How Healthtech Companies Can Successfully Access the Self-Insured Employer Market

How Healthtech Companies Can Successfully Access the Self-Insured Employer Market

So, you have a new health technology that you’ve packaged into a hot product offering. You’re excited about your product. As you think about going to market, you practice reciting all the great things about your offering. This product’s going to take the world by storm! Your largest potential market: self-insured employers.

You’re not alone. The self-insured employer (SIE) marketplace is enormous. And with each year, more medium-sized and smaller employers are joining the fray. According to the most recent EBRI (Employee Benefit Research Institute) findings research, 78.5% of employers with 500 or more employees offered a self-insured health plan. That’s translates into more than 56,000 plans covering more than 75 million participants, according to a recent Deloitte study prepared for the Department of Labor.

However, self-insured employers are barraged by “next best thing” solutions touting a new technology that will revolutionize the marketplace in a new or unique way. Some recent examples include:

  • A new diagnostic blood test to help fine tune the treatment for certain kinds of cancer

  • A new application of telecommunications technology to optimize patient/provider interaction

  • Targeted pharmacogenomic testing for psychiatric therapeutics

  • A new stem cell treatment for joint injuries

  • A condition-specific self-management app

  • A new imaging technology that can be offered onsite.

Key Strategies That Drive SIE’s Business Goals

So how can you break through the noise and get attention in this crowded market? First, you need to understand what  self-insured employers are trying to accomplish. The four key strategies that usually drive SIE business goals for benefits are:

  1. Medical cost reduction through plan design
  2. Medical cost reduction through marketplace innovation
  3. Improved member engagement in health and wellness
  4. Improved workplace engagement and performance 

Self-funded health insurance plans enable employers to better customize plan and coverage options, as well as to better target cost-saving strategies. Naturally, employers struggling with escalating medical costs are looking for the next big thing. SIEs, in particular are sensitive to medical costs since they are spending “their own” money. 

To do this, employers typically choose one of two options: an Administrative Service Only (ASO) plan from an insurance carrier, or a Third Party Administrator (TPA) plan. ASOs tend to be more turnkey, offering ease of administration and more limited plan options. TPAs tend to be more flexible and enable employers greater choice in plan design and offerings. The distinction is important, as the appetite and feasibility for new solutions increases with greater employer flexibility.

How to Convince SIE’s to Adopt Innovation 

Many SIEs are willing to consider leading edge solutions if they can be convinced that the return on investment is worth the risk and the hassle. 

Understanding not just what your new product offers but how it aligns with what a particular SIE wants to accomplish makes all the difference in the world. Understanding employer cost drivers and identifying specific ways that those costs might be avoided or reduced is key to making a smart, targeted pitch to your potential customers.

Many healthtech companies promise medical cost reduction through marketplace innovation. But they often underestimate the level of detailed understanding of medical spending that SIEs and their advisors have. Increasingly, employers can influence cost trends and clinical drivers to an impressive degree.  Some of the key factors many SIEs consider include

  • Cost per member

  • Utilization trends 

  • Acute and chronic conditions 

  • Gaps in care 

  • Risk scores pharmacy/medical ratios for their plans.

These metrics can be further analyzed by company location, member type (employee, spouse and dependent), and by plan.

It is vital to understand precisely what metrics your new health product will impact, and how it will change them in new ways.

What the Self-Insured Employer Needs to Know From You

Do commercial medical carriers pay for your service? If not, why not?

Most SIEs have an insurance carrier, or some other plan administrator, process their medical claims. These carriers and administrators abide by a set of clinical policies that relate to medical necessity. Some policies may be developed internally, some externally. Some common examples include: 

  • Is your service  in accordance with generally accepted standards of medical practice?

  • Is it clinically appropriate and effective?

  • Is it not primarily for convenience?

  • Is it less expensive than an equivalent alternative service?

  • Is it endorsed or recommended by national medical societies and associations?

  • Does your technology have final approval from the appropriate governmental regulatory bodies, when required? (FDA approval, where applicable, is necessary but not sufficient to meet coverage criteria.)

  • Is your service covered by Medicare? While carriers are not obligated to follow Medicare policy for their commercial members, it is often considered in formulating clinical policies for commercial plans.

How will your health product disrupt the status quo? 

When considering a new diagnostic, therapeutic or behavioral change solution as part of an employee benefits plan, there are some basic questions you should be prepared to answer for a SIE:

  • What does the new capability offer?

