|Palo Alto – January 7, 2019 – In my “State of Digital Health” report published last year, I wrote about the progression of healthcare delivery from reactive ⇒ pro-active ⇒ pre-emptive ⇒ personalized. The two key themes enabling that journey are data, and bleeding edge technologies like Artificial Intelligence and Machine Learning. The basic premise is that the more data (qualitative, quantitative, and contextual) you provide “the machine”, the better, more accurate, and more effective the results are. What I observe is that while the notion of more innovative personalized health technology is absolutely amazing, the entire digital health community (that will make the pilgrimage to the annual JP Morgan conference in San Francisco this week) may be losing sight of some fundamental issues that must continue to be considered, as I will discuss below.|
There are two key events, or set of events, that have solidified my thinking around the human or analog nuances of digital innovation. While I am all for encouraging continued momentum in digital health innovation, I feel like we are missing the forest from the trees and trying to design a Lamborghini, while both the infrastructure and the labor pool are stuck in the Model-T era. Let me explain.
I live in Palo Alto, the self-proclaimed heart of Silicon Valley and (also self-proclaimed) center of gravity of global innovation. With three kids (and a dog), prone to illnesses, I have found myself seeking medical care for the family on a regular basis from some of the supposedly most sophisticated institutions in the country, and perhaps the world. Last year, the family switched insurance providers. Since then, as we have visited various facilities from general practitioners to specialists, we have provided the new insurance information. But despite that, I still receive collection notices indicating that the provider billed the insurance and was denied payment. That’s because they were billing the prior insurance provider. The point of the above anecdote is that while we can all talk about the bleeding edge technologies, and AI being the end-all, be-all, we still need to deal with the reality of existing infrastructure, human interactions, and errors.Heading to the doctor’s office for routine issues like shots, flu/cold etc. is a hassle. I have found apps like Heal and others to be very useful in those situations where, for a reasonable fee, one can request a physician at one’s home – sort of like how healthcare used to be delivered. The rise of tele-health or virtual health is something that is clearly having an impact, but only if the company and its business model are built from the ground-up on the idea of tele/video/virtual health. However, the existing healthcare providers with traditional workflows are often struggling to add on the power of video or tele-health for their patients. The interaction between patients and physicians, especially if it’s something that requires follow-up via email, phone or video chat, is neither encouraged, nor enabled by the systems and incentives currently in place for physicians. I recently had a conversation with two very reputable physicians affiliated with a very reputable organization. We started chatting about the movement from a transactional fee for service model, to an outcomes and results-based approach. I asked them whether they were in favor of that transition. Their response was a unanimous “yes, of course”. I asked them what if a patient wanted to follow up via email or a call after they had prescribed a course of action to ensure a particular outcome. Much to my dismay, they both said that there was simply no financial incentive for them to respond. In other words, spending time on the phone, or via video interaction with existing patients does not generate revenue for the physicians or their respective organizations. So, while the technology and the intent is there (remember every physician went to medical school to “help humankind”), the behavioral change needed to implement those technologies will only happen if the right incentives are in place. And for many physicians, for various reasons, the “helping humankind” does morph into $$/hr or opportunity cost calculation the further away they get from their medical school days. Simply put, they could be seeing other patients and making more money rather than spending time on their current patients, for which they do not get financial compensation. Ironically, some of the same physicians may be moonlighting for tele-health or on-demand health delivery companies. But I don’t think it’s fair to point the finger at physicians/providers alone. The overall compensation structure, driven primarily by the payors, is not set up to reward tele, video or email follow-ups. Until that changes, the dream of patient-centric healthcare will stay just that…a dream.
What the examples above indicate is that there are significant issues both with existing infrastructure, workflows and processes as well as with the current mindset of healthcare providers/payors. So, while the bleeding edge technologies, AI and real-time data analytics will definitely help, there are significant challenges. The overall impact, in terms of efficacy, efficiency and especially cost, will only be delivered over time. While investments in health technologies have gone up significantly over the past decade, the costs continue to increase. So, just like behavioral change on the part of the patient or consumer is non-trivial, so might be the case with the providers/physicians as well. I am not saying that changes aren’t taking place, but I think the ubiquity of the data-driven change may take longer than the Silicon Valley startups and their VC investors might be anticipating.
Recently, there has been a lot of talk about large social media technology companies, especially Facebook, using or abusing consumer data to drive profitability and shareholder value. Facebook, Google and others would argue that it’s the consumers who are more than willing to share their every waking and sleeping second so that they can be served a contextually relevant and personalized content experience. Similarly, companies that leverage consumer or patient data through digital health applications are promising very much that same thing. The more data one shares with a wearables company, the more customized content, promotions, and transactional opportunities will be surfaced for the individual. Perhaps the most extreme case is with the genomic companies like 23&me. Clearly, the curiosity factor of knowing one’s DNA and ancestry is the initial hook. But then, the idea really is to share that consumer data, albeit anonymized, with pharmaceutical companies for research or a personalized medicine value proposition. The reality, however, just like with Facebook, Google and others is that a vast majority of the customers have no idea what data is being gathered, what is being shared, with whom, when, how, and why. This is the quintessential dilemma between utility and privacy. So many companies, especially in the technology domain, are fundamentally based on collecting and leveraging personal data to directly or indirectly deliver value to customers. For example, sharing your driving and vehicle data with your auto insurance company may lead to reduced premiums. The world is moving towards a similar model in healthcare, life insurance, and the like. The more the vendor knows about you, the more they can incent you to act a certain way, or penalize you if you don’t.
Bottom line is two fold: One, that Silicon Valley may be falling head over heels in love with technology, especially when it comes to health. The policies, systems, processes, and human mindset has yet to catch up with many of the amazing innovations already in the market. The biggest litmus test will be when the overall healthcare spend actually decreases meaningfully, given that the value proposition many companies are offering is a data-driven, efficient, effective, outcome-based healthcare. While a record number of startups are raising record amounts of venture capital, the results, at scale, have yet to be seen. My hope and expectation is that it will indeed happen, but how long it might take is anyone’s guess. And two, just like in the social media domain, there may need to be some intervention to create a policy framework for personal health/activity/nutrition/genomic data to be used by digital health or pharma companies to provide better healthcare.
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