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Henry Ford, the Model T, and Digital Health

By TREVOR VAN MIERLO

Most of us know the story of the Model T – but what’s often overlooked is how it applies to other industries, especially digital health. Let’s revisit:

In the early 1900s cars were custom built. You’d meet with a consultant, design the car, place your order, and wait for months for delivery. Once your car was delivered, it was difficult to operate. Many owners hired chauffeurs because at the time, cars required technical know-how, constant maintenance, and a fair bit of strength (power steering wouldn’t arrive for decades).

Then came the Model T in 1908, which led to Ford developing his assembly line in 1913. He recognized a problem in the industry and saw an opportunity. He saw the opportunity for scale:

  • Standardization: “Any color, as long as it’s black“
  • Mass production = affordability: Prices dropped from $850 in 1908 to $300 within a decade
  • Accessible ownership: anyone could walk into a Ford dealership and drive away 
Left: Early car assembly (pre-Ford) Right: A leading digital health interface, 2000

On the right side of the above image is a cutting-edge digital health program from August 2000. I know it well – because I helped build it. Since then, I’ve worked on well over 100 digital health interventions. Probably closer to 200. Here’s the thing: what’s inside hasn’t changed very much. Behavioral science doesn’t move that quickly (although my recent work in AI is changing that).

And yes – digital interventions look better, are easier to navigate, and coding languages have evolved – but practically, digital health is still building custom cars – not Model Ts. That’s why tens of millions can’t open a browser and get the help they need.

What’s Blocking Digital Health’s Model T Moment?

1. Enterprise Sales (Death by Pipeline): Most digital health tools are sold through enterprise channels: RFPs, procurement departments, tenders, security reviews, and legal teams. The average sales cycle is 6-18 months. That’s fine for a $5M contract, but it’s lethal for a $50,000 contract. The problem isn’t the product – it’s the process.

2. The Vanishing Champion: I’ve experienced this dozens of times, and I’ve taken deep breaths watching it unfold on webinars: a digital health company demos their solution alongside a client champion. Priorities shift. The champion leaves. The reference project dies. Most contracts aren’t lost on merit – they’re lost to turnover.

3. Healthcare Pricing ≠ Software Pricing: Most patient-facing tools are priced like services, not products. That’s a symptom of the enterprise sales trap. Vendors charge annual fees regardless of usage. Clients expect hand-holding for these custom products. Pricing needs to reflect modern SaaS models – freemium, tiered access, per-user billing.

4. Static Products in a Dynamic World: Consumer software updates weekly – sometimes daily. Digital health tools? They launch, then stall. Feedback loops are weak. There’s no culture of iteration, and no expectation of continuous improvement.

5. Nobody Markets to the User: The best-designed tools fail if no one uses them. Lack of engagement is a systemic issue, yet many programs are launched without onboarding plans, email campaigns, or even prewritten content for TikTok or Instagram. Users don’t know what the tool is, why they received access to it, how they access it, or how it fits into their care. That’s not a product issue – it’s a marketing failure.

We Need to Build the Systems, Not Just the Tool

Henry Ford didn’t invent the automobile, but he’s remembered because he built a system. He looked beyond the engine, the chassis, and the tires. He focused on standardization, distribution, and access.

Digital health needs the same. Right now, too many solutions are trapped in a loop – custom-built for small populations, sold through enterprise channels, with no realistic path to scale.

The Good News? We’re Close

Cloud infrastructure, AI, and behaviorally intelligent platforms are finally catching up. We can now personalize at scale, launch instantly, track engagement in real time, and iterate fast. But to get there, we have to let go of the custom-built carriage mindset and embrace the assembly line. That’s not a compromise in quality – it’s a commitment to reach.

  • We don’t need more pilots – we need platforms.
  • We don’t need more bespoke builds – we need scale.

Digital health doesn’t have a technology problem – it has a delivery problem.

Until we achieve that, we’re just making nicer carriages – while the world waits for its Model T.

Dr. Trevor van Mierlo has built mental health and patient support products for more than two decades and is the CEO of Evolution Health

Beyond Stigma: Why Addressing Maternal Mental Health Means Confronting Systemic Failures

By EMILY JOHNSON

Imagine you’re an executive at a large health system in a major metropolitan area. One morning, you wake up to a missed call and a voicemail from your PR leader. It’s urgent: one of your employees–who was also a patient and a member of the organization–has unexpectedly died by suicide.  Their family is furious.

You follow up and learn that this wasn’t just any employee. It was a young leader you had worked with only a few months ago. You had regular meetings with them and had been serving as a mentor. You had been impressed by this young person’s drive, enthusiasm, analytical skills, and ability to build relationships. You believed they were on the path to being a strong leader in health care. But not anymore. Now, seemingly out of nowhere, they are gone.

You’re shocked. You’re devastated. You’re confused. You demand an immediate safety review to understand what happened and why.

The patient safety team moves quickly to investigate, and they discover that the patient was a young woman who had given birth to her first child just two weeks ago at one of your hospitals.

