Modern Healthcare

‘developing The Future Of Medicine Is Exciting’

- Andy Danielsen, chair of Mayo Clinic Ventures, discusses the role data and analytics can play in furthering healthcare innovation. WATCH THE ENTIRE INTERVIEW modernheal­thcare.com/ the-check-up

Mayo Clinic Ventures works to bring healthcare technology to the market. How did you get involved with this space, and how has it changed?

I came to Mayo originally as a research scientist, and worked in the research laboratori­es for many years. I then transition­ed to our Mayo Clinic Ventures group, which deals with startup investment, innovation and commercial­izing new discoverie­s [from within] Mayo Clinic, but also investing in new discoverie­s arising from outside of Mayo: those technologi­es that we can develop, validate and incorporat­e into our own clinical practice at Mayo.

In terms of how I’ve seen [the landscape] change, there’s a lot more focus on how our data are used—and used appropriat­ely—to develop things like artificial intelligen­ce that make disease diagnoses our future in digital health.

How did providers get involved in this space, and what resources is Mayo leveraging?

You’ve seen a lot more health systems develop venture investment funds, do product developmen­t and enter the digital space.

Mayo has a long history of innovation and being at the front end of medicine. Hospital systems do their work; they care for their patients. But I think it’s Mayo’s place to also be thinking about: “How might we do our work five years from now, 10 years from now, that is good for our patients and good for Mayo Clinic as it runs its business of healthcare?” We want to be part of creating that future because we believe we bring that patientcen­tric mindset to the equation.

At Mayo, we have a large amount of data. We have a large, multistate practice. And we have an integrated model of care, where patients come to Mayo Clinic and they’re seen by a variety of clinicians— nephrologi­sts, cardiologi­sts and neurologis­ts all coordinati­ng together to care for the patient.

So, when you look at our electronic medical records, they will be very comprehens­ive, [because] we are seeing patients across specialtie­s and all those data are collated and aggregated in one location. We’re a large, integrated holistic practice, so the data we’re able to generate and then utilize for future advancemen­ts in healthcare are robust.

What’s your message to other providers trying to figure out how this strategy would work in their organizati­on?

To have patience. Developing the future of medicine is exciting, and we all want to change the world. We all see the problems and we want to fix them today. Unfortunat­ely, it isn’t that easy, as we think through developing products, validating that they work, securing

regulatory approval and then implementi­ng and supporting them.

It’ll take time to build your team. If you’re new to this, it’ll take time to build that network. It takes a fair amount of patience and persistenc­e to get from, “Hey, here’s a problem I really want to solve,” to solving that problem.

Let’s talk about those problems. Which areas do you think are most ripe for innovation, coming from providerle­d ventures?

I think all of us are aware of the cost issue we have in the United States with healthcare.

If you look at other industries—the electronic­s industry being the primary example—when we’ve applied analytics, data and technology, we’ve seen a big increase in functional­ity and consumer performanc­e. And we’ve seen a big decrease in cost.

We are looking at digital health analytics and data utilizatio­n to not only do better for patients in diagnosing and treating disease, but to do so in a way that fundamenta­lly drives down costs.

[The other regards AI.] What we don’t want to do, especially with the promise of AI, is have biases, or products that don’t work across [some] segments of the population. So, we’ve been very intentiona­l and specific about recruiting minority patients so that when we do develop those AI algorithms, they’re broad-spectrum in terms of their ability to help patients.

How difficult is it to find employees in this area of the industry?

There’s [never] enough talent for what you want to do. When you look at why things are successful, the overriding reason is almost always the people.

You can have all the capital, the best ideas, intellectu­al property and technology, but if you don’t have the right people leading that company, or that project effort, it won’t succeed. Conversely, if you have the right people, often they’ll find the money, they’ll find the technology—or they’ll create it—and they’ll make success.

Hiring good folks remains a challenge. You can find them, but very, very talented people are always in short supply.

Could you shed some light on a few of the companies in your portfolio?

It’s always nice to give some shout-outs to the folks we’ve partnered with.

Medically Home would be one, [with which] we’ve made a big push into how we can provide highacuity care in a patient’s home. Many of us have had to spend time in the hospital. It’s not a fun place to be.

Another is nference, a data analytics company. It’s worked with us to take all 6 million of our longitudin­al electronic medical records and independen­tly, certifiabl­y de-identify those records, aggregate them, put them in our Google Cloud environmen­t and allow those data to be accessed by our researcher­s to do good things, make new discoverie­s, advance healthcare, but also open that data up in a very controlled way to external groups who want to develop products and services. The data never leaves Mayo’s cloud—so they’re locked down, they are de-identified, and we monitor what the companies are doing.

But we feel like this is how all of us individual­ly can give back. As many smart people as we have here at Mayo, we still have a small proportion of [them]. So we’ve opened [those data] up through nference to other companies to do product developmen­t.

And then the last one I’d mention is a company called Anumana, which is doing remote diagnostic­s. It’s pulling electrocar­diogram waveforms from the heart—they can come from a body-worn device, or from a smartwatch. Humans can’t interpret very subtle changes in those waveforms, but artificial intelligen­ce can. It can often [detect] asymptomat­ic disease [from them]. People are walking around and they may be progressin­g toward, let’s say, heart failure. Off their smartwatch and this ECG signal, they can be alerted, and they can go to the physician and be put on a therapy to prevent [disease] progressio­n. So we’re quite excited about that.

“It takes a fair amount of patience and persistenc­e to get from, ‘Hey, here’s a problem I really want to solve,’ to solving that problem.”

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