Anyone who has worked in information technology for a while knows about the old “diapers and beer” story which a fellow named Mark Madsen actually got to the bottom of a few years ago. The story goes something like this.
Back in the early 90s, a woman named Karen Heath, a senior manager for health analytics with Accenture today, was running SQL queries on datasets at an unspecified Midwest retailer. What she discovered was that the sale of diapers and beer seemed to be highly correlated. The idea was that husbands who were sent to the store to buy diapers also decided that picking up a six pack of beer at the same time might make their evenings a bit less miserable. Maybe placing the baby products closer to the beer aisle would increase sales of beer? It was a great example of how data mining can produce unexpected insights that can generate value at scale. Perhaps there are numerous ways retailers could modify store layouts to increase the sale of high-margin items. And indeed, there are.
With more data available now than ever, there is a lot of money to be made for companies that can extract valuable insights from it. In industries that haven’t seen a lot of operational innovation over the years – like healthcare – data analytics companies can add value very quickly by addressing lots of “low hanging fruit.” The ideal business model is a “Software as a Service” (SaaS) offering that charges people a subscription fee for a solution that can create loads of operational efficiencies. That way, growth can continue – or perhaps even accelerate – when the inevitable recession hits. (In late 2019, we entered into the longest bull market ever recorded.) One company that offers an appealing value proposition in good times or bad is Health Catalyst (HCAT).
About Health Catalyst
In our recent article on 8 AI Value-Based Care Startups That Took Funding in 2019, we introduced you to Salt Lake City-based Health Catalyst, a company that had an IPO this past July and currently sports a market cap of around $1.35 billion. Simply put, the company focuses on “solving healthcare data warehouse issues for some of the nation’s top health systems.” The use of the old-school term “data warehouse” is a testament to how the industry is two steps behind today’s technological advancements. In our article on Big Data vs. Data Warehouses. What’s the Difference?, we offered up the following interpretation as to how big data and data warehouses are related:
- (DATA WAREHOUSING + BIG DATA) X MACHINE LEARNING = ENTERPRISE AI
Regardless of what terminology you use, the key takeaway is that there’s loads of money to be made in transforming the disparate archaic data collections found in the healthcare industry into something that more resembles a “big data” set, and then feeding it all to some hungry machine learning algorithms that can make sense of it all.
Of the 700 employees that work at Health Catalyst, more than 28% are analytics experts who analyze all the data they import into their cloud-based Data Operating System (DOS) which can now ingest over 300 healthcare data sources through pre-built “connectors.” Embedded within DOS are machine learning algorithms that customers can easily leverage for predictive analytics. (Health Catalyst doesn’t make the machine learning aspects of their platform a huge focal point which makes sense considering the healthcare industry is still stuck trying to figure out how to make data warehousing work.)
Since 2015, analyzing all this data has resulted in “more than 650 documented, customer-verified improvements across clinical, financial, and operational domains.” The below timeline shows how their company’s growth has been progressing very quickly in recent years.
These are all success stories that can be used to convince the next client to come on board. The company has many reference clients now that are willing to share their wins. For example, here’s an impressive set of accomplishments they achieved with Alina Health, a not-for-profit health care system that owns or operates 13 hospitals and more than 90 clinics throughout Minnesota and western Wisconsin.
Cost savings, reductions in mortality rates, fewer opioids being abused, and decreasing the time patients spend in hospitals, are all benefits that appeal to multiple stakeholders.
There’s another interesting observation to be made in the Health Catalyst S-1 filing. Subscription revenues encompass 90% of total revenues, yet only 50 of their 126 clients (as of 2018) are subscribers to their DOS platform. This means that less than half their clients account for the majority of their revenues. In order to better understand how they ended up here, let’s take a look at the total market they’re looking to capture.