During her pregnancy she had disclosed to her primary OB that she was beginning to have panic attacks. The OB offered to start her on an antidepressant, but the patient declined. No referrals were placed. Red flag.

She delivered her baby after a 30+ hour labor culminating in postpartum hemorrhage. Anxiety was noted several times throughout her hospital stay. Her notes from labor say “patient acutely anxious and requesting “to be done.” Her discharge notes state “Difficulty coping with anxiety for past 1-2 weeks. Has been affecting her ability to bond with baby.” Red flag.

She was seen by a social worker, who shared with her a packet of information about postpartum depression. This person recalls the patient asking her “which of the numbers should I call if I need help immediately?” Red flag.

She presented back at the ED the day after her initial discharge with additional hemorrhage concerns. Her notes say “Patient is anxious, tearful, arriving in the ED hypertensive at 140/90, tachycardic in the 120s.” She was discharged with blood pressure medication. Red flag.

You learn that her husband tried calling the behavioral health department to make his wife an appointment, only to be told that the soonest they could get her in would be 6 weeks. He pressed and asked if there were exceptions for urgent OB patients and was told no. Red flag.

In the week leading up to her death this patient had been in contact with 3 OBs, a pediatrician, and a lactation consultant, saying things like “I am afraid of everything” and “I can’t eat or drink.” She had a positive EPDS flagging thoughts of self-harm. Big, bright, unmistakable red flag.

Phone records show that one night she tried calling the behavioral health appointment scheduling line, which was given to her by multiple providers as a 24/7 crisis line, at 2am. Red flag.

Her notes from the last time she was seen in the clinic state “she is not eating, vomits any food she eats and has diarrhea. She reports sleeping at most 4 hours a day.” She walked out of that appointment with only a prescription for hydroxyzine, which is similar to Benadryl. Red flag.

At 5:30am the next morning, her husband woke up and found that she was not in the bed. He looked over and saw that the baby was still sleeping peacefully in the bassinet. He panicked. He knew in his gut that something was wrong.

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Peter Yellowlees, AsyncHealth

Peter Yellowlees MD is CEO at AsyncHealth–this is a new company that is doing the intake interview for a psychiatrist or psychologist session. Peter demos how the AI agent asks questions, how a patient answers in real time. Then after submitting the answers, the AI creates both a full transcript in the back end, and then a summary which the clinician can use in advance of seeing the patient. You’ll see the real time transcript and patient summary. Very accurate and impressive. That saves a significant amount of time in the intake process and helps the patent get to the right type of treatment. It’s early days for Asynch Health, but you’ll quickly get the idea about how this use of AI might change one part of care–Matthew Holt

Robert Krayn & Georgia Gaveras, Talkiatry

Robert Krayn is the CEO and & Dr. Georgia Gaveras the CMO of Talkiatry. Robert and Georgia are quite the dynamic duo (she says, “He’s the money I’m the medicine!”). As a relative latecomer in the online mental health world, Talkiatry is trying to differentiate itself from the other big players like Lyra, Headspace, Brightside et al. It’s focusing on using psychiatrists as opposed to psychologists, counselors or coaches. This is both as an advertisement to patients but also they’ve set up a system that is much easier for psychiatrist themselves to join as employees and they showed me the way that patients get onboarded in their system, and how they get to that first appointment–in an average of 5 days!

Brad Kittredge, Brightside Health

Brad Kittredge is CEO of Brightside Health, which he co-founded with CMO Mimi Winsberg. They are a large online mental health group that aims a providing more access with higher quality. They have built their own technology stack and medical group, and are in network for about 135m lives. They also take patients from the emergency departments of health systems–as well as direct patient outreach for “standard” mental health conditions. Brad talked to me about measurement, quality and care improvement, including how they are using their algorithms to improve their clinicians’ prescribing accuracy. I also asked him where Brightside were in the process to, err, return at least some of the $150m they’ve raised back to their investors. Matthew Holt

Sara Ratner, Nomi Health

Sara Ratner is President of integrated Programs at Nomi Health. They work with employers and health plans to connect them to a network of providers (both telehealth and physical) who accept steep discounts in return for immediate payment. The employees in turn get no co-pay/no coinsurance. In addition they have an analytics company called Artemis which recommends care paths and a PBM to lower drug prices. Sara is trying hard to integrate mental health into their program too. Nomi raised $110m in 2022 and also made a decent amount in covid testing earlier in its life before pivoting.

Kris Engskov, Rippl

Kris Engskov is CEO of Rippl, a General Catalyst-funded company developing a wrap around care model around the primary care doctor for people with dementia. Their process is to help the family caregiver who is looking after the dementia patient and gives a ton of support to those caregivers which helps them be successful taking care of the patient at home. They start with diagnosis and use care navigators to build a care model face to face with patients. They’ve raised $52m and are nearly 2 years into serving a very neglected group of patients and caregivers–Matthew Holt

Mental Health’s Unfinished Digital Revolution

By TREVOR VAN MIERLO

In 2021, digital mental health and substance use startups attracted a record-breaking $5.1 billion in funding. Despite the surge, the promise of scalable, transformative digital health platforms remains unfulfilled.

