On the Digital Health Conundrum (Part I)
For a decade, digital health has been the supposed savior of the healthcare system, coming to drive healthcare into a data-first, low-cost industry worthy of the 21st century. Investors have poured over $30b into digital health since 2011 but what material change can we point to in health care costs or the experience of the average patient? Are there companies that qualify as major disruptors? To me, the answer is no. I call this the Digital Health Conundrum.
Consider some of the digital health companies that might qualify as big wins. Teladoc? Telehealth adoption/utilization continues to be low (<10%). Despite all the hype and fast growth, Teladoc remains an infrequent way to treat urgent care conditions. This is fine, but hardly transformative. Ask any insurance exec whether telehealth has materially impacted cost or patient access. Spoiler alert: they’ll say no and they might even say it has increased costs. What other companies could qualify? Livongo? It’s got a $2B market cap, down almost 50% from its July IPO. Health Catalyst? $1.2B in market cap and down since IPO. Phreesia? Just crossed the $1B market cap threshold. These companies pale in comparison to the massive wins elsewhere in software (Stripe, Uber, Airbnb, Square, etc.) and the jury is still out on all of them. They have incrementally improved the efficiency of existing resources but they have not dramatically improved or scaled healthcare expertise.
Livongo has perhaps been Digital Health’s biggest success, but it feels like we should see more change in the industry given the investment.
If healthcare is such a large market ready to be disrupted by technology (17% of our GDP spend), 10+ years in, where are the winners? Why are the few wins we can point to like Teladoc incremental rather than transformative?
Let’s face it: digital health has been one of the most disappointing investment areas of the last two decades. Venture investors have yet to formulate a strategy that works in healthcare. The approaches from tech entrepreneurs have been underwhelming. Most either fall into the camp of “tech for tech’s sake” (i.e. the first generation of digital health efforts like Google Health) or over-indexing on the suggestions of “health care people.” My favorite examples of the latter are companies working on AI scribing. OK, yes, charting is a huge problem for doctors. Removing it would be a win. However, this isn’t transforming healthcare, it’s putting lipstick on a pig. Insider approaches lead to incremental solutions; insiders don’t point to true innovation, they point to what they know. Incremental solutions don’t lead to venture scale change.
A Quick Aside On MA
This post addresses the payor/provider world, not pharma or biotech. I also ignore the pockets of value-based care/Medicare Advantage (MA). While there is innovation in MA due to improved incentives, it is not how the bulk of the US health system operates. The aligned incentives could create big wins. This opportunity is policy driven so I would argue it fits into the framework of this post.
Why isn’t digital health working?
The tech approach and the venture model have been marginal successes in digital health. The lack of original thinking on how to approach healthcare has surprised me. Venture investors, despite their financial incentives to find home run startups, want to back predictable go to market strategies. Few people want to take risks in their approach and instead have banged their heads against painstaking sales cycles and organizations with structural resistance to change.
Venture investors shy away from strategies with a 20% chance of being transformative and an 80% chance of being a zero. Why? Investors don’t have a healthy relationship with risk and want to see predictable progress. This is why investors love SaaS business — they’re understood and repeatable.
The common refrain to tech people entering healthcare is to “learn about the financial incentives.” This is a red herring. Learning about the financial incentives of any one player ignores how that player fits into the rest of the system. Even inside of an individual organization there are numerous players with their own incentives. The complex structure of the healthcare system and its organizations makes teasing out go to market opportunities almost impossible. Here’s my take on what the real challenges in working with existing healthcare enterprises are:
Provider Systems
Provider systems have two primary challenges in adopting digital health products: misaligned financial incentives and a change-averse culture.
The fee-for-service model is viewed as the primary blocker for change, but it’s not the only misaligned financial incentive. Provider systems do a lot of revenue with minuscule margins. The median operating margin for health systems in 2018 was 1.7%! Imagine doing 1B in revenue and taking home 10m in profit. Some startup comes along and wants to change your operational processes. Why would you ever take this risk unless you’re 100% certain it will work? These organizations have optimized the crap out of their processes to achieve that 1% margin. A $250,000 contract materially damages that profit. The tolerance for trying things isn’t there, nor should it be. Health systems often live month-to-month. Consider this list of 19 recent hospital shutdowns. Now try articulating why they should adopt your solution. The impact of your solution represents a catch-22: if it’s too small they have bigger fish to fry and if it’s too large it creates too much risk.
Health systems also have change-averse cultures with complex internal relationships. There are discrepancies between the desires of primary care physicians and specialty care. There are discrepancies between the priorities of the health informaticians and the providers. Administrators prioritize different things than both providers and informatics folks. Buy-in and adoption require all these parties. Someone from a large academic health system once told me, “we’ll kill the project due to a tie in the faculty senate if it’s one hundred for and one against.” Physicians have been trained since medical school to avoid malpractice at all costs. What does this all result in? Stagnancy. This change-averse culture pervades health systems as it should. In what world is this the kind of environment where venture scale change can happen? If you’re restricting your product to administrative processes your chances are better, but affecting care is challenging.