  • What is the upside of offering the new technology?

  • What are some of the potential downsides?

  • Do the benefits outweigh the costs?

  • Is it medical necessary? Is it advisable?

  • What population is it intended for?

  • How will it be implemented and what are the costs associated with implementation? (I.e. does it require a blood draw or physician order, and if so are those baked into the solution and costs?)

  • What are the ethical and legal ramifications of including this in the benefits program? 

  • What’s the ROI or the VOI (Value on Investment)? Can you prove it?

  • Are any other employers doing this? Why or why not?

The Practicalities: What a Smart Self-Insured Employer Looks For

In addition to understanding the details of what you offer and believing that it will accomplish what you say it will, employers need some assurances about your own credibility. Here are a few additional questions they might have for you? 

  • Can you do what you say you will do, and do it well?

  • Do you have a proven track record?

  • What will the service experience for the employees? For their families?

  • What will we see from you?

  • What kind of reporting do you offer back to us?

Anticipating this piece of the conversation is vital for new healthtech disruptors: The more you can answer these questions truthfully and with confidence, the better your position to get to the next step.

Wherever possible, providing a predicted ROI is advisable (a range is acceptable). Assume that your SIE has a sophisticated understanding of ROI and be as specific as possible. Dollars spent on your product and program should be demonstrable by key indicators. Thinking through the “what ifs” shows you understand their world. An even stronger case can be made if you’re willing to put dollars at risk. 

How Healthtech Companies Can Successfully Access the Self-Insured Employer Market 1

Before you knock on the door, have proof of concept. Pilots or case studies are critical to your credibility. Upstart enterprises will inevitably face a “chicken and egg” conundrum for this.  You need to solve for that. Funding your own study in some way may be something to think about.

Key Considerations

  • Every employer is different. Be prepared to pivot your pitch to meet what the SIE is really after.
  • An employer’s appetite for change and innovation will vary widely based on the views of decision makers, and the realities of benefits delivery for that company. Most times, “new and shiny” just isn’t enough.
  • Claims of medical cost reduction need to be credible and data driven. Understand the actual drivers of medical costs for SIEs and, if possible, touch on key cost “hot spots.”
  • Make sure you have carefully thought through the member (user) experience, as well as the employer experience.
  • Be prepared to explain why carriers don’t cover your diagnostic or therapeutic services as part of their core plan offering.

How Healthtech Companies Can Successfully Access the Self-Insured Employer Market 2

Ronald S. Leopold, MD, MBA, MPH, Physician Consultant

MDisrupt Guest Blogger Specializing in Employee Benefits, Medical Cost Solutions, New Medical Technology

As a credentialed and experienced professional, Dr. Leopold brings credibility and a breadth of knowledge as a consultant, client advocate, and marketplace spokesperson. He is an industry thought leader in employee benefits and health and productivity.

Specialties: Medical Costs, High Cost Claimants, New Medical Technologies, Employee Benefits, Heath and Productivity, Population Health Data Analytics, Global Workforce, Generations in the Workforce, Financial Wellness, Thought Leadership, Public Speaking.

If you are interested in exploring the Self Insured Employer channel for your healthtech product, MDisrupt has a network of experts that can help. Talk to us—we can help.

We wouldn’t make drugs without chemists. So why make digital health products  without behavioral scientists?

We wouldn’t make drugs without chemists. So why make digital health products without behavioral scientists?

Humans are complicated, and changing our behavior is hard. 1, 2 Despite all the hype about artificial intelligence and personalization, most consumer-facing behavior change tools are incredibly unsophisticated, relying on basic self-tracking and superficially-tailored feedback to change behavior. Techniques known to be highly effective, such as such as disrupting habit streaks, and linking contextual cues to behavior, 3, 4 are noticeably absent in most digital health products. Maybe this is why most of these products don’t actually work.

