Is Autonomous Driving Healthcare’s Most Important Competitor?

While I’ve spoken extensively about how healthcare is not paying enough—if any—attention to the technological changes that threaten its business model, I haven’t talked much about improvements in auto safety, including Tesla Full Self-Driving (FSD) and similar efforts in “autonomy” (i.e. autonomous driving).

Let me correct that with this post.

In 2024, U.S. traffic deaths dropped nearly 4%, the sharpest single-year decline in half a decade. The National Highway Traffic Safety Administration (NHTSA) credits this trend in part to technologies like automatic emergency braking (AEB), which will be mandatory on all new light vehicles by 2029. NHTSA estimates that AEB could prevent 360 deaths and 24,000 injuries annually once fully deployed.

https://waymo.com/safety/impact/

That’s before you even factor in what’s coming next: widespread autonomous driving. Tesla’s Autopilot — definitely not yet a fully autonomous driving system — already reports one crash for every 7.4 million miles: seven times safer than the U.S. fleet average. Waymo’s driverless fleet in Phoenix has now driven tens of millions of miles with zero at-fault fatalities. These systems are getting better, quickly. They don’t speed. They don’t text. And they don’t fall asleep at the wheel.

And even now, before full autonomy is widespread, the downstream effects of safer driving technologies are already being felt—just not yet on hospital dashboards.

For 2019–2020, an average of 3.8 million emergency department (ED) visits for motor vehicle crash injuries occurred annually — about 3% of ED visits. And car crashes are not low-cost visits. They trigger trauma activations, CT scans, orthopedic surgeries, ICU stays, and weeks or months of rehabilitation.

In 2022, motor vehicle accidents in the US resulted in over $470 billion in total costs, including medical costs and the cost of lost lives, according to the CDC.

Which is exactly why a slow decline in motor vehicle trauma should be setting off alarms in every hospital boardroom.

Trauma, orthopedics, imaging, rehab—many of healthcare’s most dependable, well-reimbursed services depend not just on illness, but on accidents. And no single type of accident has been more reliable, more predictable, and more lucrative than the car crash.

Autonomy changes that.

Not overnight. But incrementally, and often invisibly. There’s no press release saying “trauma cases will drop 15% this year.” There’s just a software update. And then another. And another. Every version pushes trauma volumes a little lower.

If you run a trauma center, your real competitor might not be the hospital across town—it might be the software quietly reducing your patient volume from the outside.

And it is a major threat. Trauma centers are high fixed-cost operations. They can’t scale down neatly when volume dips. You still need the surgeon on call, the CT scanner, the blood bank, the full staff. When volume becomes unpredictable, the economics start to break.

Healthcare tends to expect disruption to look like a healthcare competitor—CVS Health, Walmart, Amazon Clinic. But true disruption rarely comes from within the market. Blackberry didn’t fall to another mobile phone company, it fell to Apple — a company that had never made a phone. Taxi companies didn’t fall to another transport company. They fell to software layered onto private cars.

Healthcare’s trauma volumes may fall to something even simpler: safer roads. And any strategic plan built around growing orthopedics, expanding trauma capacity, or maximizing downstream imaging needs to be re-examined through the lens of this shift.

What if car crashes drop 20% in five years — from software updates?

If you’re a healthcare executive, or board member, you might not need need to change your mission. But you do need to change your assumptions. You can’t control the crash rate — but you can control how prepared your system is for the rapidly-approaching world in which crashes are rare.

References:

• NHTSA Final Rule on Automatic Emergency Braking (AEB)

• Tesla Autopilot Crash Data Q1 2024

• Waymo Safety Impact Report

• Overview of Emergency Department Visits Related to Injuries, by Cause of Injury, 2017

• Emergency Department Visit Rates for Motor Vehicle Crashes by Selected Characteristics: United States, 2019–2020

The Empowerment of Consumers for Health: A Long Trend, Accelerated by AI

I recently published an editorial in American Family Physician titled “The Empowerment of Consumers for Health: AI Accelerates a Long-Standing Trend.” While headlines often frame artificial intelligence (AI) as either an existential threat to physicians or a helpful clinical assistant, I argue that both views miss the broader context: AI is the latest in a series of technologies that empower consumers to manage their own health—often without a doctor at all.

