The Internet of Healthy Things

This year marks the 10th anniversary of the publication of my first book, The Internet of Healthy Things. To mark the occasion, I decided to take a trip down memory lane and reread it. This book was about predicting the future of healthcare delivery, specifically as it involved connected sensors and devices, so I’m hoping you’ll take a look back and give me and my coauthors a score. How did we do?

I must begin with a disclaimer (or some may see it as an excuse). I like to illustrate the challenges of predicting the future using the cult classic Blade Runner as an example. This Ridley Scott classic film, released in 1982, looks 37 years into the future, to 2019. One noteworthy scene shows Harrison Ford’s character making a video call (accurately predicted) from a phone booth (missed prediction) to a woman he has developed feelings for. If my coauthors and I were as accurate as Ridley Scott, I will know we’re in good company!

In the coming months, I plan to devote multiple blog posts to the topic of “How did we do?” and discuss several predictions we made in the book in depth. Stay tuned for detailed updates.

In the meantime, here is a collection of my first impressions of my recent reading.

In writing the book, my favorite part was Chapter 1, 20/20 Foresight. The essence of that chapter became fodder for a stump speech I gave while doing an informal book tour. To summarize, a software agent called Sam checks in with me by voice and text several times a day, encouraging me to make healthy choices (eat fruit instead of a cookie; park my car farther from my destination to get more steps, etc.). Sam is informed by my personal internet of things—my tracking data from GPS, mobile purchasing data, and my electronic health record. As we noted in the book, this was a completely fanciful idea in 2015, but today, thanks to technologies like text-to-speech, multimodal, and generative AI, there are very Sam-like examples on the market. I’d say we got this one mostly right.

On the downside, much of the case we made for change was based on the assumption that by now, healthcare providers in the US would be primarily compensated through value-based payment models rather than traditional fee-for-service models, covered in Chapter 3, The Big Shakeup. However, this has not come to pass, at least not as we envisioned it. This serves as a humble reminder that things move slowly at best when it comes to healthcare financing. As someone wiser than me said about the $4.9 trillion spent on healthcare, “Any dollar saved is a dollar of someone’s income lost.”

In Chapter 4, The Hardest Sell, we talked about how chronic illnesses in the US are often linked to lifestyle choices and how difficult it is to change habits. We sincerely believed that feedback loops from wearables data and personalized feedback (covered in Chapter 7) would get us further than it has. Currently, obesity is seen as a disease that can be treated by a new class of pharmaceuticals (GLP-1s) with less focus on lifestyle change as the only way to get there.

In Chapter 5, The New White Coat Anxiety, we talked about provider burnout, and sadly, I think that has only gotten worse.

Chapters 8 (Try a Little Dopamine) and 9 (Making Data Actionable) emphasized how we could learn from mobile phones’ addictive properties and create health apps that were similarly appealing. This was not easy, and I think it is still a bit of a holy grail. We fell into the trap of conflating the joy of scrolling through games and social media with efforts to improve health, particularly chronic illness, the latter of which is infinitely more difficult.

In Chapter 10, The Reinvention of Big Pharma, it was speculated that “patent cliff” fears would push pharma towards more app/molecule innovations to improve adherence and efficacy. Neither has come about on a large scale.

Likewise, in our exploration of digital therapeutics (Chapter 11, The Digital Rx), we predicted a much more substantial presence of this category by now. However, it has had challenges, from visible corporate failures to an elusive business model.

I’ll also explore a few interesting trends that have evolved over the past ten years, such as the number of innovative companies featured in the book that are no longer in business. They’ve either been swallowed by acquisition, failed, or pivoted out of telehealth. I plan to dive into this in a future post. Likewise, many of the people we interviewed have left healthcare entirely. I’ll try to catch up with as many of them as possible to get their perspectives on the last ten years.

So, future blogs will expand on many of these observations and predictions. In the meantime, consider your own predictions from 10 years ago. What surprised you? What disappointed you? Let me know.