Following the surge, investment plummeted. Unlike other industries that have been revolutionized by digital-first solutions, digital health struggles with models that fail to address cost, complexity, and access.

What we’re left with entering into 2025 are a smorgasbord of solutions clamoring to attach themselves to traditional enterprise incumbents (Health Insurance Providers, Electronic Health Records, Hospital Systems). These incumbents have achieved scale – but not the type of scale that digital health needs to flourish.

Investment in Digital Mental Health (2010-2023)
Digital Mental Health Investment (2010-2023)

Incumbents Build Deep, Startups Go Wide

Incumbent scale is infrastructure-heavy, slow, and linear, and focuses on deep integration within their established markets.

In contrast, startups aim for technology-driven, exponential, and global scale, leveraging digital platforms to serve millions of users quickly. While startups have the speed advantage, achieving scale similar to incumbents requires win-win partnerships and fundamental shifts away from established business models.

Incubent Scale vs. Startup Scale
Incumbent Scale vs. Startup Scale

The investment market does see the tremendous opportunity: a massive, growing global customer-base proactively demanding help as social stigma decreases. And as time passes, this customer-base grows exponentially with technology pervasiveness.

What investors see is unmet demand for mental health and substance use treatment, and a historic opportunity for digital health to step up and deliver solutions that are scalable, accessible, and affordable.

However, the delivery mechanism to these populations, though digital, is obfuscated through the blurred lens of incumbent purchasing power. We can’t get past incumbents’ size, their reach, and their connection to patients. In this common view, incumbents are the customer. This view is promoted by both industry and academia.

Continue reading…

Sean Bell, Spring Health

Sean Bell is head of new ventures at Spring Health, a very well-funded mental health company. They’ve built a tech platform that its providers (both contractors and FT employees) are on, and spend a lot of time using machine learning to match patients to therapists, to augment the care and also measure the impact of that care. Sean told me about both how Spring Health works and how much its grown, and what new specialized care is being introduced in 2025. He talks quick and we covered a lot of ground including the business of being a highly-valued private mental health company when there are some lower priced public companies out there. Interesting interview — Matthew Holt

Software Living in an Enterprise World: Why Digital Behavioral Health Can’t Gain Traction

By TREVOR VAN MIERLO

Let’s face it: for the past 25 years, digital behavioral health has struggled. Yet, we keep reinventing (and funding) the same models over and over again.

How It All Started

In the beginning (mid-1990s), a handful of developers, researchers, and investors envisioned high reach, lower-cost, highly tailored, anonymous interventions reaching millions of people with limited healthcare access.

The initial focus was never healthcare providers and insurers. These organizations were seen as too slow to adopt new technologies, and there was a general distrust of integrated care and insurers. Many digital health companies feared these organizations (and pharma) would leverage their power to learn from smaller companies, and then redevelop interventions internally.

Instead, the focus was on partnerships and B2C sales. Funding was easier to obtain from granting agencies, and there was ample development support flowing from sources like the tobacco Master Settlement Agreement (MSA). The primary concern was 1) whether the population could access these revolutionary tools and, 2) who would pay for them.

The Digital Divide

Back then, funders were often short-sightedly obsessed with the digital divide – the gap between people who had access to digital technology (mostly educated, higher-income earners in large cities) and everyone else. The argument was, “Why should we fund digital tools that will only benefit those who already have access to healthcare?”

Data was available, so academics armed themselves with ANOVA and relentlessly examined variables such as hardware costs, processing speed, age, gender, race, ethnicity, geography, income, and education. If you check Google Scholar, you can see the prevailing sentiment was that it would take decades for the digital divide to narrow, and new policy was desperately required to fix the problem (see: here, here, here, and here).

No More Excuses

Fast forward to 2024. According to a recent article in Forbes, there are 5.4 billion internet users worldwide (66% of the global population). In the U.S., 94.6% of Americans have internet access. Most US households have multiple devices, and according to Pew Research Center Research, 97% own a cellphone, of which 90% are smartphones.

As a Gen X’er who used a typewriter in college before upgrading to a Compaq Deskpro 286 from Future Shop (for about $400), my adult life has been a witness to the rapid progression of digital. Now, my 9-year-old daughter is teaching me how to play Fortnite (Epic Games), my 11-year-old is the only kid on his hockey team without a smartphone (this won’t last), and STARLINK allows me to chat face-to-face with my parents in rural Northern Ontario.

All aspects of technology are pervasive and accessible – but if you search Google or Bing for immediate, evidence-based behavioral help, you can’t get it. If you can find access it’s behind a paywall: through your employer (contact HR), health plan (call to see if you’re covered), or subscription ($19.99 per month).

That’s not meeting the original vision – and we have the technology. So, what’s the problem?

Continue reading…