Using science to sell apps—but not to build them

Most consumer-facing apps are not scientifically informed. 5, 6, 7 And even when they are based on evidence, implementation of the science into the product is often poor. 8, 9 This lack of science, however, does not prevent companies from using science to sell apps. On the contrary: A recent review found that over 40% of the most popular mental health apps invoked scientific language to support their effectiveness claims yet just one of these apps linked to published literature. 10

Many of the solutions being pitched or sold to us are behavior change solutions – buy this, wear that, ingest these insights about yourself, and you will be freed from pain, sleep better and lose weight! But peel back the marketing claims, and investors and consumers alike may bristle to find out that—to mention just a couple of examples— sleep-tracking apps can make insomnia worse, 11 and the published benefits of a daily blood pressure monitoring app (whose makers just raised $12 million 12) were based on just 2% of those sampled. 13

An alarming number of companies are publicizing results using inappropriate statistical techniques. For example, conducting what is known as a completers- only analysis involves selectively analyzing only those data from people who completed the trial/experiment, and ignoring the data from people who quit. This approach makes it way more likely you will conclude your product is amazing, because the people who make it to the finish line are inherently more motivated. We want to see your intent-to-treat results, which include the people who dropped out. It is also worth pointing out that the same statistical rules apply to both big and small data. Yet amid the promise of big data, many people have grown increasingly comfortable eschewing the fundamentals. 14, 15, 16 We need to remember that methods matter too: Applying the right statistical analysis can’t overcome bad execution or study design.

The mainstream media, investors, consumers, and industry players have been sold on the idea that behavior change is one appropriately timed nudge away and that we can educate our way toward healthier living. The expectation that exists in the space is wrong: You cannot simply click ‘like’ to change your behavior. 17

So how do you change behavior?

Behavioral science can help us design for behavior change, and build technologies that not only spark change but sustain it. 18

Behavioral science is the empirical study of human behavior across the lifespan. It encompasses fields such as psychology, cognitive science, public health and economics. Behavioral science emphasizes how context, and the social and physical environments, play profound roles in behavior, beliefs, and decision- making. People are different, context matters, and things change. 19 This table lists some behavioral interventions shown to effectively address common health problems.

  Links for references below correspond with number bubbles above.

Links for references below correspond with number bubbles above.

20 21 22 23 24 25 26 27 28 29 30 31 32 33 34

Behavior change science can tell us what works and what doesn’t. 35 If digital health technology companies ignore behavior change science, they will fail to produce meaningful, long-lasting results. 36

Behavioral science + 21 st century technology

Behavioral science has undergone radical transformation in step with the technological revolution. No longer must we rely on humans to self-report what they are doing—now wearables and sensors can passively detect behavior throughout the day. And in instances where we must ask people questions, new technology-enabled methods can illuminate the behavioral context, such as what the person is doing while sedentary, having cravings, and feeling blue. 37

The data accrued from these newer methods are reinforcing long-held (but previously untestable) hypotheses about the non-linear nature of change. 38, 39 They also enable us to intervene at the right time. 40, 41 In other words, we can get closer to automating human support than ever before. These new data also provide strong evidence that conclusions drawn from group-level data are extremely imprecise for individuals. 42 Fortunately, we can now optimize interventions at the individual level and realize the power of behavioral phenotyping. 43

For example, let’s consider how people react differently to self-tracking. We know that some people reject it because of waning motivation – they get negative feedback and stop tracking themselves. Measuring individuals’ determination, resilience, and/or coping style can provide insight into who will benefit from consistent tracking and feedback. For those who respond poorly to consistent tracking, reframing failure as within one’s control can overcome the tendency to avoid. 44

Wellness apps: A behavior change opportunity

Historically, our focus has been on helping people once they get sick, focusing our investment dollars, product pipelines, and healthcare reimbursement strategies toward treating disease. On its face, this makes sense: There is a lot of sickness to treat. Six in 10 US adults have at least one chronic disease, and four in 10 have two or more. 45 By 2030, the number of adults with three or more is estimated to almost triple from 31 to 83 million. 46 Including lost productivity, the economic burden of chronic disease is estimated to be a staggering 20% of our gross domestic product or $3.7 trillion. 47

But, what if we helped people before they got sick? What if we could recoup some of that $3.7 trillion, and pump it back into our economy? Lifestyle behaviors drive most chronic disease incidence, morbidity, and mortality. 48 These behaviors include smoking, excessive alcohol consumption, insufficient physical activity, and poor sleep habits. 49 With the help of science, these behaviors can be changed. And while there exists a dizzying number of consumer-facing wellness apps that claim to change these behaviors, very few have published evidence to indicate that they do so in any meaningful way. 50

Shockingly, even highly valued healthcare startups do not publish peer-reviewed evidence on their apps’ effectiveness. 51 If we are to move the needle on health, this indifference toward evidence and limited use of science must come to an end. We simply cannot afford to fall victim to the illusory truth effect whereby we accept evidence to be true based on how often we hear it repeated.