And this didn’t begin with ChatGPT. For decades, consumers have used online search engines, wearables, and over-the-counter medications to bypass the traditional gatekeepers of care. AI simply supercharges a longstanding trend: the democratization of health knowledge and decision-making.

“As with OTC drugs, the rise of AI represents another step toward empowering consumers to take control of their health decisions.”

What happens when free, always-on tools help patients adjust their insulin, distinguish between a cold and pneumonia, or monitor key metrics continuously rather than once a year? The answer isn’t a dystopian future without doctors—but it is a future where clinicians must reorient their value toward what cannot be automated.

In the piece, I encourage physicians to embrace AI, not fear it—to find new roles, contribute to the development of patient-centered tools, and show the unique value only human clinicians can provide.

If you’re a health leader, technologist, or clinician, I’d love to hear how you’re navigating this shift. The question is no longer whether change is coming—but whether doctors play the role of leader or observer.

🔗 Read the full article in American Family Physician:

https://www.aafp.org/pubs/afp/issues/2025/0300/editorial-artificial-intelligence-consumer-empowerment.html

In the Future, You'll Need Your Doctor Less

What If Healthcare Just… Fades?

What happens to healthcare when obesity goes away?

Most discussions of disruption in healthcare assume the healthcare system remains essential — just reshaped. Virtual visits replace office visits. AI handles documentation. Automation reduces friction. But the assumption is always that the care is still needed.

What happens when it isn’t?

Some of the most significant disruptions now emerging aren’t aimed at healthcare, but may make large parts of it unnecessary.

Prevention That Sidesteps the System

For example:

• GLP-1 drugs may reduce obesity, diabetes, and hypertension across entire populations. In fact, in 2023 the US population obesity rate declined for the first time in a decade — and one leading theory attributes it to the effect of GLP drugs.

• Self-driving cars could cut motor vehicle trauma by 30% or more. RAND estimated back in 2017 that even a 10% decrease in accident rate could save “hundreds of thousands of lives”. Meanwhile, even current technology promises a much greater reduction, with Waymo reporting a 57% decrease in police-reported accidents compared to human drivers.

• AI therapy chatbots are already showing promise for mental health treatment, and could dramatically lower the cost of therapy — and might prevent mental health crises before they begin. And they may just be the thin edge of the wedge, presaging the automation of all medical conversations where only information is exchanged.

Endocrine Disruptors

Each of these innovations reduces the need for healthcare, rather than streamlining its delivery or improving its process. And yet few health systems — actually, none that I am aware of — are modeling what happens when demand drops dramatically, not for elective procedures but for entire categories of care.

Food companies have run scenarios to prepare for GLP-1-driven shifts in consumption, and are already rolling out products tailored to GLP users. Where are the equivalent conversations inside healthcare?

If the number of diabetic patients drops by 20% (a conservative estimate, given the effectiveness of GLP-1 agonists like Ozempic), what happens to the business model of the average hospital? Will we need fewer endocrinologists — or none at all? What happens to primary care visits (already drastically declining) if hypertension declines by a similar percentage? What happens to orthopedics and emergency medicine if autonomous vehicles mean car crashes plummet by 50? Who owns prevention — and what happens to the institutions built on managing failure to prevent?

Failing to Plan is…

Healthcare leaders need to consider, in a world where health problems are increasingly prevented, not treated — what’s left for the system to do? I’ve spoken with hundreds of healthcare leaders in the past five years — including dozens of CEOs — and not one has mentioned the kind of “best case / worst case” modeling now common in the snack food industry.

If healthcare is going to meet this moment, it needs to do better.

And yes, there’s something ironic about hospitals taking planning cues from potato chip companies. But maybe that’s exactly what needs to happen.

---

Much of this post has focused on technologies that reduce the need for healthcare by preventing illness or injury. But the most widely discussed disruption today — generative AI — may reduce the need by eroding healthcare’s monopoly on information and expertise.

