The OnDigitalHealth Blog

My latest thoughts on the industry I love.

DIY Hacking​ Digital Health: Value

Welcome to the third installment of my (as-yet) ongoing (you guys keep encouraging me – thanks, btw!) series of rant-raves on various topics associated with “digital health.” Okay, quick “word” to the ever-hip Venture Valkyrie: Yes, at some point, we should and will divest ourselves of the phrase “digital health” – I agree. But we’re not quite there yet, IMO. If nothing else, I think it does provide a (somewhat) useful standard under which we can (still) rally the troops of the broader healthcare industry, so there’s that. Also provides for a (still / somewhat) useful summary category for tracking investment in the category. Lots of conversations and lots of dollars, some progress. Anyway, this third installment will be the best, I think, what with three being a magic number and all. “Woah,” said Keanu Reeves…at multiple points during the course of his career. Yes, indeed, Keanu.

What I really wanted to rap with you about today is the value of digital health, whether real or perceived. At face value, this seems a pretty simple concept. The perceived value (and near-endless potential) of digital health was certainly one of the most compelling factors that helped to push me into the space, more than 7 years ago now. On the flip side – and with that 7 years of experience – I’ve come to appreciate how complex the ‘value’ issue in digital health really is. “Value is in the eye of the stakeholder,” you say. Well, “yes, you’re very smart. Shut up.” And, I have always been of the opinion that any measure or measurement of value – whether qualitative or quantitative – is itself more valuable when it can be used as a means of comparing two or more things. Preferably ‘apples to apples’, as opposed to ‘apples to jackfruit’ (FYI, jackfruit for the win), as the more disparate the comparisons, the less meaningful generally speaking, particularly when real dollars are at stake. And even more particularly when they are your dollars.

Let’s contemplate a couple of ‘real-world’ theoretical examples: A) Richard, the health and wellness benefits administrator for a F500 employer, has an incremental $100K to put toward a new digital health program for the next annual benefits program cycle. At present, he’s considering either: a) a stress management / reduction app, which might presumably be more applicable to a larger number of employees in his company’s employee population, or b) a type 2 diabetes self-management program, which is much more expensive per user / employee (depending on the pricing model), applicable to fewer employees, but prospectively may have a larger, positive impact on risk and cost reduction (ultimately tying to MLR for their payer(s), another measure of value in healthcare). For administrative, operational and other reasons, Richard believes that he can only take on one of the two programs, as they have already invested in a number of other initiatives, which at present, are not living up to the hype. Also, Richard and his team – and their partners / vendors – jointly continue to struggle with employee engagement (ahem). What should Dick do? Where should he place his bet? Unfortunately, in my experience, most of the health, wellness and benefits decision makers have limited tools and/or expertise to assess value, particularly with regard to quantitative measures. Not their fault. It’s largely because such quantitative data is still in relatively short supply in digital health. It’s happening, it’s just happening slowly, and for many reasons (number of stakeholders involved, where data comes from, how and when data can be shared, cost of conducting clinical studies, etc., etc.), i.e., in an evolutionary manner, rather than in a revolutionary one. Okay, so in example B), Jane, a managing director at digital health-focused venture capital firm, is looking to invest in “disruptive”, fairly early-stage companies in the digital health space, probably those looking to raise an A or B round. She and her team of associate(s) have narrowed the firm’s next investment down to a couple of options which fill the high-level requirements of: tangible (largish) market and market opportunity, novel or intriguing business model and/or technology platform (both of which are highly scalable – see below), experienced executive team, strong revenue growth and continued prospects (even if profitability is a ways off), one or more marquee customers, in-range valuation, strategic fit with rest of the current portfolio companies, clearly articulated use of prospective funds, an easily-imagined exit path, etc. Prospective portfolio Company A is a SaaS-based (surprise!) “healthcare analytics” company doing interesting things with a pre-packaged and further customizable suite of automated population health management and CDS algorithms. Prospective portfolio Company B has developed a nutrition platform that customizes meal plans and grocery shopping lists and rewards upon healthy eating behaviors. As one can imagine, both have applicability to more than one customer segment (i.e., across payers, providers, employers, pharma, pharmacy, etc.). What data will Jane use to make her final call? Well, as you can envision, let’s hope that the decision-making process in Example B) is considerably more quantitative, imbued with more (applicable?) experience, and is purposed to a different objective. But hey, guess what?! I’ve personally witnessed hundreds of millions of dollars poured into digital health cos, with literally no chance of a decent return – and I don’t mean 10x or even 5x – I mean that Jane may not even get a 2-3x return. “How is that possible?”, you ask. Well, we’ve already established that you’re very smart, so naturally you ask great, segue-way inducing, leading questions…

Getting to it: There are already a number of highly-publicized measures of “value” in the healthcare space. Some guy named “Porter” has written about it, fairly extensively. He seems pretty smart, too, at least in part because he wrote this, “value depends on results, not inputs, value in health care is measured by the outcomes achieved.” He continues with, “Outcomes, the numerator of the value equation, are inherently condition-specific and multidimensional. For any medical condition, no single outcome captures the results of care. Cost, the equation’s denominator, refers to the total costs of the full cycle of care for the patient’s medical condition, not the cost of individual services,” states Porter. The full cycle of care. “Woah,” – Keanu chimes in again. Yay, verily, mind-blowing stuff, written in 2010.