Payors
Payors are more open to change but are difficult customers due to their inability to change provider group behavior, lack of direct connection to the patient, and, again, misaligned financial incentives.
One of the fundamental challenges of working with payors is their inability to affect provider behavior. Except for pockets of value-based care, anything that needs changes in provider behavior to save costs or improve patient experience/access requires a separate value proposition for the providers. Providers have little incentive to adopt anything new. This kills a number of impactful businesses. Take the case of Call9. Call9 had an amazing premise: give patients in Skilled Nursing Facilities (SNF’s) access to telemedicine so doctors could prevent patients from unnecessary trips to the ED. The value proposition here is insane! SNF patients are an expensive patient population. Nurses are on hand to help assess the patient and communicate with the doctor. The patient’s medical history is known by the SNF. Saving a trip to the ED can be tens of thousands of dollars and the telemedicine unit costs are a few hundred dollars. In June, Call9 shut down. Why? Among other things, it was difficult to get SNF’s to participate despite payors benefitting from the cost savings.
Even when companies have gotten distribution through payors they have struggled with customer utilization. Teladoc markets its 8% utilization rate as 4x the industry standard. Imagine Slack marketing that 8% of their customer’s employees used the product! Folks at one successful company that sold through Self-Insured Employers (SIE’s) told me they did bespoke marketing campaigns for each new customer. The adoption challenge becomes a cascading risk with a long enterprise sales cycle AND a consumer marketing challenge. Reaching the consumers is difficult: insurance databases with customer information are out of date, have incorrect addresses and contact information, and issues with duplication of patients and missing records. Good luck!
Last, medical loss ratio restrictions, amongst other things, creates negative incentives for insurance companies to reduce costs. If you’re interested in digging in, this post by Sidney Primas explains why insurance companies benefit when the cost of care increases. Here’s the salient part on the “80/20 rule”:
[I]nsurers can [by law] at most keep 20% of the money they collect from consumer premiums for profit and administrative costs (e.g. salaries). So, if insurers want to increase profits, they need to increase the total amount of premiums collected. However, they cannot just increase premiums since insurers need to maintain competitive premium rates as compared to other insurance companies. The solution is allowing the cost of care to increase.
What’s Missing?
What is missing from healthcare that has driven tech-enabled growth in other industries? In healthcare, go-lives, implementation periods, and pilots grind adoption to a halt. Contrast this to the learnings from the SaaS world that the best software companies start as self-serve. Self-serve software never happens in healthcare. Why not? What’s missing to enable self-serve or other forms of rapid progress in healthcare? Three things come to mind: a lack of early adopters, a lack of platforms for low-cost experimentation, and the challenges of integration into the system.
There are few small organizations that act as early adopters of new products. This has been exacerbated by consolidation in healthcare. Physician practices, where they do exist, are not set up to adopt new software tools the way SMB’s are. On the insurance side, it is hard to even imagine the concept of small early adopters: insurance is a business of scale. New plans like Oscar and Clover may be the closest thing, but they are still figuring out the blocking and tackling of insurance as they scale.
Continuity of care and plugging into the existing healthcare system is near impossible. There have been few platforms for building healthcare “apps” in the way we use API’s like AWS, Plaid for fintech, or Stripe for payments. This is starting to change with the rise of companies trying to build a platform layer for digital health applications like Eligible and TruePill. The biggest problem, of course, is data interoperability, which hasn’t yet been solved. This would let standalone digital health apps exchange patient data with health systems and vice versa. Integration into these systems requires a long development cycle because of shoddy endpoints and risk aversion around sharing data. For example, at Curai, because of the monopolistic behavior of SureScripts, we were facing an 8 to 18 month timeline to be able to write an e-prescription into any pharmacy in America (don’t worry, we have a workaround).
Distribution channels prevent building customer centric solutions. Enterprise players have incentives independent of what end users want (whether those end users are patients or physicians). The result is clunky user experiences that don’t get used. Hence the low utilization rates. Instead of feature checklists to enable enterprise sales (ahem, EMR’s…), healthcare needs products built with the customer obsession we see elsewhere in tech.
What are my takeaways? Everything is fucked up in healthcare and digital health hasn’t been an exception. Change isn’t coming with linear approaches. We need radically new approaches or black swan events. We need people who think differently. Isn’t this what tech does best? In Part II, I’ll talk about my framework for driving change in healthcare and how I think we’ll get there.
Update: You can read Part II here.
Thanks to Nikhil Krishnan, Vinod Khosla, Sylvan Waller, and Kunal Sethy for feedback on this post.
This was originally posted on Medium on December 10, 2019 and reposted here.