Digital health won’t advance without behavioral science

Digital health companies should have behavioral scientists embedded in their product development teams from the very beginning. Companies should also include behavioral science in their medical affairs departments, for both evidence generation and strategic leadership. The most forward-thinking companies will have chief behavioral science officers. 52

Within product development, behavioral design should operate in concert with user- experience design. 53 Behavioral design involves translating science into products and services. In addition, behavioral science should be positioned to work alongside analytics and data science. Establishing behavioral-data science architecture is necessary for many reasons, including planning experiments and interpreting users’ engagement data. Digital health companies need to go beyond a focus on the number of monthly or daily active users and ask themselves, what effective engagement looks like. 54, 55

Four questions for evaluating a product’s behavioral claims

  • What evidence supports these claims?

  • How was this evidence generated?

  • How is behavioral science informing product/service design?

  • Who is responsible for pilot tests/experiments?

Remember: Behavior change is hard. Science helps.

We wouldn’t make drugs without chemists. So why make digital health products  without behavioral scientists? 3

Dr. Gina Merchant, PhD, MA

MDisrupt Guest Blogger

Dr. Gina Merchant is a behavioral scientist specializing in digital health. She is an expert in user/patient engagement, how our social networks influence our health, and behavior change design. Gina has a PhD in Public Health, and an MA in experimental psychology.

Disrupt has a network of behavioral scientists; If your company needs this type of expertise to help you build your health product, talk to us—we can help.

The Differences Between Medical and Scientific Expertise. What The Healthtech Industry Should Know.

The Differences Between Medical and Scientific Expertise. What The Healthtech Industry Should Know.

In my 10 years as a medical executive in health tech start-ups, I noticed that medical/science people do not necessarily appreciate the difference between the different types of engineers or designers. To be honest, when I came to Silicon Valley, I considered all people who do anything with computers to simply be “IT people.” Likewise, many people from the tech industry don’t necessarily know the difference between the different types of scientists or the different types of medical doctors—or even the difference between a medical doctor (MD) and a research scientist (PhD).

Good Science Doesn’t Instantly Translate into a Viable Health Product 

Tech investors are increasingly interested in the $4-trillion US healthcare industry. Many are new to this sector. Although they use lawyers to do their legal diligence, they often use their own associates to do their “medical diligence.” Understanding the difference between medical training and scientist training helps to explain why the passion of a scientist entrepreneur may not necessarily translate into a viable health product or why the associate who did your medical diligence missed all the red flags that blocked your investment from widespread market adoption. 

Scientific validity is not the same as clinical validity, yet most of the literature provides scientific validity. In addition, not all MDs are the same. Some specialties get more training in clinical trials, while others develop more expertise in digital imaging, informatics, or device/test development. A dermatologist MD may not be the best person to handle medical diligence for a home laboratory testing start-up.

Medical Review Isn’t the Same as Scientific Review 

The confusion about medical and scientific training can impact efficiency in health tech startups. Once, after working at a particular startup for a couple years, I got frustrated at the commercial team for not getting medical review before releasing new collateral, despite multiple requests. When we met to talk about it, they explained that they did have medical review because a PhD scientist had approved the collateral. I said, “It’s good to get a scientific review, but it’s not the same as a medical review.” One of my teammates asked, “What’s the difference?” When I explained it, many of them seemed genuinely surprised. The purpose of this blog is to shorten the learning cycle on that epiphany.

(In a future blog, I’ll try to explain the different kinds of engineers to the healthcare industry. And I’ll tell them not to call software engineers “IT people.” I will also explain the difference between scientific and clinical validity, and what is required to bridge the gap between interesting science and a viable medical product.)


   Table 1:    The training and expertise of medical doctors versus research scientists.  Table 1: The training and expertise of medical doctors versus research scientists.

