Dan Burton is CEO of Health Catalyst of Salt Lake City, UT.
Tell me about yourself and the company.
Health Catalyst was founded by a couple of folks from Intermountain Healthcare. We provide a data platform that’s really good at aggregating data from lots of different sources. We analyze the data and we have a layer of analytics apps that pinpoints opportunities for improvement clinically, financially, or operationally. Then we provide clinical, financial, and operational expertise to go after those opportunities.
What led to the Medicity acquisition and what synergy do you expect to see?
We have deep roots and connections to Medicity going back to the company’s founding. Former Medicity President Brent Dover joined Health Catalyst a number of years ago, as did the former head of sales and other management team members. Like us, they are headquartered in Salt Lake City.
What Medicity does is complementary to what we do. The data asset that we have amassed is rich, especially on the acute care side, with about 100 million patient records. But it’s lighter than we would like on the ambulatory side, which is Medicity’s strength. They have about 75 million patient records, largely coming through the ambulatory space. Adding that data asset and the transactional capabilities of being effective in moving data to lots of different places felt like an important complement to the ability of our platform to meet the needs of our clients.
From a mission orientation perspective, the folks at Medicity are focused on using data to improve outcomes. That’s why we exist. We felt like from a data asset perspective and from a mission perspective, it lined up well.
How much of the information that a provider organization needs to meet today’s challenges exists outside their EHR?
The province of Alberta, Canada did a study about two years ago to try to answer that question. Their conclusion was that to effectively run population health for their province, only about 8 percent of the relevant data existed in the EHR. We think that’s about right, and our experience with our clients is similar. The EHR is an important source of data, but we have many clients that need to pull information from 50 or 100 additional sources. We also have clients that have four or five EHRs whose information needs to be brought together into a single source of truth.
What is the level of provider analytics maturity and what are the higher achievers accomplishing that the lower achievers are not?
We are still in the very early innings of analytics prowess or analytics maturity. Even our most advanced clients are still facing some of the same challenges that the rest of the client base that we work with seems to face.
One is a talent shortage. It’s hard to find great data scientists and great analysts in competing with Silicon Valley, with Google, Microsoft, Amazon, and many other tech companies. We’ve seen a real gap in our clients being able to staff the kind of analytics talent that they would like to have. That’s one of the reasons that our analytics expertise, our services offering, has exploded over the last three years. We’ve been fortunate to compete pretty well for talent against Silicon Valley, so we can bring that talent to bear.
It’s not surprising that our industry is early in developing analytics capabilities. It has taken us a long time to transition from paper to electronic data. Without electronic data, there was nothing to analyze. Since we’re early relative to other industries in that transition, it follows pretty naturally that we would be early in developing significant analytics prowess.
The best conference speaker I’ve heard was Billy Beane from the Oakland Athletics at your Healthcare Analytics Summit a few years back, who in “Moneyball” used analytics rigor to find market inefficiencies that could be exploited by an underfunded baseball team. Do we have a Billy Beane-like provider who is taking the culture in a new direction in ways that everybody else is missing?
The analogy is important, including the cultural change required and the doubts he had to overcome from within his organization. We experience a lot of the same in healthcare. But we see some of our most innovative health systems choosing to face the truth from the data, to realize that they have significant inefficiency and significant variation. There’s a lot of vulnerability, for example, in facing patient injury elements, but that’s a necessary step to transform and dramatically improve.
We are also seeing an interesting uptick in innovative openness to being data-driven, coming maybe from outside of the traditional provider segment of the healthcare ecosystem. I think that pattern will continue for a decade or more, where you will see innovative employers thinking differently about how they utilize the data they can collect on the health of the population that they care about most, which is their employees and their loved ones.
We think data and analytics have an important role to play through many different vectors, including the traditional delivery mechanisms, but it will play a role in non-traditional ways, too.
