C-Suite Q&A: Clarify CEO Jean Drouin on Starting Up in Value-Based Analytics

In our quest to bring together powerful, informative perspectives in the health tech sphere, Healthcare Analytics News regularly speaks to leaders, influencers, and innovators in our recurring C-Suite Q&A series. This week’s focus is on Jean Drouin, MD, MBA, the CEO and co-founder of Clarify Health Solutions, a San-Francisco based startup focused on value-based care analytics. Clarify uses analytics to inform the best course of care, and offers physicians an integrated app that they can prescribe to patients to stay on top of their treatment.

Dr. Drouin, in the first part of our interview, spoke to the needs his company aims to fill, the pursuit of value-based care, and the process of leaving a career and getting a startup off the ground.

Let’s start off by talking about how you got into the industry and what you like about it

I was at McKinsey in healthcare consulting for 15 years, where I ultimately headed up the healthcare IT and digital practice. On the one hand I was working with companies like the IBMs, and the Sales Forces, etc., on how they should approach healthcare, and on the other hand most of the work that I did was with large hospital systems and academic medical centers on improving operational efficiency.

The reality in that world right now is that most healthcare economists, at an industry-wide level, say that 20 to 30% of what we spend on health today is not effectively driving outcomes.

When you get down to a more micro level, though, and you try to work with hospitals to become more efficient and provide more satisfying journeys for patients, you very quickly realize that the tools of the trade today are often still Excel and Post-It Notes. When applied with good management practice, actually, those tools do tend to reduce variation and improve performance and the quality of patient care and the patient experience. This is not to denigrate that, it’s more to make the point that in healthcare, we’re still very much at a stage where we still have an enormous amount of value to create in just bringing in what I would say are the basic, standard, good practice analytics that you would find in most other industries, say financial services or consumer manufacturing.

The reason that I left McKinsey two years ago to start Clarify was precisely that. There’s a massive opportunity in healthcare to bring the same kind of analytics and logistics approaches that you find in other industries to patient care. The premise though, in order to do that, was that you want to bring together a team of clinically savvy operators with essentially an enterprise software team capable of building a scalable platform to deliver these kinds of capabilities.

That leads into the process of starting a company like this, ground up. How did you assemble that team?

I would not have left a job and a career I was very happy with if I had not had some amount of conviction that the change in payment model from fee-for-service to value-based, which is a massive transition, would finally create the forcing function or the impetus for providers and payers to invest in the same kind of platforms we see in other industries.

The analogy we always use is that of FedEx, or Amazon Logistics. They put a tag on a package that allows them to track it in real time, and they expose that to us as consumers either through our phones or computers or a call center, and they can tell use right where our package is and we can reroute it to another address if you want. In the background, they have very sophisticated workflow optimization software to route each truck precisely every day based on what’s packed inside it. I left with the business plan that we were going to bring exactly that kind of capability to, for example, the way a hip replacement journey works today, or a coronary bypass, or asthma, if you will. We will have a physician prescribe an app that contains a precise pathway that can then guide the patient through their journey.

What I knew I needed was a great CTO, and a terrific software engineering team. I was in New York at the time and decided that it would likely be easier for me to network my way to a CTO if I came back to the Bay Area. I somewhat classically put my stuff into a moving truck and came back out here and stayed with friends for 5 or 6 weeks.

I had the good fortune of being connected to Todd Gottula, who is our CTO and my cofounder, He and his team had just sold their company in financial services and did very well. They had built the platform so that each night would take a third of the world’s trading volume, about $12 trillion in assets, would mark the books back to market for 5,000 banks and hedge funds and financial institutions.

Very deliberately, we brought together a set of folks with clinical operational backgrounds with the capability to build an enterprise software platform that can do the kind of automated analytics that one would want. Essentially, it was a bit of serendipity in terms of working with the Bay Area tech and VC community.

And an essential, though simpler part of a startup is the name, and how did you reach that? It seems to just sum up the concept of value-based care rather cleanly, does it not?

It does, and I’ll be brutally honest with you. We were sitting around at the stage where we were still working out of Todd’s house around the kitchen table, and there were 5 of us. We said “OK, what about a name that has something to do with lighthouse?” Or showing the way, if you will. It took us 5 hours and we went through about 150 possible names to find one that was available.

That said, sometimes serendipity smiles. It’s turned out to be a terrific name. People will laugh sometimes and say, no pun intended, that a lot of what we bring is an ability to clarify for providers or individual physicians or payers where it is that they should invest their time and energy to more effectively deliver care.

So let’s shift gears now, you’ve got the team and the name, who are your clients and what do you provide them?

We work with both providers and payers. In the provider context, our initial focus has been hospitals that have been mandatorily selected for the Medicare episode of care or bundled payment arrangements for total joint replacement, or soon to be cardiac. Those hospitals are now receiving on a quarterly basis either penalties or bonus checks based on how well they are managing the total cost of care. That’s all the bills within the 90-day period post-discharge. Their unmet need there is that while their electronic health record gives them visibility on what’s going on while the patient is in the hospital, once the patient is discharged typically they haven’t had a ton of visibility as to what was going on. We provide them both with the retrospective look at how well they’ve done at managing (or not) those 90-day periods in the past, and then the ability to track the patients in that period so that they can more effectively manage them.

Our initial customer is a large health system in the Bay Area that does quite a bit of hip and knee volume, and we have several others, mostly in California and in New York that we’re about to start working with.

That’s the provider end of things. Interestingly, we had some very senior C-level executives from one of the larger health insurers come to see us a few months back. They said, “Wait a second: the rapid variation identification machine you have built to better clarify variation in practice at individual physician levels…we get how it can help a hospital to improve the way it handles episodes of care, but could you not use the same analytics to help us better understand patients up front. In the same way Amazon can figure out when they need to re-order something, can’t we use that understanding of the patient to better match them to the right physicians or facilities, or to the right pathway of care?” So we work with insurers on that, in giving them the predictive understanding of a patient.

So that aspect of the business came entirely out of their ask?

Correct, it came out of their suggestion that the very same core analytics foundation that we had built with a view to helping the management of a real-time journey…for them, could be turned around to better match a member in their case to the right care protocol. The reason that’s important for an insurer is that the most bang-for-the-buck lever they can pull to manage their member population is to match them to the right physicians. The thing they then want to do is to work with the physicians to improve the way that they deliver care, but it’s easier to find ones that are already delivering care well today.