Not All MDs Are the Same

The next table addresses the high-level differences between the different kinds of MDs. This classic joke sums up the stereotypes quite nicely:

“A medical student, an internist, a radiologist, a surgeon and a pathologist go duck hunting. They barely find their duck blind before the first duck flies over. The medical student is the first to raise his shotgun, but unable to tell if the duck is really a duck, he does not shoot. The internist aims his shotgun, but can not tell for sure what subspecies of duck it is and wants to order more tests. He does not shoot. He asks the radiologist to take a picture of the duck. The surgeon quickly raises his shotgun, aims, and without pause shoots. The duck falls to the ground. The surgeon turns to the pathologist. “Go figure out if that’s a duck or not.” Funny, right? Even other doctors don’t really know what pathologists do. Pretty sure my family doesn’t. Now I can refer them to this blog.

   Table 2:    Different types of medical doctors  Table 2: Different types of medical doctors

Not All Lab Directors Are Created Equal

Some health tech companies choose to operate their own clinical laboratories, if their product includes a clinical test. The decision to operate one’s own lab rather than outsource the testing to an established clinical testing laboratory has important pros and cons that will be unpacked in a future blog. But one of the requirements of a clinical laboratory is that it is overseen by appropriately credentialed (and in some states, licensed) clinical laboratory professionals. So it is relevant to this blog to know who those professionals might be. 

Most types of clinical testing must be overseen and interpreted by a MD. However, a few types of clinical tests can be overseen by credentialed PhDs who have done a post-doctoral clinical laboratory fellowship. These include germ-line genetic testing, microbiology, chemistry, and toxicology. For many tech people, the difference between MD pathologists (who are trained to run all types of clinical labs) and subspecialty-focused clinical PhDs is not obvious. Using the example of genetics, the following table outlines the difference between the MDs and the PhDs.

   Table 3:    Different types of laboratory directors allowed by CLIA ‘88 regulations.  Table 3: Different types of laboratory directors allowed by CLIA ‘88 regulations.

The bottom line: Know your experts and what each is best suited for. Tapping the precise expertise you need will get your health product faster into the hands of the people who need it.

The Differences Between Medical and Scientific Expertise. What The Healthtech Industry Should Know. 4

Jill Hagenkord, MD

MDisrupt Guest Author

Jill is a board-certified pathologist with subspecialty boards in molecular genetic pathology and a fellowship in pathology/oncology informatics. She brings expertise in health product strategy, coding, coverage, reimbursement, medical and regulatory affairs, health policy, clinical laboratory medicine, population health, provider education and patient engagement.

MDisrupt has a network of MDs and PhDs with a wide range of knowledge and skills. If you’re evaluating a product or company and would like healthcare expertise, talk to us—we can help.

Understanding the Differences between Medical Culture and Tech Culture

Understanding the Differences between Medical Culture and Tech Culture

In a recent Business Insider article, John Ioannidis, Racquel Bracken, and other health tech experts lamented that the Silicon Valley tech ethos of “move fast and break things” is not being counterbalanced by the healthcare principle of “do no harm. (Why everybody gets duped by hot health and science startups, June 2019). Ironically, tech’s desire to move fast is slowing its ability to achieve widespread market adoption and profitability for health-related products. The goal of this blog is to help both industries better understand the importance of their cultural differences in order to get high-impact products to consumers more quickly.

 The healthcare perspective is underrepresented in health tech. I spent the past decade serving as the Chief Medical Officer of several health tech startups. With each one, I was initially energized by the potential for responsible disruption. The engineering, design, and product talent—and the money—was unlike anything available to physicians in a traditional healthcare setting. It truly felt like an embarrassment of riches. With each company, I was the only medical professional on the executive team, and usually the only MD in the company. With each one, I knew that we could have been more successful more quickly if the company had had an earlier understanding of the expectations of the healthcare industry and sensitivity to healthcare culture. I observed this same phenomenon in many of the health tech startups evolving into and out of existence around me.

Tech Needs to Get Curious about Medical Culture

 When I left traditional practice to embed myself in Silicon Valley, I recognized quickly that my tech teammates spoke differently than I did. They solved problems differently than I did. They worked differently than I did. If I was going to effectively partner with them to disrupt health care, I needed to learn about tech culture. I read every Silicon Valley holy book I could find—The Lean Startup, The Hard Thing About Hard Things, Measure What Matters, The Four, In the Plex, Hatching Twitter, The Upstarts, The Everything Store, From Good to Great, etc. I learned about OKRs, MVPs, 20% time, flywheels, doom loops, BHAGs, pivots, dogfooding, flat org charts, and scrums. I read about the history of the tech industry and the stories of how the FAANGs became FAANGs. (In a future blog, we will unpack all these terms. For now, just realize that in order to respect a different culture, it’s important to learn about why that culture is the way it is.) Too often, my tech teammates did not reciprocate my willingness to understand their culture. This limited the company’s ability to design appropriate products, close deals, and compile realistic financial projections. It cost real time and real money.