From diagnostic chatbots to at-home guidance systems, AI is already starting to displace parts of the care experience.

I’ve written about that in previous posts — and I’ll return to it soon.

Disruption for Doctors 2: Healthcare Examples

Recap of part I: disruptors are worse, not better

In my last post, I introduced the concepts of innovation developed by Clayton Christensen of Harvard. In Christensen’s paradigm, “sustaining” innovation enables incumbent organizations to better please their existing customers, while “disruptive” innovation weakens incumbents by creating new markets with cheaper but arguably worse technology.

As an example of “worse” disruptive technology, I talked about Netflix, which originally sent customers DVDs by postal mail. That seemed ridiculous to many who liked being able to just walk into a Blockbuster video store and then walk out with a video in a short time.

And the incumbents at Blockbuster apparently laughed and laughed . . . but Netflix was able to siphon off Blockbuster customers who were more price-sensitive. Then, when Netflix adopted streaming technology, they took all the remaining customers because at that point they were both cheaper AND faster.

But healthcare is not video streaming, so what about some examples of disruption in healthcare?

Non-IT-based healthcare disruption

There has been a lot of disruption within healthcare in the last decades; with some of it mostly related to information technology (IT) and some not. Let’s look first at some of the non-IT stuff.

Some examples:

• doctors getting disrupted by ancillary providers like nurse practitioners, who have many fewer years of expensive training, and are paid less

• primary care clinics and emergency departments getting disrupted by urgent care centers with a limited menu of services, and without the legacy costs of giant hospital-centric systems

• specialists getting disrupted by other specialists (see next section, below)

Note that, as with our Netflix example, the disrupters are arguably worse in certain ways than the doctors they are trying to replace (sorry, “augment” 🤣). It’s hard to argue, for example, that nurse practitioners are better than primary care doctors. The important thing, however, is that they are good enough for some section of the patient population — and that they are cheaper.

Also, although these disruptive innovations aren’t mostly related to IT, they are dependent on the IT innovations of the last 40 years: it wouldn’t be so easy to run an efficient urgent care center without inexpensive personal computers, etc.

A simple menu means costs can come down.

Example of non-IT healthcare disruption: heart disease treatment

Back in 2000, in an article entitled “Will Disruptive Innovations Cure Health Care?” Christensen himself provided an example of healthcare disruption. He and his coauthors talk about coronary angioplasty (or PCI, for “percutaneous intervention”), which enabled cardiologists to treat heart disease patients by inserting tiny tubes called stents into blood vessels — instead of requiring cardiac surgeons to perform cardiac bypass grafts (CABG). This is disruptive technology, for sure, and it’s a good illustration that disruptive technology doesn’t have to be information technology.

PCI didn’t eliminate heart surgeons, of course, but it did drastically reduce their activities: between 2001 and 2008, the annual rate of CABG in the US went down by 30%! So the incumbents (cardiac surgeons) lost a lot of revenue to the disruptive practitioners (interventional cardiologists) doing the PCI.

Keep in mind that CABG operations were, and are, better in certain circumstances but the disruptive PCI was generally cheaper because cardiologists are cheaper than cardiac surgeons, and PCI can often be outpatient. So the general idea of “disruption by worse, but cheaper” holds for this example.

The latest disruptor?

Interestingly, more recent data to 2016 demonstrated a roughly 40% decrease in both CABG and PCI — possibly due to more effective medicines (like statins and beta-blockers) reducing the need for surgery. So perhaps medical treatment for heart disease is now disrupting PCI, which previously disrupted CABG? Which might shift revenue back to primary care providers, whether doctors or nurse practitioners or other.

IT-based healthcare disruption

Disruptor of many things

Disruptor of many things

The reason that nowadays we focus on IT when we think about disruption is that for about 40 years, most business disruption in the world has been driven by the IT revolution (further reading: Why Software is Eating the World).

Think about the efficiencies and cost savings made possible by the PC, the internet, cloud computing, and the mobile phone.

Now think about the fact that healthcare has really only adopted one of those innovations: personal computers. Ouch.