Health Catalyst spent a lot of money to create the Data Operating System. What does it offer that a data warehouse doesn’t?
A lot of value can still be realized from the concepts that were breakthrough for us a decade ago, like a late-binding data architecture. In many ways, that has become a more common practice in healthcare, which is great for the entire industry since it still offers value.
What we saw a number of years ago — and I’ll credit Dale Sanders, our head of technology, for seeing this before many others — was that there would be an explosion in the number of potentially relevant data sources. Specific use cases exist where having access to data sources such as genomics and social determinants of health data leads to much better decisions and dramatically improved outcomes, both financially and clinically.
That explosion in potentially relevant data sources requires a much more scalable data platform. A traditional, on-premise data platform using 10-year-old technology just can’t handle that level of scale. We feel that the right combination is a more modern technology stack that takes advantage of the best Silicon Valley thinking coupled with deep healthcare domain expertise.
We made a bet a few years ago to invest $200 million in this next-generation Data Operating System data platform to support that need to scale. We’re early in enabling our clients to realize the return on that investment, but we’re not super early. We’re seeing more and more interesting use cases where you bring in non-traditional data sources and you have compute power through an Azure-based, cloud-based, scalable technology infrastructure that you just couldn’t achieve in the old model.
Analytics is often applied to address clinical quality and outcomes, but health system cost pressure is increasing. What data tools do organizations use to manage costs?
A cost focus and a precise ability to measure cost at a granular level will become a central focus over the next five years. The low-cost providers will be the survivors, and those who are going to be low cost have to first understand their costs.
There are real challenges, partly because we are not systematically collecting all the data needed to answer the question of, what are my precise costs on a given day, with a given provider, in a given location, with a given procedure? There is data that needs to be collected at a very specific level, but that isn’t being collected today.
We’ve spent a good deal of time over the last five years developing a Pareto version of precise activity-based costing for healthcare, where you get 80 percent of the precision benefit with about 20 percent of the effort. It’s hard to do precision-based costing all the way. It’s incredibly expensive to collect all of that data in every case. We hypothesize an 80/20 rule that we’re finding actually exists. We co-developed this with UPMC.
My opinion is that five years from now, every surviving health system will be collecting all of that data and analyzing it very carefully to identify the hundreds and even thousands of cost-savings opportunities. The health systems that execute most flawlessly against those improvement opportunities will be the health systems that thrive and survive. Those that don’t pay attention are very much at risk.
Health Catalyst is on everybody’s list of health IT companies that are expected to go public next. I know you can’t talk about that specifically, but what does it take to prepare a company for growth?
It’s very hard to do. That’s probably appropriate. To become a successful publicly-traded company requires that size and scale be in place and to have predictability to the business model and the revenue. There needs to be stability in the client base and a significant Net Promoter Score or satisfaction level. In our opinion, there needs to be a culture that is built to last and team members who are deeply engaged in the company’s mission and the success of a client.
That’s a model that we have tried to follow in the event of a scenario where our board decides that going public would be the right path for our company to pursue. We have obviously chosen to raise capital from investors, so we understand that those investors eventually need liquidity and a return on their investment. One way that can happen is through the public markets.
One element that the leadership team really likes is the opportunity to remain as Health Catalyst for the long haul. That’s very important to us, and an appealing element of the public company path.
In any regard, preparing to be a successful public company overlaps significantly with preparing to be a scalable, independent, sustainable company as well. For a number of years, we’ve been trying to prepare ourselves to be the latter, and by preparing for the latter, you are also preparing for the former.
Do you have any final thoughts?:
It’s an exciting time to be in healthcare. It’s a time of transition, which can evoke feelings of nervousness and anxiety for good reason. But it also represents a real opportunity to think about things differently. Data and analytics provide us with visibility we’ve never had about what we should change and what we should do differently so we can see the industry transform. It’s a great thing to be a part of. It’s a meaningful activity to get up in the morning and work hard to fulfill.