 Granted, the tech industry has successfully disrupted almost every industry in the last 20 years. Tech entrepreneurs are somewhat justified in feeling like their way is the right way and everyone else should get out of the way. But the reality is that the healthcare industry is different. One of the key differences is that it is not a free market. Full stop. 

In addition, there are multiple, very powerful stakeholders in health care—insurers, regulators, physicians, professional societies, pharma, and patient advocacy groups. Consumers often don’t feel like they should have to pay for legitimate health products out of pocket, so simply delighting consumers and getting them to vote with their feet is not enough to achieve widespread adoption, let alone topple the incumbent system. Unlike other industries, a direct-to-consumer product can’t circumvent the incumbent stakeholders. That’s because consumers will inevitably take the results of their health products to their healthcare providers. If the healthcare provider says, “What is this? This is junk. You’ve been swindled,” it doesn’t make for a positive consumer experience. The flywheel cannot gain momentum. You simply have to understand the values and social mores of the healthcare stakeholders to win.

Being Awesome is Not Enough

 So, how do you do that? With data, credibility, and transparency. It is not sufficient to think your product is awesome and convince consumers of this. You have to prove that your product is awesome. And not just awesome, but medically beneficial and economically worthy enough to justify the high cost of implementation. Generating this proof needs to be part of your go-to-market strategy and financial strategy from inception. What’s more, there is a well-established formula for how to do this. That means there is no excuse for confusion or delay, if investors and founders do their homework.

An obvious way to ensure success is to balance your leadership team with the right tech and medical professionals. If you go too far in the medical direction, you are essentially a traditional device company. If you go too far in the tech direction, you will waste too much time and energy learning the basics of market access and product-market fit. In general, I recommend hiring most of your engineering, product, and design teams from tech and most of your commercial and medical affairs teams from health care. Medical affairs can help make sure your product solves a real problem in health care and design the proof studies. Experienced sales, business development, and marketing professionals not only have the right contacts, but they also know how to deliver the right messages through the right channels at the right time. A future blog will elaborate on how to do this.

Culture Clash

This table highlights some of the cultural differences I’ve observed between healthcare and tech. 

  More details on the    Nuremberg Code    referenced above.  More details on the Nuremberg Code referenced above.

Finding the Right Balance

We need to find the right balance of healthcare and tech cultures to get impactful products to patients quickly and responsibly, and to successfully usher in the much needed disruption of the incumbent healthcare system. The longer we delay prioritizing this balance, the longer we all have to live with the current broken system, and the longer we have to watch billions of dollars wasted on health tech startups  that are doomed to fail because the founders do not understand healthcare culture—both are pretty unbearable!

Understanding the Differences between Medical Culture and Tech Culture 5

Jill Hagenkord, MD

MDisrupt Guest Author

Jill is a board-certified pathologist with subspecialty boards in molecular genetic pathology and a fellowship in pathology/oncology informatics. She brings expertise in health product strategy, coding, coverage, reimbursement, medical and regulatory affairs, health policy, clinical laboratory medicine, population health, provider education and patient engagement.

Every health tech company wants widespread adoption for its health product. There is a community of healthcare experts who would love to help you. Talk to us—we can help.

Why Investors Need to Do More Rigorous Medical Diligence as a Core Part of any Healthtech Investment

Why Investors Need to Do More Rigorous Medical Diligence as a Core Part of any Healthtech Investment

Yesterday’s big news, reported by Chrissy Farr of CNBC, was ‘“Gut health start-up uBiome files for bankruptcy five months after FBI raid.”  In other words, yet another health tech company is making headlines for avoidable, costly—or dangerous—missteps. The troubles of uBiome, Theranos, Nurx and 23andMe have been high profile enough to make the press, but they are by no means unusual. In fact, similar missteps are happening all the time with smaller health tech companies, usually unbeknown to their investors. 

It’s time that we in the industry, who are creating the health products of the future, ask ourselves why these problems keep  happening and what we need to do to fix them. A heated debate erupted on Twitter in response to the latest uBiome headlines, questioning what role investors play in enabling missteps and whether they are doing an appropriate level of medical diligence when they fund health tech companies.

