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By Robin Gaster
For 100 years, retailers have segmented the broad marketplace into groups – soccer moms, or Millennials, or New Yorkers, or readers… pretty much every retailer uses target segments like those. But Amazon has never been interested. Instead, it wants a segment of one: you. It gathers information about what you look at, what you buy, your browsing habits. To that it adds information from your purchases – address and credit cards on file – as well as your Amazon address book to find those close to you. It is also the second biggest tracker on the web, after Google, so it follows your activity far beyond the Amazon ecosystem. And it can access the standard sets of information that can easily be sucked in from outside: your credit score, your home ownership, criminal complaints and records…. Amazon probably knows more about you than any other entity on the planet, including your mother and your spouse.
Put that aside for a moment.
Turn to healthcare. The pandemic has accelerated some trends here, notably telemedicine. That’s given a healthy push to an emerging field – remote diagnostics. Your phone is gradually – with some extensions – turning into a remote diagnostic tool to replace doctor visits and expensive tests. That’s fairly well known, even if it is extraordinary: blood oxygen levels are captured by a device costing less than $20, while an always-on cardiac monitor tracks heart activity, for example.
But that’s just the very tip of the iceberg. Remote diagnosis can transform the entire scientific basis of modern medicine. Currently, the gold standard for testing the safety and efficacy of treatments is the randomized control trial (RCT), in which some part of the trial group is treated while another part is not. Both are tracked to see whether the treatment worked, and to look for adverse events like additional illness or even deaths. Outcomes are assessed using standard statistical tools to compare the two groups.
This is the gold standard. But it is based on a single core assumption: that humans by and large react similarly to treatments, and hence that the best way to address disease is to identify treatments that work effectively for large numbers of patients. Ideally, treatments work for everyone, although sometimes RCTs and subsequent tracking find groups for which a treatment doesn’t work, or another for which it works especially well – maybe the old (or young), men (or women), or people with specific pre-existing conditions. Still, this is definitely mass-oriented medicine: it’s based on the impact of treatments on what might be called the median patient.
Amazon is about to enter healthcare in a big way. It is already planning to offer Amazon Care (its primary care system organized around telehealth) not just to its 1.2 million employees, but to other employers as a service, much like it offered Amazon Web Services 15 years ago (and AWS is now the leading provider of internet infrastructure in the world). It also purchased Pillpack and set up Amazon Pharmacy to deliver medications and other health products online for delivery. But the real revolution is coming inside the home. The Amazon Halo is a new health monitoring device (with some admittedly creepy privacy-related features). It is designed to apply the capabilities of AI to the needs of individual patients. And then there is Alexa, which is clearly going to be Amazon’s device of choice for wellness in the home. It’s already partnered with Sharecare to provide automated advice on 80,000 wellness and health questions, as a first line response to health concerns. Alexa will likely expand, gaining the capacity to integrate remote diagnostics and escalation into Amazon’s wider telehealth network.
Still, this mostly sounds like more of the same: using telehealth and the telemedicine capabilities, but mainly just extending what we do now, making it all a bit more convenient – possibly, a lot more convenient. But all these new tools, and especially diagnostics tools, make truly personal medicine possible – like Amazon, all this will be individual-specific: a market segment of you.
Let me tell you a personal story. I suffer from sleep apnea. I discovered this after going into a hospital for a sleep study. I then used a CPAP positive airflow machine while I slept, to push air into my lungs. A second sleep study confirmed this was working. A few years later, the in-hospital sleep study had been replaced by one I could do at home, using a machine the provider gave me for the night. It too confirmed that for that specific night the CPAP worked. But I hated it.
And then I found an app for my phone that tracked my sleep. More, it encouraged experimentation by tracking all manner of variables – whether I had had a drink before bed, the kind of pillow, room temperature – about 30 variables that might affect my sleep, along with a range of potential treatments. Every morning, I would check and the app would give me an apnea score along with other helpful sleep data. So I experimented. After a while, I narrowed in on a small set of factors that made a difference for me. I used a dental device to hold my mouth open instead of CPAP; I tilted the mattress slightly; and I used a specific pillow. That did it! My apnea score dropped from an average of about 30 to 2.
Critically, I could now easily run endless experiments: I wasn’t limited by the need for expensive tech which had to be returned to the clinic, I didn’t have to depend on extremely expensive (and slow!) RCT’s that could only test one solution at a time. I could run new experiments every night, and I got new data every morning. And that’s transformative: I could move beyond large-scale RCTs, towards experiments that tracked treatment effects for me alone, assessing the impact of dozens of variables in the course of a few weeks. Al that was now possible because the data collection tools had advanced so dramatically.
The implications are enormous. This is not “personalized medicine.” It is personal medicine, designed by me for me alone. I have no idea if this works for others. But now imagine if Amazon was available to support this. Imagine if Amazon tracked the activities and outcomes for every experiment that every person ran using the app (or the Halo). Imagine if Alexa could say to you, “362 people found this to be useful, and another 201 found something different helps. Maybe you should consider using both these approaches, and let me know what happens.” Amazon can also crunch the numbers – I analyzed my own experiments, but Amazon could easily do that for you, becoming your own personal expert on your own specific individual health.
This approach is of course not limited to sleep apnea. It could be applied to many chronic diseases, like skin conditions, or joint pain, or muscular issues – or more serious problems like diabetes, where monitoring tools that work via phones are already available. In particular, it seems well-suited to managing digestion issues which plague millions of Americans. Currently, a lot of medical treatment is already hit-and-miss. Doctors give you something to try, then try something else when it doesn’t work. The difference is the granularity and the reporting. Further, the US spends billions on useless treatments, and this new approach is ideal for identifying expensive treatments that don’t work: for example, it could help people find specific supplements that work for them, eliminating many others.
In the aggregate, personal experiments could radically advance treatment. Imagine if Alexa was able to aggregate the data from thousands of individual sleep apnea experiments. It could quite quickly identify commonalities – groups for whom specific treatments worked best (or indeed worse). It could also rule out solutions that worked for no-one, and highlight those that might be prioritized. It would in effect be running an endless series of A/B tests (in the language of software development). They would not be RCT’s, although maybe subsequent RCT’s would be a useful way to confirm findings. But Alexa-collated experiments would be much quicker, much cheaper, and much more agile than any RCT.
Other companies for both the technology sector and healthcare have ambitions here too. But because Amazon has such an enormous customer base, very high levels of customer trust, and its existing mass of in-home health-related assets (in particular Alexa), Amazon is uniquely well-positioned to drive the next steps into the era of personal medicine.
Of course there need to be privacy controls. Amazon cannot be allowed to simply suck in all of my data and spit out ads, or worse still sell the data or use it when Amazon (inevitably) gets into the health and life insurance business. Personal information like this is very touchy, and HIPPA will probably need to be amended to protect us all.
But, on balance, there will be a day soon when our personal health care AI is waiting in our pockets to meet our specific needs.
Dr. Robin Gaster is the CEO of Incumetrics and a visiting scholar at George Washington University Institute for Public Policy. He is the author of Behemoth – Amazon Rising: Power and Seduction in the Age of Amazon. For more information, please visit, www.robingaster.com.