With the alphabet finally making headlines (thank you, Google), it seems only fitting to join the letter grab and call dibs on “A” for a profession built on foundations nearly as old as the modern English alphabet itself. There are a number of contemporary ideas that fit under “A” when it comes to digital health—accessibility, affordability, accountability—but there is one common thread among all of them: the actuary.
Actuaries are credentialed professionals on which the healthcare industry relies to measure, track, and mitigate risks associated with future cost and utilization of healthcare resources. As with many professions, actuaries are governed by strict professional standards and a code of ethics, and are required to stay informed of their ever-evolving industry through annual continuing education requirements. Actuarial science is now recognized by digital health companies as an integral part of their development. These companies are determined to change the way people consume, navigate, and interact with the healthcare system. Whether they are diagnosing a heart attack through a smartphone, remotely monitoring glucose levels more efficiently, or allowing a rural patient to consult a specialist virtually, many hope to reduce healthcare costs by way of better outcomes for patients or by replacing higher-cost services with innovative lower-cost options—and they are collecting mountains of data in the process.
According to Rock Health’s Digital Health Venture Funding report, big data was the number one funding category in 2014 with close to $400 million funded.1 This emerging trend will lead to more data for companies to base decisions on which, if used correctly, could lead to better outcomes. Even the federal government is showing its cards: For the first time the Centers for Medicare and Medicaid Services (CMS) will allow entrepreneurs and innovators to access its data beginning September 2015.2
This is another step in the right direction, but having access to all of this data will only pay off if it is used appropriately. The learning curve in healthcare data analytics is steep, and we are already finding this to be a challenge for smaller digital health start-up companies. This is where innovation collides with institution and where new ideas meet proven methods. Actuaries are intimately familiar with healthcare data, and we spend a great deal of energy developing best practices to quantify, track, and evaluate key performance metrics that are crucial to the business decisions made by healthcare stakeholders.
With the staggering growth of venture capital (VC) funding flooding the digital health market during 2014 (roughly $4.2 billion, according to Rock Health), and with 2015 deals tracking with similar numbers, it should be a top priority for all healthcare professionals to maximize the efficacy of each funding dollar. From clinicians to data scientists, it is our job to lend our expertise to this charge in support of innovation and the evolution (revolution/reform/modernization) of healthcare delivery. This, of course, is not a new sentiment. Industry leaders clearly recognize the barriers that start-ups face in this space and agree that in-depth industry knowledge and expertise is needed. Anne Wojcicki, CEO and cofounder of 23andMe, has said, “I think that one thing that is lacking in the Valley is sort of a network of people who understand the regulatory environment and sort of a coalition that can help others.”3
Wojcicki also notes that start-ups cannot afford expertise on every front, so they must constantly look externally for critical guidance. Whatever the specific environment may be—regulatory, analytics, market intelligence—chances are that the expertise is not going to be found within the start-up itself. Oftentimes this leads to a large amount of capital being burned only to find out that the business model, technology, and/or service does not have legs. For start-ups in any industry, funding is fuel to the fire. It is the knowledge, strength, and connectivity of this “coalition” that will help identify the fires worth fueling in digital health.
Actuaries play a number of key roles within this coalition. Our expertise in healthcare data analytics is currently being leveraged by digital health start-ups in developing business plans, products, and data analytics. Through our experience navigating the regulatory maelstroms of Medicare, Medicaid, and the Patient Protection and Affordable Care Act (ACA), actuaries have also become accustomed to reviewing and interpreting regulations as the landscape rapidly changes. Our familiarity working with state and federal regulatory agencies has matured from necessity, and we use this knowledge to help guide new companies in this space.
However, in order to maximize the funding dollars that are pouring into this industry, actuaries also need to be sitting on the other side of the (funding) table. Lisa Suennen, managing partner at Venture Valkyrie LLC, estimates that nearly 60% of companies that receive funding eventually go bust, yielding zero return on investment.4 She is certainly not referring just to digital health start-ups, but let us assume for the sake of argument that the $4.2 billion in 2014 digital health funding was funded uniformly across all companies. It does not take an actuary to determine that this results in roughly $2.5 billion that will soon cease its contribution to innovation due to start-up failure. It does, however, take an actuary to help determine how to shrink that number in the years to come.