Humans like to waste a lot of stuff. If you thought 30% of food going to waste was bad, then you’ll be equally surprised to hear about waste in the U.S. healthcare system. According to Health Catalyst, research estimates show that “30% of U.S. healthcare spending is wasteful in nature, implying more than $1 trillion of waste amongst $3.6 trillion of total healthcare expenditure in 2018.” Out of that number, Health Catalyst has carved a conservative total addressable market (TAM) of $8 billion which represents more than 1,200 U.S. health systems and risk-bearing entities. Of that number, they had only captured around 4% going into 2019 (50 current clients / 1,200 potential clients). As expected, they’re spending lots of cash to capture market share very quickly.
To that end, they’ve also made several acquisitions, one of which presents an unknown degree of operational risk.
In early 2011, health insurance company Aetna plunked down $500 million to acquire Medicity, a health information exchange technology company also based in Salt Lake City, Utah. At that time, Medicity was said to have the “largest installed base of enterprise health information exchange (HIE) systems for hospitals, physicians and other health care providers,” with 750 hospitals and 125,000 physicians on board. In June of 2018, Health Catalyst acquired Medicity from Aetna for a total consideration of $2.3 million. Consequently, the majority of their customers not on a DOS subscription contract are interoperability subscription customers resulting from their recent acquisition of Medicity. They now need to cross-sell more than half their existing customer base in order to achieve revenues growth from this acquisition. A few excerpts from the S-1:
- We are in the initial phases of that cross-selling initiative and do not have full visibility into the incremental growth opportunities from that effort.
- We expect flat to declining revenue from Medicity customers in the foreseeable future
- We plan to integrate portions of Medicity’s technology into the DOS platform and are currently in the process of that technical integration.
Between 2011 and 2018, the value of Medicity fell from $500 million to $2.3 million. That’s not a good sign. Investors need to pay close attention to how the integration of Medicity unfolds. Now that Health Catalyst has completed the acquisition, they’re starting to figure out where all the bodies are buried. Who knows what Health Catalyst has inherited here, and one can only hope that proper due diligence was taken to ensure that this acquisition accelerates growth instead of impeding it.
Getting Back to Basics
Health Catalyst talks about how the market for healthcare solutions is intensely competitive,” citing their competition as industry-agnostic analytics companies, EHR companies such as Epic Systems and Cerner, and “current large competitors, such as Optum Analytics and IBM.” In their S-1 filing, Health Catalyst provides the below commentary as to why these competitors have been falling short:
- Legacy clinical software and industry-agnostic horizontal data vendors have attempted to enter the healthcare data space, but have been unsuccessful due to the healthcare-specific content, logic, and advanced analytics capabilities required.
- In addition, many healthcare organizations have attempted to develop their own analytics solutions but have found them to be too costly to develop and maintain.
- They have also looked to traditional EHR vendors; however, these vendors lack the capabilities needed to compile and derive analytics insights from the vast number of available data sources in a flexible manner that drives time-to-value.
As for IBM, we posed the question last year – Is “IBM Watson Health Imaging” the Future of Healthcare? An article by FierceBiotech this past summer talked about how IBM’s beleaguered Watson Health division now has a new leader who is doing the typical come to Jesus talk about getting back to basics, doubling down, being super focused on execution, IBM’s great work on Apollo, trusted adviser relationships, and other platitudes that mean very little. (For weary IBM investors, it’s almost unbearable.) The author of the article talked about how “Watson’s early stages have been hampered by interoperability concerns and issues in translating disparate data sources into something it could use.” Seems like that’s exactly what Health Catalyst has figured out.
We like growth companies that use a SaaS business model because they provide investors with a very simple performance metric – run rate – that can be used to gauge success in capturing market share. What’s even more likable about Health Catalyst is that they’re targeting an industry that’s a complete mess of inefficiencies. The downside to selling data analytics solutions to the healthcare industry is the amount of time it takes to convince decision makers that they ought to adopt a new solution. However, when you can point to 650 process improvements that demonstrate the value of your solution in saving money, your sales lifecycle just might shorten when the market enters a recession, and everyone is looking for ways to quickly cut costs.
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