Hype (& Companies) May be Fleeting, But Medical Device Wearables Keep Moving Forward
Kate Stephenson, PhD, takes a look at how wearables are shaping the medical device industry.
August 30, 2024
At a Glance
- Wearable medical devices are regulated based on their function rather than their form.
- The pandemic accelerated the use of wearables for telehealth, but long-term value & reimbursement challenges have emerged.
- Advancements in adhesive tech & data integration are improving wearable practicality, while AI plays a role in managing data.
There has been an ongoing love/hate relationship with wearables within the medical device industry for the last two decades. Are they going to disrupt us, enable us, or just make everything more confusing? It depends on who you asked, and in what round of the hype cycle you were in at the time.
If you ask Google what a wearable is, you will receive the accurate but unhelpful definition: “A technology wearable is technology that is worn on the body.”
From this, we can make the nearly equally unhelpful assumption that a “medical device wearable” is a “medical device that is worn on the body”. The ambiguity is not unfamiliar when a “medical device” can be anything from a wooden stick (tongue depressor) to a Linear Electron Accelerator (used in radiation therapy for cancer).
We’ve seen the evolving definition of “wellness devices” emerge to separate the step counters and smartwatches from the insulin pumps and hearing aids, then witnessed those same consumer products begin to pursue 510(k)s. Wearable device classifications in the Code of Federal Regulations include items as old as external pacemakers (appearing in the late 1950’s), to the latest over-the-counter Continuous Glucose Monitoring (CGM) systems.
US medical device regulation has no umbrella “wearable” category. Like implantable stimulation units, which address conditions from bladder incontinence to epilepsy with the same tightly sealed titanium boxes of electronics, indication trumps form factor in defining medical devices. The clearest examples of medical device wearables are those whose successful function is linked to keeping close contact with a patient’s body for long periods. These include diagnostics that rely on signals collected over days and weeks, drug delivery and therapeutic products with adaptive dosing, and prosthetics that improve or replace a body function.
At the peak of the pandemic, emerging medtech wearables were receiving emergency approvals for both sale and reimbursement to enable the rapid pivot to telehealth. The long-term impact of those technologies floundered once these approvals were rolled back at the end of the public health emergency.
We are seeing a resurgence in wearable interest with the fervor over Artificial Intelligence (AI) and Large Language Learning Models (LLM), as wearables are a means to deliver the large-scale data collection necessary to support those technologies. When the current hype of data grows cold, be prepared for aesthetically designed patches to address the “green field” of menopause and cognitive decline as interest in women’s health and aging disorders takes off. We are continuing to see startups boom and crash because there are fundamental assumptions in wearables that technology development alone cannot fix.
The great appeal of today’s AI models is the potential. Like miners rushing to hit it big, there is a temptation to believe that if we dig deep enough, and shift through enough data, we’ll eventually hit clinical gold. We’re relying on “brute force” research that seeks out patterns so complex we cannot explain them, in volumes of health data that can only be achieved with widespread wearable adoption. While some of these applications are conceptually sound, there is no guarantee that they will ultimately prove clinically useful. This is particularly troubling with wearable startups looking to solve problems on tiny, efficient microelectronics that are still being solved on larger-scale equipment.
For example, LLM AI algorithms have made massive strides in the accuracy of automated ECG (Electrocardiogram) reading in just the last several years. However, these rely on a full 12 lead electrode system wrapped around the body, not the diminutive 3-electrode patch. The idea that we will ultimately be able to replicate 12 lead functions (such as accurately identifying complex heart rhythm dysfunctions) with just 3 is based on conjecture and pitch decks, not clinical data.
Beyond clinical efficacy, one of the great experiments of the first round of telehealth-enabling wearables has been in reimbursement. Regulated wearable companies have fought for pricing equivalence to in-clinic services performed by technicians. We have also seen pricing based on the potential to reduce escalation expenses, such as minimizing emergency room visits. Results have been mixed as payers are developing their own policies for deciding the value of the technology. iRhythm is still reeling from the 2020 decision to reimburse their services at a fraction of the pricing they had promised their investors. As home health applications ranging from physical therapy to nursing wellness checks try to replace or augment human interventions with devices, expectations are being reset as to what those technologies will ultimately earn for their companies.
Those lowered returns are a sharp wake-up call for those expecting high-tech, high-touch experiences for patients that parallel the consumer tech world. While a robotics company like Intuitive Surgical can afford to hire Hollywood designers for their interfaces, a $10 (or even a $100) patch in a niche medical application has a much tighter budget. Fitbit has sold over 136 million devices since 2007.
Apple Watch, launched in 2015, has approximately 115 million users. These are general-use devices that have massive customer bases to support their design, development and maintenance. Even the biggest medical indications can’t touch those numbers. Proteus Digital Health, one of the first “smart patches” to get FDA approval, struggled to find a combination product market that could handle its $1,600 price tag before succumbing to bankruptcy in 2020.
However, if you can avoid the hype, there is hope. Having a front-row seat to these booms and busts, there are noticeable changes to how the new products are developing. Like the smartphone industry, the fitness tracker, and the smart watch, each new product launch builds on the existing industry infrastructure. Every new product being developed is more focused in its development, borrowing more from communal resources. Proteus Health was founded in 2001, six years before Apple launched its smartphone. While their indication choice and focus on pharma may have been a mistake, they also had no easy way to transfer their patch data back to the clinician. Today, every patient is expected to have a blue-tooth-enabled smartphone and we see Wi-Fi access as a health-outcomes critical resource.
The available options for skin adhesives were also minimal in the early 2000s. Patches had to be swapped daily. Adhesives used in clinic-based monitoring applications were not expected to last more than a day or two, and certainly not through showering and workouts. Compare this to 3M’s most recent adhesive offering with a 28-day wear time, up from the 21 days announced just two years previously. For iRhythm, getting their patch to stay on for a full 14 days in 2014 was one of their biggest engineering challenges. It was a challenge that was much smaller when the first Continuous Glucose Monitors (CGMs) came out only a few years later, also touting 14-day wear times.
In 2000, you needed to build your own data servers from the ground up and hire a team of security and HIPAA experts. Now, you sign a contract with Amazon Cloud Services. Integration access to electronic medical records has been vastly expanded since the HITECH act of 2009 and integration businesses are exploding as fast as the wearable companies themselves. AI, while not yet ready for diagnosing patients solo, is critical to managing the complexity of both the wearable data itself and the processes to keep it safe and secure. While federal policies may always lag behind the latest technology, we now have emerging frameworks for addressing them as they come along. Whether exploring partnering programs with Tech Giants, standing up the Digital Health Center of Excellence, or building mobile health tech into major public health initiatives like interim director Dr. Tarver’s Health at Home, there have been major investments in the necessary regulatory infrastructure.
It is exceedingly difficult for a first mover to pioneer a technology and survive long enough to remain a leader in the new market. However, instead of focusing on individual company’s performance, we should look at what they built on. There is a big difference between projects that succeed and fail on hype and branding, and those that struggled to address the major challenges in both their rise and fall. The first only makes headlines, the second is what makes our modern reality possible.
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