Which means that companies that are very, very good at IT are turning their attention to healthcare to see if they can begin picking off the low-hanging fruit from set-in-their-ways old-school health systems. And this includes those using the very latest technology: artificial intelligence (AI).

Some examples:

• efficient lower-overhead systems (like Walmart Health) disrupting hospital-based systems (AND the urgent care companies!) with lower-cost systems that provide only the most commonly-needed services, and that can leverage their enormous portfolio of existing stores for office space. Also remember that Walmart got to be Walmart by being really good at IT (for supply chain management): we can expect efficiencies that most hospital systems can’t approach.

• deep-pocketed tech companies, like Amazon Care, disrupting primary care by using tech to run clinics at lower cost. How can Amazon be successful? By using the same online tools they use as the biggest online retailer in the world and, less well known to the public, as one of the leading providers of cloud computing services to other tech companies, via their AWS division. And they are on a healthcare spending spree lately, having just purchased One Medical [Note: the day after publishing this, Amazon announced they’re shutting down Amazon Care and focusing on One Medical].

• AI-based tools pulling some services away from expensive specialists, with one example being IDx-DR (see next section, below).

These IT-based disruptors are trying to use IT to create simpler, easier to use, cheaper versions of existing healthcare services.

Example of AI disruption: IDx-DR

Digital Diagnostics is a company based in Coralville, Iowa, far from tech centers like Silicon Valley or Boston. Using artificial intelligence computer vision techniques, they’ve built IDx-DR: the “first and only FDA authorized AI system for the autonomous detection of diabetic retinopathy.”

Translated, that means they have a machine that can take pictures of your retina and determine if you have diabetic retinopathy (DR, a debilitating problem that often occurs in poorly controlled diabetes).

Before IDx-DR, the only way to diagnose DR was for a very highly-trained and highly-paid ophthalmologist to look at your eyes. With Idx-DR, the diagnosis is automated and requires no input from any doctor, much less an expensive specialist.

This is the first machine capable of making a medical diagnosis by itself, and according to the website is “now part of the American Diabetes Association’s Standard of Diabetes care”.

Interestingly, it is marketed as a tool for primary care clinics, who can now avoid sending diabetic patients to expensive ophthalmologists for this diagnosis. That is a boon to primary care docs (and their patients) — but with 37 million diabetics in the US alone there is no real technological reason why this shouldn’t eventually find its way to a drugstore near you, right next to that automated blood pressure cuff.

Used to require a doctor

Also used to require a doctor

Example of AI disruption: ChestLink

Another great example of AI-based disruptive innovation has been developed by Oxipit. Their ChestLink app, which is approved by European regulators but not yet the FDA, uses AI to read chest x-rays. It is apparently sensitive enough to identify the presence of problem, but not (yet) as good as a human radiologist to identify what the specific problem is.

ChestLink’s main use, as a result, is to automate the reading of the up-to-80% of chest x-rays that are normal, freeing up radiologists to focus on those images flagged by the software as suspicious. Note again that the software isn’t necessarily as good as a radiologist in identifying a specific problem, but it is good enough for a very common task that takes up a lot of human radiologist time.

How is this disruptive? Well, because using the software to verify x-rays as normal is so much cheaper than using a radiologist for the same purpose:

1. rich countries with radiologists won’t need as many, so the cost of this one small facet of healthcare (i.e. reading chest x-rays) will go down.

2. in poor countries, the software isn’t competing against radiologists, it is — in Christensen’s terms — competing against “non-consumption.” It can thus create a new market for the use of chest x-rays, bringing that beneficial medical technology to many more people.

From https://oxipit.ai

From specialists to generalists, from physicians to nurse practitioners, from hospitals to supermarkets

In Christensen’s 2000 article (echoed later in his 2016 book The Innovator’s Prescription) Christensen presciently wrote about many of the now-established trends in healthcare:

We need diagnostic and therapeutic advances that allow nurse practitioners to treat diseases that used to require a physician’s care, for example, or primary care physicians to treat conditions that used to require specialists. Similarly, we need innovations that enable procedures to be done in less expensive, more convenient settings—for doctors to provide services in their offices that used to be done during a hospital stay, for example.

