of those ties in, we’ll be there with connected health. But mind again – the concept is not a value in itself. It becomes valuable only if we use connected health sensors and services to provide better service at lower costs and avoid pain and diseases.