Digital Health is Underfunded

digital health is underfundedOverall venture capital funding made a sharp decline in the last two quarters amid worries (justifiable or not) of a bear market and a funding bubble in technology investments. In contrast to the tech market, however, digital health funding continues to grow at a record pace. According to Rock Health, $4.5B was invested in digital health in 2015 (an increase from $4.3B from 2014) and $981 million has already been invested in the first quarter of this year. It seems on pace to be another stellar year, which is remarkable considering what is going on in other sectors.

Many are skeptical about the investment potential of healthcare technology investments and have been wary to enter the market (perhaps especially so with all the negative media that companies like Theranos and Zenefits have attracted). Additionally, regulatory barriers and the longer timeline needed with healthcare innovations tend to scare potential investors away.  But anyone familiar with the sad state of technology in healthcare can see, even with the record-breaking investments thus far, that there continues to be an enormous untapped opportunity in healthcare–greater, I believe, than in any other sector.

Digital health is vastly underfunded.

Technology is taking over most of our personal and professional lives with indispensable apps, wearables, and other connected devices and software. At home, we have smart appliances, lighting, thermostats, security systems, media systems, and even smart cars. And we have Siri, Cortana, and Alexa doing our bidding. But in healthcare, we’re still in the Stone Ages in terms of technology. Communication via faxes, for example, is still common between hospitals and doctors offices. There are small glimmers of hope, such as patient portals, higher-functionality EMR systems, and telehealth services, but the fact is that we are still a far cry from the ideal vision for healthcare, which includes a seamless cloud-based network of devices and software that can track and record a vast spectrum of patient information, the ultimate goal being the use of computational technology to help prevent, predict, diagnose, and yes, even treat disease. Ultimately, collecting information on large populations of patients could have profound impact through public health measures that can prevent disease and thereby reduce healthcare costs. This can only be accomplished with a wide-spread network of software and devices, that includes electronic health records, wearables, devices based in the hospital, office, and at-home, and with telehealth capabilities. In addition, there are too few companies working to collect, store, manage, and interpret health data.

There is still a lot that needs to be done.

According to MarketResearch.com, the healthcare “internet of things” (IoT) is expected to reach $117B by the year 2020. The fact is, the full potential of digital health won’t be seen until every hospital and doctor’s office and home is connected via cloud-based devices and software and with the development of machine learning platforms that can make sense of the reams of health information.

It is a little challenging to think of all of this in the abstract, so here are a few examples of the potential of the healthcare IoT. Imagine that a spike in certain population health data (like temperature) is detected in a region of the country that alerts public health officials to early to a disease outbreak that can then be contained to prevent an epidemic. Imagine that a change in an individual’s biometric data alerts that person to seek medical care, detecting a life-threatening disease, like cancer, early and improving the chances of cure. Imagine chronic health conditions like diabetes are monitored routinely and continuously with real-time blood glucose levels, with immediate adjustment by doctors of insulin dosages, thereby preventing hospitalizations due to uncontrolled diabetes, and also preventing long-term diabetic complications, such as kidney disease.

These are only a few examples.  There are countless other opportunities in healthcare.

In addition to the opportunity to improve healthcare delivery, there is the opportunity to improve the quality of care through tools that provide greater communication and transparency of information with patients and improve care coordination between the providers of those patients. And by changing the focus of medical care to prevention and early diagnosis of disease, there is the opportunity to decrease the outrageous cost of healthcare as well, by decreasing the need for excessive medication, surgery, unnecessary visits, and hospitalizations. According to the Commonwealth Fund, in the US we spend an outsized proportion of our GDP on healthcare versus other countries. Other developed countries spend between 8.8%-11.6% to our 17% of GDP, related in part to better-connected health IT networks.

It’s hard to fathom how much digital health tech is needed to serve a US population of 318 million and a global population of 7 billion, but one thing is certain: the market is huge.  We should stay bullish on health tech investments now, and probably for a long while to come.

 

Cool Startup: GenoSpace

daniel meyer

Healthcare is drowning in a deluge of data. Decision-makers must somehow make sense of a heterogeneous array of information — demographic, clinical, patient-generated, treatment and outcomes data. The latest waves of information also include data from mHealth and genomic sources. It’s not hard to imagine that many in the healthcare industry suffer from information overload and struggle with a bit of ‘analysis paralysis.’ How can organizations make sense of all this big data and actually harness it to improve healthcare and outcomes?