Investing in early-stage companies is always risky particularly in the unproven health tech sector. In every investment transaction, investors conduct a process of due diligence to confirm the accuracy of claims about the company’s finances, business model and teams. The due diligence process is intended to help identify the potential winners, elucidate key risks, and develop a risk mitigation plan with the management team. Common areas of review during the diligence process include finances, operations, legal, and, when appropriate, technical. Although the investors and entrepreneurs need to be aware of diligence issues, the actual assessment is typically done by professionals—accountants for financial diligence, lawyers for legal diligence, and so forth.This is because these individuals do a far better job of identifying potential pitfalls or risks.

Yet in health tech, the process happens in a different way. When it comes to the medical diligence required to evaluate a company, tech investors usually rely on their associates instead of on professionals with medical industry expertise. 

Medical Diligence Is Missing

We would hope that by simply presenting the above sentence to the investor world, the logical disconnect would speak for itself. In case that’s not convincing enough, the proof of the problem is in the numbers: Over $50 billion has been invested in health tech in the last ten years, but with very few successful exits. Clearly, most medical diligence that has been done to date has not been rigorous enough. For the most part, it has failed to separate those companies who are creating a clinically and commercially viable health product from those who are not. And it has failed to detect the ones making the egregious missteps we are seeing in the headlines.

Tech entrepreneurs are famous for solving problems with rapid iteration and learning. However, they can often take far too long—five years or more—to discover certain requirements for success in health tech: Specifically, that: 

  • There is a formula for achieving widespread market access in health care 

  • They need team members who are part of the healthcare industry 

  • Credible evidence presented in the right places is necessary before widespread adoption of a new health product can happen. 

Proper medical diligence that takes these principles into account can save entrepreneurs years in opportunity cost and save investors tens of millions of dollars per company.  

Investors Need to Lead

The investment community has the power to propel the health tech industry forward and accelerate the disruption of health care by identifying the most viable health products faster. In order to do this effectively, investors need to know that a company’s business practices and financing are sound. But they also need to know if a product or service is actually clinically useful, solves a real healthcare challenge, and whether the company has data or is conducting studies that support its claims and stated value propositions. The timeframe to investors’ return on investment is overtly tied to the answers to these questions. Rigorous medical diligence is ESSENTIAL to investor success and to the creative disruption of healthcare.

While the elements of medical diligence are well known to traditional healthcare investors, we believe it’s important for all investors to obtain an assessment of these criteria when considering an investment in a health tech company.  We have outlined these essential parameters in our blog The Formula for Widespread Adoption of Health Products that Every Investor and Health Tech Entrepreneur Needs to Know.

At MDisrupt, we believe that an obvious solution to the problems in health tech is to engage healthcare professionals and market access experts to assess the viability of health tech investments. As with legal, financial, and technical diligence, medical diligence, when conducted by experienced professionals, can save time and money, avoid embarrassing missteps, and set appropriate revenue timeline expectations. 

MDisrupt works with investors and health tech entrepreneurs to do an independent, transparent, and objective assessment of the clinical and commercial viability of health-related products and services. We can identify red flags early on as well as work with companies to bridge any gaps they may have. Our assessment includes: 

  • Clinical Viability

    • Intended use and product-market fit

    • Analytical and clinical validity

    • Clinical utility and health economic models

    • Prospective outcomes studies

  • Commercial Viability 

    • Coding, coverage, and reimbursement, if appropriate

    • Clinical dossier development

    • Key opinion leader strategy and eventual inclusion in professional society guidelines

    • Channel optimization and market access strategy

  • Regulatory Strategy

  • Privacy and Security

As an industry, we need to do better. We need to combine the best business philosophies of the tech industry with the best practices of the healthcare industry to help get the most impactful products to patients faster. This is MDisrupt’s mission.  

If you are an investor considering an investment in a health tech company, talk to us. We are happy to outline and explain the essential elements of medical diligence and why they are important to successful investments. Medical diligence can help keep you and your portfolio companies from making headlines for the wrong reasons.

Why Investors Need to Do More Rigorous Medical Diligence as a Core Part of any Healthtech Investment 6

Jill Hagenkord, MD

MDisrupt Guest Author

Jill is a board-certified pathologist with subspecialty boards in molecular genetic pathology and a fellowship in pathology/oncology informatics. She brings expertise in health product strategy, coding, coverage, reimbursement, medical and regulatory affairs, health policy, clinical laboratory medicine, population health, provider education and patient engagement.