All of this, of course, is commonplace in the healthcare of 2022: urgent care centers staffed by nurse practitioners, outpatient surgicenters, more techs working throughout healthcare.

But Christensen wrote that in the world of 2000: Google was 2 years old, AI was still frozen in a decades-old “winter”, and the iPhone existed only in the mind of Steve Jobs. The advent of two decades of consumer technology has not only accelerated the healthcare changes that Christensen envisioned, but also accelerated something he doesn’t seem to have thought much about: selfcare. That is, the ability of the consumer to treat their own illness, and to maintain their own health.

And in my next post, I’ll talk about healthcare moving not from doctors to nurse practitioners, but from nurse practitioners to . . . us.

Stay tuned.

---

This post draws on themes from my keynote talks.

Disruption for Doctors 1: What’s Disruption?

We’re number 46!

Healthcare in the United States is a $1.27 trillion dollar industry known for

1. very high prices

2. terrible customer service (long waits, short visits, poor coordination)

3. impossible-to-understand billing

4. antiquated information technology (e.g. using fax machines in 2022)

While the saving grace for a long time was that the healthcare system got outstanding results, that doesn’t seem to be the case anymore. While the US spends much more on healthcare than other rich countries, for example, the country is number 46 for life expectancy at birth — right behind Estonia.

And a recent study published in the Journal of the American Medical Association demonstrated that for many common health issues (e.g. colon cancer, heart attack, infant mortality), even the richest Americans often had worse healthcare outcomes than the average citizen of many European countries.

Ripe for disruption — whatever that is

Whenever you have a very expensive product with major problems, there is always an opportunity to find ways to improve or replace it. One important type of replacement using technology is called “disruption”, and it is one of the main strategies that Big Tech companies and others use to take over major segments of whole industries (see: advertising, retail, music, travel, photography, etc).

Unfortunately, most doctors, nurses, PAs, techs, and others aren’t familiar with the term — and are unaware of how technological trends have already begun disrupting their current business models.

The purpose of this and some following posts is to give folks working in healthcare a framework to better see what’s happening in healthcare and better prepare for the future — a future which will be very different from the traditional doctor-and-hospital-centric healthcare model.

What does “disruption” mean?

If the fire alarm goes off at the grocery store while I’m looking for tomatoes, that would definitely “disrupt” my shopping — but this is not the disruption I’m talking about. Likewise, I don’t just mean the introduction of something “new” or “innovative.” And I definitely don’t mean a new style of denim shorts:

Ah . . . no.

I’m using the concept of disruption as defined by the late Clayton Christensen in his incredibly influential book The Innovator’s Dilemma (TID), originally published in 1997. TID talks about how technological change can sometimes improve existing companies’ products, while other times putting such companies out of business.

The Bible of Disruptive Innovation

As a way to explain these two very different outcomes Christensen divides tech innovation into two categories: sustaining and disruptive.

Sustaining innovations

A sustaining innovation is a new technology that helps existing companies (“incumbents”) make their products better for their existing customers.

A great innovation — but not a disruptive one

LED light bulbs are a great example of a sustaining innovation. They’re definitely way better than incandescent bulbs — much longer-lasting, way more energy efficient, cooler — and they’ve helped big incumbent light bulb manufacturers like Philips and GE to make better products, and serve their customers better, and to increase their profits. This sustaining innovation makes incumbents more profitable.

Other examples of sustaining innovation are not hard to find: many of the products we use everyday get better over time. Detergent pods? New versions of your phone’s operating system? Bigger (flatter!) TV screens? Better cushioning material in your running shoes? Self-checkout at the grocery store? Waterproof/breathable rain gear?

Sustaining innovation example #3,452,778

None of these innovations are putting anyone out of business. They’re “just” incremental improvements that make useful products even better.

Disruptive innovations

A disruptive innovation is a new technology that lets new companies make a product or service more affordable and accessible to more people in a way that puts incumbents out of business.

“Telephone did not come into existence from the persistent improvement of the postcard.”