One company helping answer this question is GenoSpace, an ambitious genomic and health data management startup based in Cambridge, Mass. Its current chairman, John Quackenbush, and CEO, Mick Correll worked together in the Center for Cancer Computational Biology at Dana Farber before co-founding the company in 2012. Contracts with notable customers like the Multiple Myeloma Research Foundation (MMRF) and PathGroup funded GenoSpace before the first round of outside funding in 2014.

It was around that time that GenoSpace hired Daniel Meyer, an entrepreneur with a background in venture capital, as Chief Operating Officer. According to him, it was GenoSpace’s ability to attract high-quality customers early on (a rarity for most early-stage companies in life sciences) that convinced him to join. Recently, we sat down with Meyer to learn more about how GenoSpace helps healthcare organizations make sense of all the big data.

Tell us about what you do at GenoSpace.

When you’re dealing with genomics and other biomedical data, there are a variety of different users and reasons for their use. So you could have an institution that has users engaged in research, clinical development, lab medicine and clinical care. They have different software application needs that cut across the same or similar data sets. One of the things we try to do is develop the tools, the interfaces and the experience that will enable all of those different people to get the most from the data.

Could you go over your major offerings?  

We have three primary categories of offerings: analysis and interpretation of a single assay result together with phenotypic and other clinical data, interactive analysis of data from many individuals as a group, such as from a large observational study (where we really excel is when a customer has integrated demographic, clinical, genomic, treatment, outcomes and other data) and enabling patients to directly report and interact with their data. We’ve created software applications and web-based sites for patients to upload their data, track their results and better understand their condition. Although we have a core competency in genomic data, we do not only deal with genomic data.  Research and clinical care rarely rely solely on a single data type.

Now that Obama has announced the Precision Medicine Initiative expanding genomic study, do you also expect your work to expand?

We think it’s a fascinating announcement and those are the types of initiatives we support. One of the interesting things is that we have customers right now solving many of the problems that the initiative will face. For example, we have been working with Inova, a healthcare system based in Northern Virginia that serves more than two million people per year in the metro DC area. They have been collecting a rich set of whole-genome sequencing data together with structured clinical data on thousands of people. Their data management and analysis needs map directly to those of precision medicine initiatives like the one announced by the White House.

I’d imagine that you’d have greater demand on the private side.  

We have spent most of our time there. Our first clinical lab customer, PathGroup, is delivering industry-leading molecular profiling across a wide geographic footprint, including to some big cities in their coverage area and also smaller cities and towns.  Our ability to help them bring academic-quality medicine to community oncology is a huge impact. Roughly 85% of oncology patients are treated in a community setting. If you’re only deploying in major cities with academic medical centers, you’re missing out.

What are your next plans? Any new projects or goals?

We are  looking to expand to different customer use cases. That can be in terms of the therapeutic indication, such as rare diseases, neurologic or cardiac disease. But it can also be integrating different kinds of data. We have a lot of experience working with demographic, diagnostic, treatment and outcomes data together with genomic results, and there are more opportunities to expand.

Are you also working on using machine learning to do predictive analytics?

We think about that a little differently. There’s supervised analysis, the user asking questions and getting answers about the data, and there’s unsupervised analysis. For many of our customers, they’re not looking for a black box. Our goal is not to replace molecular pathologists, but to work hand in hand with them to make sure their work is better, more operationally efficient and more sustainable, particularly if it’s a commercial entity.

That last piece is underappreciated by a lot of folks. We do a lot of work in genomics and in precision medicine and there’s a lot of science and advanced technology. All that work is lost in most settings if you don’t deliver it properly. You have to understand the science and the innovation, but also how to get it in the hands of people who can impact patients. That’s a big part of what we do.

Any final thoughts?

One of the fun things about being here is we have folks with a lot of different capabilities—in software engineering, interactive design, data science, etc. For a lot of the interesting problems that people are trying to solve in medicine, it takes that interdisciplinary team approach as opposed to a whole bunch of people with the same type of experience.

To learn more about GenoSpace, visit their website at genospace.com or follow them on Twitter at @GENOSPACE.

This article was originally published on MedTech Boston.

10 Genius Ideas to Improve Healthcare

Photo courtesy Anna Shaynurova
Photo courtesy Anna Shaynurova

10 Genius Ideas to Improve Healthcare from MIT Sloan’s Bioinnovations Conference

The MIT Sloan School of Management held its 11th annual Bioinnovations Conference at the Boston Marriott Cambridge Hotel on September 20th, featuring influential speakers from the healthcare, life sciences, research, and regulatory sectors. This year’s theme was “Value in Healthcare” and brought an impressive turnout of over 350 attendees.

