Quantified Self: It is not just a numbers game

A new cultural phenomenon is sweeping across the world, led by the digital paradigm shift. However, it is not just systems and processes being digitised, individuals themselves are also undergoing ‘digitalisation’. Through the widespread adoption of smart devices, people have begun to track their own wellbeing. This global phenomenon has been coined as the ‘quantified self’, with many programs entering the space aimed at helping individuals meet their health goals from fitness to diet, mental health and more.

To achieve such goals, the quantified self programs have identified key biomarkers; be it biological molecules found in our body fluids, blood or tissues that can be a sign of either normal or abnormal process or digital biomarkers like everything measured on our smartphone or wearable. With the identification of biomarkers we can measure our body, performance, or wellbeing every week. And there is no end in sight.

Overall, the quantified self in healthcare market will reach $39 billion globally by 2026, and hundreds of companies are looking to claim a piece. For the companies eager to enter the race, while the quantified self may be focused on data-points and trends, it’s important to not forget about the very human aspect behind the numbers.

In this article we want to share our insights on what we at Heal Capital believe can be game changing… or rather lifestyle changing solutions. As we like to say: Find me the smallest action with the highest impact to achieve my goal!

Afterall, we are all too often lazy, complacent and too comfortable. If the data tells me I need to eat healthy and run a 10k per day, it will not really help me. But, if it tells me “leave out the white rice, while keeping the chocolate and just take a 10min walk post dinner and you achieved a lot” — I say “hell yeah”. So let us share a bit more about the ass-kick effect and the volatility factor!

Quantified Self: enabling the empowered patient

The quantified self refers to the cultural trend and community of users using self-tracking tools to gain an understanding of themselves through numbers, without becoming a cyborg. It overlaps with lifelogging and other aspects that incorporate tech and data into their life to improve their wellbeing, be it physical or mental. Users break down this data to make lifestyle changes, whether it is adding more iron to their diet, taking walks after lunch, or meditating each night before sleep.

The widespread adoption of wearable health tech gadgets is linked with a larger health phenomenon taking place. In the field of healthcare, individuals are tired about being passive with their health. The ‘empowered patient‘ represents the paradigm shift taking place where patients begin to take a bigger role in their health, actively tracking their wellbeing, actively taking a preventive stance against illness, and working to reach their peak mental, emotional and physical wellbeing. As patients desire to become more knowledgeable on their health and be able to participate in conversations with physicians, more have turned to wearable health-tech devices, with fitness trackers reaching a global market value of $7.3bn in 2018.

The arrival of quantified self coupled with the empowered patient could not come at a better time. The rates of chronic illness are rapidly raising, linked to an aging population as well as poor diet and physical inactivity. Globally 1 in 3 adults experience Multiple Chronic Conditions, with illnesses like cardiovascular disease, diabetes, cancer, and more. A contributing factor to this growing crisis is largely based on our current reactive approach to health. Fortunately, with the quantified self trend, individuals are able to monitor their wellbeing and make responsible life-style changes to address the growing risk of chronic illness.

Promising health-tracking/biomarkers

The relevance of the Quantified Self has been well-established, heralding a healthier more empowered future for many. But that leaves us with the key question, what on earth can we successfully quantify? The list of health-tracking devices and biomarkers have grown over the past few years. Below we have listed 3 approaches that we find promising.

1. Continuous Glucose Monitoring (CGM): is a compact medical system that continuously monitors your glucose levels in real time. The application has been gaining popularity to gain insight on one’s metabolic health to maximise diet and exercise. Companies like Levels and January AI have begun carving out the space. While Levels is still in its beta phase and not yet available to the public it already has a long waiting list and raised $11.9 million in its seed round. With Levels, individuals continue with their normal and diet, however with the CGM device they receive instant feedback on how their meal and exercise impacted them. As metabolic health is unique to each user, individuals can gain insight on what foods they can eat and when they can maximise their exercise for the best health outcomes.
2. Heart Rate Variability (HRV) — HRV measures the time between each heartbeat and is heavily influenced by a variety of factors like stress, hormones, sleep, metabolism and more. It has been adapted to smartwatches and medical grade devices and used as an indicator for evaluating the hearts condition, analysing its ability to adapt to environmental stressors and increased fitness. Low heart rate variability may indicate that some factors in your life are impacting your wellbeing such as insufficient sleep or poor nutrition. However, in contrast to blood glucose levels the medical depth of HRV as a biomarker is still shallow. It might, however been an easy way to indicate stress levels and help us to make minor adjustments to temper it. Companies that have adopted this biomarker include Welltory and Kenkou. Welltory analyses HRV throughout the day from morning to night, between exercise, eating, working and sleeping. From the data collected, correlations can be made to see how one’s habits affects this biomarker, and how that shift can impact wellbeing indicators like mood, productivity, and mental health.
3. Sleep: Another key indicator is sleep. While our understanding of all the purposes of sleep is not yet complete, it is well-established that is goes beyond restoring energy but promotes healing, interacts with our immune system, and impacts our brain function and behaviour. Changes in sleep pattern can have serious repercussions, acute sleep deprivation can impair judgement and cognitive performance, while long-term sleep issues can be linked with disease development like obesity, heart disease, high blood pressure and diabetes. Many companies like Eight Sleep and Oura are taking a crack at the space. Eight Sleep has developed a `smart´ mattress that tracks breathing, temperature, and heartrate, then adjusts the mattresses temperature to ensure long, healthy sleep. Oura uses a smart ring that tracks resting heartrate, HRV, body temperature, movement, and respiratory rate while sleeping. It sends all the data to an app on your phone, giving you insight on your predicted energy levels and sleep habits.

