Summary of Quantified Self report by The Economist

The Economist published a report on the Quantified Self this week. It’s an excellent overview of the field and included some interesting facts I wasn’t aware of. It’s behind a paywall and consists of several reasonably dense articles, so here’s a brief summary with the odd comment by myself.?

Additional issues that we at Healthskouts feel strongly about, and that weren’t really addressed in this report, include:

• Using a patient centric approach - or Delight Thinking as we call it - to build and integrate these solutions in existing flows and operations.
• Levelling up the delight factor of digital health solutions radically, because today’s quality criteria are minimalistic and mostly about risk avoidance.
• Using citizen-centric data platforms to solve the crucial privacy issues that bedevil the field.?

As a final note, I disagree with the final conclusion of the report that equity/inclusion is the biggest challenge at present. Yes, it’s a huge challenge, but shouldn’t be an obstacle to innovation and progress in the field, in analogy to the way a premium concept like Tesla was ultimately instrumental in bringing electric vehicles to maturity. The most important challenges today, imo, are 1) data ownership & privacy, 2) the user/patient experience and engagement.

So here’s the summary of the report.

The quantified self

• The Quantified Self movement (“the meticulous collection and analysis of data about bodies and lifestyle that people do to hack their way to better health”) has evolved from a geeky niche community to something that is growing at the pace of mobile phone adoption. One in four Americans are estimated to own a smartwatch or fitness tracker and Apps sold more watches in 2019 than the entire Swiss watch industry.
• Wearable devices promise to bridge the gap between parts of society that care for us when sick vs parts that help us stay healthy, a trend accelerated thx to the pandemic.
• Personal activity trackers have real health benefits: users of such devices move and exercise somewhat more, but even small increases in activity can have large health impacts.
• Such benefits have convinced some health insurers to give away wearables to customers. Doctors are “warming up” to the idea that wearables can help them take better care of their patients (indeed, see poor prescribing rates in Germany). Bigger impact comes from large health systems that are making wearables a seamless part of clinical care. Finland’s citizens can link their wearables with their national health records (was news to me!)
• Looking ahead, key challenges include privacy and discrimination based on health data from wearables (indeed, see debacle around Roe vs Wade and fertility apps). Other challenges are variable quality of apps and how to evaluate and regulate apps.
• Nevertheless, the promise is huge since 80% of the burden of disease in America is caused by lifestyle factors and drugs work as intended in 30-50% of people.

Tracking your health: one ring to rule them all

• Detailed look at how the Oura ring works, combining sensor data and algorithms to generate measurements of heart rate, sleep duration & quality and step counts.? using data from photodetectors and 3D accelerometer?
• IQVIA reports 384 wearable devices marketed to consumers, including wrist bands, smartwatches, jewellery, patches, straps, clip-ons and clothes.
• Devices apply algorithms to sensor data to create “digital biomarkers” linked to particular health condition. How Fitbit and Apple Watch can identify atrial fibrillation. Activity trackers can sense abnormal gait associated with early stage Parkinson’s disease. Measures of sentiment in voice can be used to detect depression and changes in mood. Devices claim to track sleep stages, but most trackers aren’t very accurate, except Fitbit and Oura.
• Fitbit and Apple, among others, are good at measuring heart rate and predicting atrial fibrillation, as demonstrated in their large heart studies (each enrolled more than 400,000 people).?
• A key concern at present is the lack of decent clinical trials; most studies are small proof of concept studies. Privacy is another major issue, since unregulated devices are not bound by health data regulation, meaning personal data could be sold via data brokers to insurance companies or others. (This is a major issue, and dealt with differently in Europe. Also, see the Roe vs Wade and fertility apps issue).
• Interesting mentions: Rockly Photonics, claims its new sensor can measure hydration, sugar, alcohol, lactate, body temperature, blood pressure. HumanFirst, for its catalogue of sensors.

Dealing with the data: Killer apps, saving lives

• Continuous glucose monitors have replaced finger-pricked blood tests for diabetics and silicon valley geeks are using such devices to ‘hack’ their metabolism and personalise their nutrition.?
• Formal studies of metabolism using such devices have changed scientific thinking of what a healthy diet looks like, with a key conclusion that there is a lot of metabolic variation in people, meaning personalised nutrition makes sense. For example, some healthy people have large post-meal spikes in blood sugar, which is linked to development of pre-diabetes. Such ‘big dippers’ could be targeted with personalised nutrition to reduce their risk of diabetes.
• AI-based personalised nutrition apps such as Zoe are able to create personalised predictive models of their customers’ metabolism and recommend foods with predicted blood-sugar reactions to each.
• Early results reported by users of precision nutrition apps look encouraging, with reported weight loss, higher energy levels and improved sleep. Some diabetics no longer need medication.
• The user experience and design of many health tech apps are still poor however, with scant consideration of behavioural science, which is probably why drop off is huge. There are about 5 million health app downloads per day, but 95% of those downloads are deleted within 24 hours.
• A claim from an Orcha representative (Orcha evaluates apps): “the problem is that people do not just need a product that is well designed. They need a product that is well designed for them.” (I would argue that better design can take us very far in engaging users, akin to the way a good Netflix series doesn’t need to be personalised to enchant millions of people. The problem is that most apps are not enchanting at all).
• Orcha has rated 7000 health apps on 3 criteria: privacy, user experience and evidence. Only a quarter meet its quality threshold on all three (I wouldn’t use the word ‘only’). According to Orcha, quality is improving because thanks to guidelines set by British health authorities, developers now have clarity on what “good” looks like. (my sense is that we still have a very minimalistic perspective on quality.)?
• The biggest challenge in public health is making people stick to healthy behaviours, which is a key opportunity for digital products that boost compliance. E.g. Isreali startup Sweetch, an AI-based personal coach/secretary, makes timely suggestions about when you could go for a walk or eat something healthy. Personal goals adapt to how you are doing and you can personalise the tone of voice of the bot to friendly, commanding etc.