— Amit Kalantri

Characteristics of disruptive innovations usually include:

1. they are typically worse in many respects than existing tech (this one is a bit counterintuitive, but read on)

2. they are typically better in at least one respect, usually some combination of price and simplicity

3. by being cheaper, or simpler to use, they create a new market of users that couldn’t afford to participate using older technologies

4. they are ignored — or laughed at — by incumbents because they don’t (initially) make much money. Plus, they’re clearly worse (see #1, above).

A great example of disruptive innovation that most of us have lived through is Netflix’ original business model (before they became a streaming giant). You might remember that when Netflix came online in 1997 there was no streaming (the internet wasn’t fast enough yet): Netflix was a DVD rental company. They pioneered a new way to rent DVDs, by ordering them online and receiving them through the mail, which was in direct competition with Blockbuster and other physical video rental shops.

How was this classic disruption? Let’s go through the points:

worse — the first thing I thought when Netflix came out was “who wants to wait 3 days to get a DVD in the mail??” Most people liked the instant gratification of going to the video store and walking out with a movie a short time later. Netflix was definitely much worse in this respect, and was the butt of many jokes when it started.

better — the thing people hated most about Blockbuster and other video retail shops was . . . the late fees. You’d get the DVD or VHS tape for cheap but if you forgot to return it on time you were nailed with a big late fee. In fact, according to Netflix lore, Netflix founder Reed Hastings got the idea when he forgot to return a copy of Apollo 13 on time and got hit with a $40 late fee. Netflix had NO late fees: you could keep a DVD as long as you wanted and just paid the same subscription fee each month.

new market – the market for Blockbuster was obviously limited to places with a Blockbuster store. Netflix, on the other hand, could bring in more customers because they were (1) cheaper and (2) available to anyone in the US that could get mail (i.e. everyone).

ignored/laughed at — a lot has been written about why Blockbuster didn’t/couldn’t adapt to the challenge from Netflix. Christensen would say that it’s because Netflix was offering a mail-order subscription service that — at least initially — Blockbuster’s customers weren’t asking for, and Netflix wasn’t making much money doing it. In fact, in 2000, the Netflix founders tried to sell Netflix to Blockbuster, and they remember that at that meeting the Blockbuster CEO “was struggling not to laugh.”

Netflix initially got subscribers who were angry about late fees, or who didn’t have a good video shop nearby, but as they got more popular their business grew. The last straw was in 2007, ten years after Netflix started, when they announced that they would start streaming movies.

This removed the last objection anyone had to Netflix (having to wait for the mail), and actually made them a faster option than Blockbuster. Three years later, as everyone got used to picking and immediately watching movies without getting up from the couch, Blockbuster went out of business.

Other examples of disruptive innovation include social media — which has put many traditional news media like newspapers out of business — and electronic messaging like email, WhatsApp, and Skype, which has nearly eliminated traditional paper-based messaging. Not to mention the smartphone — which by making computing simpler and cheaper (especially with low-cost Android phones) has brought BILLIONS of new computing users into the market.

Sometimes people argue about whether a new technology is sustaining or disruptive, and the answer can depend on who, exactly, is getting disrupted. The iPhone, Tesla, Uber . . . all of these clear innovations have had people arguing both sides. To read more about the example of Tesla, try “Is Tesla Disruptive” by Ben Evans. To read why even Clayton Christensen, the father of disruption theory, got the iPhone’s disruptive potential wrong, try “What Clayton Christensen Got Wrong” by Ben Thompson.

So what does this have to do with health?

When you work in a very expensive system with arguably poor results, it’s a natural question to think “how can we improve this?”

If you work outside the system, and you understand disruption theory, the natural question is “how can we disrupt this system?”

These questions are being asked throughout healthcare, and by companies outside healthcare. We’re seeing sustaining innovations like better drugs and electronic medical records, as well as potentially disruptive innovations like urgent care centers run by Walmart, and smartphone apps that treat depression without a human therapist

In my next post I talk about the many, many ways that information technology is acting as a catalyst for both sustaining AND disruptive innovations, and the implications for traditional healthcare.

---

This post draws on themes from my keynote talks.