Based on the 3 examples above, there is clearly diverse data sets that are being collected. While some are medically accepted, others are less established or are completely new indicators for wellbeing and yet to be determined.

Creating the framework for actionable insights

While there exists countless of indicators and biomarkers, the following question arises, what should we collect? Any data is only relevant if it provides actionable insights. Therefore, we identified 4 key objectives that any data needs to provide. We call it “ease of collection” “volatility factor”, “degressive effect” and “ass-kick impact”.

Ease of collection is straightforward, referring to a health-tracking device that is minimal bother to its user. In the case of tracking sleep, the company Eight Sleep provides a better approach then say the apple watch, with its comfortable mattress that can collect various biomarkers and adjust itself accordingly. Wearing an apple-watch to bed… not so much.

Volatility is important as data is only relevant if there is change. Hence, height would be a bad indicator, weight more so, while glucose level is continuously shifting resulting in a high volatility factor. This allows the user to identify patterns quickly and thus make the right changes. With CGM, whether the user eats a banana, goes for a walk, or eats a heavy carb meal… the feedback will be instantaneous, and the results will vary (bananas are good, walk helps lower sugar spike, and for the love of god, lay off the carbs).

Degressive effect can be compared to a learning curve. The ideal approach is to have a continuous curve, so new insights will be gathered even after weeks or months with the application. While CGM has high volatility, it also has a higher degressive effect. After a month or two of application, you know what works and does not work in your diet. The lessons fade and thus, so does your interest. Ideally, an approach has a lower degressive effect, like blood pressure. There are thousands of factors that can apply from poor sleep, social setting, diet, exercise etc. One can continuously learn about their body and its reaction, thus making changes accordingly.

Lastly, the “kick-ass impact” — there, the data shows us the stark price we face if we do not change. Those that frequently have high sugar spikes, low HRV rate and high blood pressure should receive warning bells loud and clear. Something like step away from the red meat, white rice, and step up the exercise unless you want to keel over from a heart attack at 40. Overall, we believe it is always important to understand how valuable the underlying data set really is.

Heal Capital Thesis

The Quantified Self movement has the potential to improve wellbeing and lifestyle choices. However, the quantified self is more than just a numbers game. While concrete data on your health choices can perhaps sway some into making changes, in the end we all still face the human challenge, which is sticking to the regime/diet/exercise change. It is important that we focus on small attainable steps rather than big ones… as we know nothing feels worse than failing.

Companies today have excelled at the data-collection aspect. New biomarkers are identified and tracked, with all the data flowing seamlessly from device to device. However, the point of it all falls short if one cannot interpret the data to make the best improvements.

Thus, Heal Capital is seeking for companies that goes beyond the numbers, and incorporates our 4 objectives: ease of collection, volatility, degressive, and kick-ass. We want to achieve our goals and not become data scientists. A solution should be able to collect and analyse all the data around the quantified self and provide the individual with feasible yet big impact results. Companies must think acutely about the user experience: less data, less friction, and more value. In day-to-day products, from our smartwatches to smartphones, apps should deliver easy, high-impact feedback at the precise moment it is needed. If we want to help the masses to address a disadvantageous path to chronic diseases, we need to start with simple with easy measures that are helpful for the individual.

What has the highest “kick-ass factor” for you? Tell us about your best quantified self solutions to achieve your goals.