Software as treatment: digital therapeutics

• Kaia Health’s AI physiotherapist relies on the user’s smartphone camera to guide him or her through exercises. Studies show that Kaia’s app is on many measures as good as a human therapist.
• Kaia is just one of many new FDA approved digital therapeutics for medical conditions such as diabetes, back pain, addiction, anxiety, ADHD and asthma.?
• Germany, Belgium and France are creating pathways for digital therapeutics to be reimbursed by health insurers.?
• Interesting perspective from Brent Vaughan (CEO Cognito Therapeutics) who says there have been 3 waves in the evolution of DTx:?
• The first is “nagware” - apps that remind or nudge users to do things, like move, take medication,etc. These could have a big impact on population health to improve compliance and lifestyle among chronic disease patients. Some can even replace medication-based treatment, such as BlueStar’s diabetes program and Perfood, an AI-based app for migraine that has a personalised nutrition component.
• The second wave are digitised versions of existing interventions that have almost no safety risk, such as cognitive behavioural therapy for various mental health problems.?
• The third wave are the genuine medical breakthroughs: the therapies that change the progression of a disease by changing the biological mechanism. The latter is illustrated by MedRhythms, a therapy that uses music to restore movement-related brain connections in stroke patients.?
• Freespira, a digital therapy for panic attacks and PTSD, is illustrative of a digital treatment of a health condition for which existing treatments are of limited benefit.?
• A key priority for digital therapeutics is to prove their value and health benefits to payers and healthcare providers.
• Health systems such as Advocate Aurora Health are beginning to batch-prescribe digital therapeutics to relevant groups of patients.?
• The key challenges for providers is finding the most suitable apps for specific patient groups and connecting those apps to the medical record systems. Companies such as Orcha, AppScript and Xealth are focused on addressing those challenges.?
• Regulator approved digital therapeutics are being positioned as high-margin products. Pear Therapeutic’s 3-month program for insomnia costs $899. Akili’s therapy for ADHD costs $450.?
• Since digital therapeutics are still a novelty for doctors and not prescribed at significant volume yet, many DTx makers partner with pharmaceutical companies to fund and distribute the product. Pharma companies hope that apps could increase drug sales by boosting the efficacy of their drugs, or that they generate real world intelligence.?

Measuring the masses: The pulse of the people

• Research institutes such Robert Koch in Germany and Scripps in California set up studies during the covid-19 pandemic that asked people to share data from wearable trackers. These studies showed that covid infection can be detected by tracking abnormal changes in people’s resting heart rate. Studies by Scripps also showed that abnormal changes in heart rate, sleep and activity are correlated with flu-like symptoms. This illustrates that consumer fitness trackers and smartwatches could play a key role in population level disease surveillance.?
• Since people use a wide variety of different devices, the data won’t be consistent and perfectly accurate, but for disease surveillance purposes the data is still useful. One group of researchers has developed algorithms that detect changes in people’s metrics, irrespective of the type of device and type of data. If lots of people are diverging from their baseline at the same time, irrespective of the specific measure, it suggests that lots of people are getting sick, probably from the same thing.?
• A key challenge is understanding whether such algorithms might systematically miss things in some types of people. E.g. an algorithm could be optimised for affluent areas.?
• These studies also turn up mysterious findings, such that Germans appearing to be sleeping less well in 2022 than in 2020, or that resting heart rate is higher in the east of Germany compared to the west.
• Wearables are also changing the way clinical drug trials are done, with 10% of late stage clinical trials in 2020 using connected devices to monitor people.
• A key benefit is that medical researchers can see how patients experience a disease and treatment in their natural context, can replace or simplify standard outcome measures such as the six-minute walk test can be simplified using trackers, can compliment standard outcome measures with more patient-centric quality of life data, and can open trials to more patients who otherwise would be excluded.?
• The first fully digital trials have been successfully run. Such trials make it easier to recruit many people, but they also suffer from large drop off.?

The report concludes on a positive note, arguing that wearable trackers can change the way people look after their own health, the way doctors take care of them and the way population-level health interventions are organised. Notwithstanding the rapid adoption of such technology, even in developing nations, the biggest challenge remains the digital divide whereby some people don’t have internet access, lack the digital literacy or simply the time to make use of new health technology.?