So how does one get to a (more) accurate measurement of value, when, as we discussed above, there is a dearth of quantitative digital health data? Funny you should ask! A few empirically-sourced thoughts follow. This is by no means meant to be a definitive list, but it is a list of some pretty important considerations, IMO, some of which seemingly get overlooked, even by some really wicked-smart people…not you, of course, as you probably already know all of this. But just indulge me, won’t you, and if you could, please check my work against your abacus / B.S.-O-Meter. Here we go, in no particular order.

  1. The ‘Usability Factor’: As in, “Hey, would I (thinking very objectively) use it?”, and if not, “under what (specific) circumstances would I use it?” Not “that sounds like something of value to somebody”, or, “yeah, I can envision certain circumstances under which that might be useful for [X]”, or, “I bet [insert population] would use it.” No. Just no! If whatever this is is not extremely compelling, with a perceived value proposition and tactical-missile-like solution to an as-yet unmet need that screams, “you need me,” then chances are, you don’t – and neither do a heck of a lot of other people. Believe it or not, I’ve seen would-be customers and investors hold their nose / close their eyes and look right past this one, time and again. The most compelling solutions cut across many user types and market and customer segments because they’re just plain awesome. And people will pick them up the first time, and will continue to log in and use them, because they are (close enough) to indispensable. How many apps of any variety do you have on your phone that you would put in the above category? Rest assured, weary traveler, they’re out there, even in the digital health space. You’ll recognize one by the curly horn sticking out of its head!
  2. ROI: Quite simply, “Am I going to get more out of this, than the amount I put into it?”. And if so (awesome), how much more, and over what payback period? ROI is one of many measures of value. For reasons we’ve already covered, there are not a lot of well-defined, time-tested and/or reproducible ROI equations in digital health. But again, there are some. And we as an industry should keep pushing until ‘ROI’ is a part of our everyday vernacular, part of every purchase and/or investment decision, one of our most-reached-for tools in the value measurement toolbox.
  3. Customer satisfaction: I can haz? Well, in most cases you “can’t get no,” or at least, very little, as the majority of the companies (many of them start-up or growth-stage companies) in the space either don’t know how to measure satisfaction, or have purposely chosen to devote very limited resources to do so. Yes, you can and should ask how a prospective portfolio company / vendor measures customer satisfaction. Yes, you can and should ask for a list of reference customers. But these don’t go far enough, in my experience. You need to make some specific requests (i.e., demands) and do some homework on your own. There is significant value in reaching out to known customers that are not on the list of reference customers. Ask them about their experiences, and you’ll probably find out why they’re not on the ‘list’.
  4. [The Rest of The] Metrics: Some (all?) industries are less complex than healthcare. Some industries subsequently have a more-or-less standardized set of valuation / operational / execution success metrics. Some of these are even applicable to digital health companies (personally, I L-O-V-E the ones around LTV, churn and renewal!). But the trick is that they need to be applied. I know, I know, revolutionary thinking.
  5. Probability of realizing maximum future value (a.k.a. the discount rate in your NPV calculation): This is a bit more intangible than some of the other items in the list, primarily because there are a multitude of factors in the equation. This comes down to your ‘due diligence’ process, as potential purchaser / investor. Do you really look under the hood, or are you content to peruse a slide deck, some marketing collateral or a few documents in the data room? Do you know what you’re looking for? Can you spot a red flag? Here are a few variables for your consideration:
  • Scalability: Can the operational / organizational structure and resources as well as the technology platform be readily scaled to match the lofty goals of business model? I’ve seen even the bluest of blue-chip VC firms invest without considering how the requisite scaling of people resources might drag down SaaS margins, or taking a company at its word that they’ve performed “sufficient” load testing…with the entire system later crashing when it reached 1,000 concurrent users for the first time. Ouch.
  • The Code: I’m far from being any kind of coder or S/W engineer (though I did write some BASIC in high school!)…but even I have heard warning bells when listening for such things as the size of the engineering team – particularly in comparison to the company’s technology roadmap, development cycles and the content of its release notes. How efficient is the engineering function, and at what (resource) burn rate? There’s also the consideration of just how well the code is organized. Neo could tell you that in a flash, but I’m thinking a SME could assess this for you, if you or your organization doesn’t have the requisite expertise. Don’t leave such things to chance. They go directly to future product development (quality, capacity and speed), time to market, competitive advantage, profitability, scalability and long-term viability. Those things seem kind of important to me – but what do I know?
  • Risk Management: As in, does the company have the requisite leadership ‘chops’ and experience to put in place a robust (or any?) risk management process, with clearly-delineated risks and subsequent probabilities of occurrence, triggers, mitigation strategies, and both strategic and tactical options? Not many startups do, unfortunately, as they tend to seemingly prefer to “fly by the seat of their pants.” Guess what (again)? When something unforeseen happens, the typical response is to throw the entirety of the organization into damage control mode…this is not very efficient, to say the least.

I still love you, D.H. And, I think, as many have already postulated, that 2017 is a “rubber meets road” type of year in the digital health industry. There will be increased consolidation and ‘exits’ – not all of which will be of the back-slapping, celebratory variety. There are simply too many boats in the harbor, for them all to stay afloat. I think the five points I covered above will – at least in part – help to determine over time which companies will be setting sail for bright – and hopefully not too distant – shores. ‘Til next time, “bon voyage,” y’all!

In Good (Digital) Health,

Karl

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