“Our goal for the conference was to bring together industry leaders across business, science and medicine to discuss some of the most pressing issues in healthcare,” said conference organizer Anita Kalathil. “MIT and Sloan are passionate about how to improve healthcare, whether at the molecular or systems level, and we know that any solutions are going to have to be cross functional. Our goal was to make the MIT Sloan Bioinnovations conference the connecting point for these different groups.”

There were many great takeaways from this conference, but here are 10 of the most noteworthy:

1. Delivering true value in healthcare.

Neel Shah, founder and executive of Costs of Care, was the conference’s opening speaker. “There’s a misperception that considering cost is not aligned with patient interests,” he said. Cost consideration is becoming ever more important in healthcare, as policymakers demand greater accountability and patients demand greater transparency in pricing.

2. Refocusing the future of research & development.

Mark Fishman, President of Novartis Institutes of Biomedical Research, shared in his opening keynote that aging, cancer, brain disease and genetic therapies hold the greatest promise for future research. He also shared his unique approach for R&D, which is to focus less on cost-benefit and more on areas with the greatest patient needs and solid scientific knowledge.

3. Putting Big Data to good use.

There was a lively discussion during the Big Data, Policy, and Personalized Medicine panel, highlighting the need for better ways of collecting, analyzing and interpreting the huge amounts of data that are being generated from various sources, including medical records, diagnostics, genomics, and sensory data from patient devices. The panel members represented a number of impressive companies (TwoXAR, Privacy Analytics and Genospace) that are attempting to do just that.

4. Researching therapies (and prevention).

In his keynote address, Gary Kelloff, Special Advisor to the National Cancer Institute and the National Institute of Health, shared that the present approach in cancer research involves discovering and developing targeted therapies to biomarkers of cancer. While acknowledging the importance this research, Dr. Kelloff also urged participants to invest in researching the prevention of disease.

5. Improving health IT.

In his keynote, John Halamka, CIO at Beth Israel Deaconess, discussed the ongoing challenges in health information technology that need to be addressed: lack of interoperability, providing transparency while also ensuring privacy, harnessing HIT and Big Data to improve quality of care, and facing the ongoing threat of accelerating security incidents.

6. Considering a team approach.

During a panel about medical device development, Ramesh Raskar, Associate Professor at MIT Media Lab & Head of Camera Culture Research Group, shared that he felt the sciences needed to move away from independent research (which can be slow to produce innovations) and toward a culture that allows individuals to work more collaboratively in teams (which can be faster). He also shared a memorable quote: “The innovator may or may not be an entrepreneur,” which again highlighted the advantage of a diverse team approach.

7. Incorporating patient-centered design.

Kristian Olson, Medical Director at the Consortium for Affordable Medical Technology, recommended that “patients be in the room” when designing medical innovations. And Elizabeth Johansen, Director of Product Design and Implementation at Diagnostics for All, shared her techniques for creating user-friendly devices. Particularly helpful was her advice to observe how patients interact with their devices in their own surroundings.

8. Overhauling healthcare delivery.

According to Mikki Nasch, co-founder of The Activity Exchange, “Your zip code is still a better predictor of your health than your genetic code.” Social and environmental factors are huge determinants of health, and the delivery of healthcare in old models doesn’t address this issue. Healthcare needs urgently to transition away from traditional paradigms and into newer models of care, such as ACOs, that better address these social factors.

9. Finding collaboration between payers and pharma.

There was a lively debate during one of the panels about specialty drug pricing. Panel members suggested that payers and pharma need to come together at a systems level to help advance development of treatments and cures. Dr. Winton from Biogen Idec Market Access suggested new payer-pharma models and shared risk plans.

10. Driving innovation with patients at the wheel.

The final keynote of the day was given by Jamie Heywood, Co-Founder and Chairman of PatientsLikeMe, an online platform that allows patients to share information about their medical conditions and treatments and connect with others with similar conditions. Not only does this novel website help patients, but the open platform also allows healthcare and industry professionals to better understand patients’ experiences and conditions and may help to accelerate the development of new treatments. Conference attendee Dimple Mirchandani was impressed with Heywood’s emphasis on continuous learning to better understand diseases and their treatments, and by his inspiring vision for caregivers and patients to use “data for good.”

This article was originally posted on MedTech Boston.