Every health tech company wants widespread adoption for its health product. There is a community of healthcare experts who would love to help you. Talk to us—we can help.

Why medical diligence is essential for healthtech

Why medical diligence is essential for healthtech

We spent the early part of our careers working in the traditional health and life sciences industries. That’s where we met, traveled the world together on medical roadshows, and became great friends. We bonded around our shared frustrations at the slow pace of innovation within our respective fields. We had recognized that technology was going to transform the healthcare industry and were inspired by the early trends in consumer-empowering health products. We wanted to contribute to that transformation.   

Ten years ago, we each decided to move to Silicon Valley. Since then, within our industry, we have seen and witnessed the incredible, the inspirational, the irresponsible, and the wasteful. And now we are on a mission.

Despite healthtech being one of the fastest growing industries (over $50 billion spent since 2011) it can claim relatively few success stories. Most venture investors expect an exit within 7-10 years. Yet for a health product, it can take 10-17 years to gain widespread adoption and reimbursement. Many companies have (and will) run out of money before they become profitable.

Furthermore, many companies with promising ideas have suffered completely preventable missteps because they simply didn’t understand the process of successfully getting a product into the healthcare market. Some well-known examples include Theranos, uBiome, and 23andMe. There are many other stories that weren’t high-profile enough to make it into the mainstream press.

Our early years at healthtech companies in Silicon Valley were challenging. After working at a number of startups we realized that medical expertise was often significantly underrepresented. We learned that tech had a completely different culture from what we had been accustomed to in health care. For example, a common ethos in the tech industry is move fast and break things . It’s standard practice in consumer tech to launch a minimally viable product (MVP) and iterate on the fly.   

In contrast, the primary rule in health care is first, do no harm. And the data proof points for health products are much higher than in other industries.

 And yet there is a clear and well-established formula for healthcare market adoption and reimbursement. Unfortunately, entrepreneurs are often several years in before they are fully aware of all the steps that this formula requires.

 For example, when commercializing a health product you have to communicate in a different way in order to convince a skeptical audience. There is a strategic approach to marketing and business development activities. It requires a combination of the right message, at the right time, with the right data, from the right person, through the right channels. Persuading a scientist or physician isn’t done with a testimonial or a five-star rating. It happens through studies, peer-reviewed publications, podium talks, health economics data, and medical society guidelines.  

 We believe that what’s missing in the healthtech industry is a medical diligence process. In most investment transactions, there is usually a rigorous due diligence process which includes legal, financial, and technical diligence. But there is currently no established protocol for assessing the clinical and commercial viability of a healthtech product.   

 Our hypotheses are

  •  Healthtech entrepreneurs need to find the balance between “go fast and break things” and “first do no harm.” If they understood the formula for healthcare market adoption earlier, they could accelerate their path to market.
  • Investors in healthtech need better ways to assess whether or not a healthtech company can successfully capture sufficient market adoption in the expected timeframe.
  • Organizations such as employers, health systems, and commercial retailers who are being approached by healthtech companies need an objective way to assess the clinical viability of health products before they adopt them.

 It’s taken us 10 years to learn how to speak both languages and balance the best of both worlds. Our aspirations when we came to Silicon Valley were to be a part of the responsible transformation of healthcare. We believe that a core part of this is bridging the cultural divide. 

 That’s why we founded MDisrupt.

 MDisrupt is the world’s first medical diligence company for the healthtech industry. Our mission is to unite healthtech and healthcare stakeholders to accelerate the responsible disruption of medicine. By doing so, we can get potentially impactful health products to patients faster.

 MDisrupt also provides an easy path for practicing medical professionals to participate in our mission. We will matchmake them with the healthtech companies who need their expertise. Our network consists of some of the most experienced people from the scientific, medical, regulatory and commercial sectors of health care. We call them MDisruptors. 

 We all share a common desire to see the products that can have the biggest impact on patient care make it to market quickly and responsibly. We believe that by uniting the innovators, entrepreneurs, and investors from the healthtech industry with our team of experienced MDisruptors, and applying a medical diligence process, we can get there faster together.

Written by Jill Hagenkord, MD and Ruby Gadelrab