According to a mid-year study, $3.5B was invested into 188 digital health companies in the first half of 2017.
Every pillar of the “health” umbrella is now acknowledging the importance of innovation, and more than ever we are seeing the prioritization of streamlined processes through digital platforms. Medicine, in particular, is a very old industry with massive companies that struggle to innovate from the inside—hence why so much money is being invested externally.
Here are four trends I would keep top of mind through the rest of 2017, and watch closely over the next few years.
1. Digital Health Interventions
This is one of the broader categories within digital health—the idea of using digital interventions to monitor and improve everything from sleep patterns to patient treatment. The goal with digital interventions is to improve patient outcomes and empower people to fix problems that are either chronic or acute.
Insurance companies, in particular, are realizing that there is value here because they can improve success rates for treatments and reduce the amount of patient readmissions. The venture arms of insurers such as Humana and Kaiser Permanente have made significant investments in this arena.
However, since this is also a fairly broad category, it should be noted that the results of the studies related to digital interventions tend to be somewhat inflated. While potential has been proven in this area, we really don’t know yet whether these platforms are as powerful as people want them to be in terms of improving patient behavior.
What I often remind other digital health thought leaders, and what I believe is important to stay at the forefront of conversations surrounding innovation in health care, is that tech is not intended to replace human interaction. Digital can help streamline processes or improve patient engagement, but should not aim to remove human interaction altogether.
2. Provider-Centric Solutions
One of the most prominent pain points in health care is the fact that providers are constantly overwhelmed by the tediousness of documentation. As a result, their margins are squeezed because they’re now receiving less money per patient, per procedure, and they’re being forced to do more and more patient documentation (which is an added cost depending on how they manage it).
My wife is an endocrinologist at an academic medical center, and I know that while she’s seeing patients, she’s getting their history while facing a computer and documenting the information she’s collecting. This is really not due to choice, but necessity to be efficient. Although she maximizes patient interaction and is hyper focused on the development of a strong doctor-patient relationship, there is bound to be some disruption that happens by the clear obstacle of technology that lies between the patient and doctor during this type of encounter. This applies to many, or most, specialties where documentation requirements have taken over the patient encounter.
Solutions in this space are looking to reduce the documentation workload and allow for a streamlining of documentation practices that will allow doctors to give their full attention to their patients.
One way that this problem is currently managed by some providers is through the use of a scribe. As medical providers know, a scribe is usually a contracted employee who stands in and types up each visit’s interaction between doctor and patient. This is one solution that has been developed to allow the physician to focus on the patient during the visit. But having a scribe can be expensive and many primary care and medical providers can’t support it. One example of innovation in this space comes from a company called Augmedix, which is utilizing the technology of Google Glass. A good friend of mine who is a practicing internist is part of a beta program in which doctors wear Google Glass instead of using a scribe. The doctor wears a pair and has the entire doctor-patient interaction streamed to a remote transcription center, where the cost of the transcription is exponentially cheaper.
A creative approach, yes, but as you can probably tell, this space is still largely undefined.
3. Big Data & Analytics
This is one of the most exciting categories for innovation within digital health.
We are getting to the point now where companies have so much data that we can start to model the risk factors associated with a given patient or procedure. For example, we can assume how likely someone is to be readmitted back to a hospital, or what their anticipated recovery time will be. Big data has the potential to fundamentally change how we care for people.
This is one of the areas of digital health I am most interested in, and a big reason why I chose to develop my own healthcare platform, called Pulse. It is a cloud-based mobile and web platform, and what Pulse does it is follows up with patients after a surgical procedure to ensure that they are recovering in the best way possible. The primary difference between big data collection and what we’re doing with the Pulse platform, however, is that big data is reflective – it can really only evaluate a static data set. I like to call what we’re doing with Pulse “Dynamic Risk Stratification.”
What this means is that most people stratify risk prior to an intervention, looking at previous data sets to anticipate the future. For example, a patient might be identified as being high risk for a certain procedure based on a history of heart disease, and we can reach that conclusion by looking at thousands and thousands of cases of similar patients. And while that data is absolutely important, it’s really only part of the puzzle.
Taking it a step further, and what we’ve implemented into the Pulse platform, is a constant and dynamic stratification of a patient’s risk level. For example, if a patient is low risk prior to hip surgery, but on day seven we ask him or her (through the Pulse app), “Is your wound dry?” and the patient answers “No,” then he or she is automatically re-stratified to be a high-risk patient because at that point, following hip surgery, the patient is at high risk for a hip infection.
The opportunity in this space isn’t just to gather large sets of data and draw sweeping conclusions. It’s to be constantly re-stratifying risk levels, especially in scenarios of interventions or high-risk procedures.
4. New Model Insurance Companies
One of the most curious areas of development, and one that has captured quite a bit of venture capital funding, is new-model insurers. There are two companies specifically that have clearly gained some traction and significant funding – Oscar and Clover Health, raising $725 million and $425 million, respectively. So far, just in 2017, insurance-focused startups have raised more than $700 million overall. Interestingly, a sizeable portion of the financing for these new-model companies has come from the traditional insurers themselves. Specifically, MassMutual Ventures, the VC arm of the huge insurer MassMutual, and AXA Strategic Ventures, the VC arm of the multinational insurer AXA, have led the charge.
The widespread dissatisfaction with the ACA marketplace and some of the traditional insurers has created this potential opening for companies that want to think about insurance ‘differently.’ The VC firms and traditional insurers have opened the spigot of funds because they’re hoping these tech-insurance startups can control costs and utilize technology in a way that perhaps traditional insurers have always struggled with. These new-model insurers claim to be at-the-core ‘technology’ companies that are truly driven by tech and data to make decisions and improve the patient experience. However, that’s yet to be proven. Companies will have to demonstrate over time that they can actually care for patient members and manage the associated costs better, or even as good as a traditional insurer. This was all while the large insurers made huge technology investments over the last five years because they realized the need to integrate better with modern tech and manage consumer spending on healthcare in a data-driven fashion.
This is an amazing time in the digital health world because ‘all bets are off.’ The bottom line is, if there is a founder or executive team that is deeply passionate about their product or solution, while genuinely understanding the complexities of healthcare, and they are able to show real clinical evidence on outcomes, costs, and patient experience, they have a chance for success. But that last piece is critical.