Enter comparative analysis through the standardization of measurement and evaluation. The actuarial discipline has invested considerable resources in developing best practices to objectively evaluate healthcare intervention programs using vetted, standard measures. So how important are these studies to maximizing digital health funding? Assume you are the managing partner at a VC firm, and you have two digital health start-ups that have caught your eye for a potential seven-figure investment. Each of them has made it through a fair amount of due diligence already, and now you are comparing their purported returns on investments (ROIs). How do you know that the 5:1 ROI is truly better than the 3:1 ROI if the method of measurement is not the same—if it is not standardized in some way? The answer is that you don’t unless you have the time and expertise to dig into both numbers and the assumptions backing them.
When (if) you do dig in, you find yourself staring at a slew of assumptions driving the ROI figures that could be aggressive or conservative—how are you going to know the difference? What is the average cost of a hospital readmission for a 44-year-old male in Baltimore with congestive heart failure? What is the rate of avoidance that needs to be achieved to reach the purported level of savings? To complicate things even more, how does the consumer market differ from the enterprise wellness market?
These are types of questions that are commonplace in the actuarial field. Actuaries are armed with standardized methods and the appropriate data to quantify the risk (or benefit) of healthcare delivery and innovation consistently. This is paramount in comparing potential investments. In conjunction with qualification through clinical trials, observational studies, and/or pilot programs, this capability gives a much clearer picture of potential financial results. After all, we are not just interested in improving healthcare delivery and access, but we have a cost problem to solve as well.
In the purview of digital health funding—whether venture capital, corporate venture, angels, or the like—the hunt for the next unicorn will never end. However, finding one should not be necessary to make a positive return on investment. There are plenty of digital health thoroughbreds finishing in the money; it just takes a trained and concerted effort to identify them. At the moment, growing concerns around the comparatively long timelines required to make a return on digital health investments are putting downward pressure on funding—which is one reason that 2014’s growth rate in funding has not continued in 2015. As Leighton Read, M.D., and venture partner at Alloy Ventures, explains, the new mantra for healthcare innovation is to fail fast, frequently, and frugally.5 This approach is clearly geared towards maximizing funding dollars, but as Dr. Read goes on to explain, it is also maximizing innovation by shifting intellectual focus to the next big idea—both of which are extremely important.
There is one point that Dr. Read does not expand on during his brief comments, however—that in order to fail fast, frugally, and appropriately, an idea or concept must be rigorously tested and measured correctly the first time. Concepts that come out the other side of this gauntlet can be invested in with more confidence regardless of duration. CMS clearly endorsed this paradigm when it launched the second round of Health Care Innovation Awards in 2013 in which government funding was awarded to innovative healthcare programs touting substantial program savings. In order to ensure a high level of confidence in the purported savings, CMS required an actuarial certification of the financial projections for every applicant requesting over $2 million. This not only eliminated the unsubstantiated applicants before they even made it to CMS for review, but it also effectively positioned actuaries as the gatekeepers to $1 billion in funding.6
Every day a dollar is invested in a team, an idea, a product that shows potential to make its mark on healthcare. Regardless if you are the company seeking funding or the investor writing a check, you are not expected to be an expert in every aspect of the industry. Rather, be sure to seek out the professionals who are experts. Talk with clinicians about the efficacy of treatments and the feasibility of innovation. Speak with attorneys about HIPAA, the Health Information Technology for Economic and Clinical Health (HITECH) Act, and the impact of the ACA. Finally, make sure you sit down with an actuary to discuss your data needs, the assumptions driving the ROI in your pro forma, and how the digital health innovation in question can address each of the other important “A’s.”
1Gandhi, M. & Wang, T. (2015). Digital Health Funding: 2014 Year in Review. Rock Health. Retrieved September 15, 2015, from http://rockhealth.com/2015/01/digital-health-funding-tops-4-1b-2014-year-review/.
2CMS (June 2, 2015). Press release: CMS announces entrepreneurs and innovators to access Medicare data. Retrieved September 15, 2015, from http://www.cms.gov/Newsroom/MediaReleaseDatabase/Press-releases/2015-Press-releases-items/2015-06-02.html.
3Rock Health (June 29, 2015). Video: Building a Customer-First Company: Anne Wojcicki, 23andMe. Startup Elements. Retrieved September 15, 2015, from https://youtu.be/dQPV9Xgsj6c?list=PL706EB8B0816474FD.
4Digital Health Live (June 25, 2015). Video: What's Your Technology Worth? - 2015 Digital Health Summer Summit. Center for Digital Health Innovation. Retrieved September 15, 2015, from https://www.youtube.com/watch?v=_03ywINy22s.
5PwC (October 24, 2014). Video: New Mantra for Healthcare Innovation: Failing Fast, Frequently and Frugally. Retrieved September 15, 2015, from https://youtu.be/FJclqWj_eCU.