From the heartbeat captured by a jogger’s fitness tracker to the treatments at an emergency room, health-related data has been growing exponentially. Putting this data to valuable use and monetizing it has largely eluded most healthcare-related companies, though a few have recently begun to capitalize on proprietary data.
Several other industries have already found ways to use data to create entirely new business lines and upend established markets. In movies and television, researchers once could obtain only ticket sales and viewership estimates. As more people streamed shows online, companies such as Netflix began to harvest new forms of data that showed how viewers browsed, when they stopped watching an episode and what they switched to—all of which allowed Netflix to eventually compete against traditional movie and TV companies.
Healthcare faces a similar disruption by new, data-intensive companies. To be sure, healthcare has more regulatory complications than most industries, including strict privacy controls, as well as a fragmented system of providers, payers and patients that impede the collection and sharing of data. Still, the surge of interest in data affords opportunities that can be assembled within a PE portfolio. Potentially valuable use cases include the following:
- helping consumers make better decisions about healthy living;
- helping them find the right care and understand the true cost of that care;
- making care delivery more efficient for payers and providers;
- helping providers harness the power of artificial intelligence (AI) and robotic process automation;
- making clinical trials and R&D within biopharma more efficient;
- determining the commercial positioning of drugs through real patient data and evidence; and
- speeding up how a core business runs.
Where the value lies
Not all data will be equally valuable. What makes a data asset valuable for PE investors is a blend of several characteristics.
First, the data should solve an important use case, addressing a valuable pain point in some unique ways. While this may sound obvious, healthcare companies too often compile data without a clear purpose in mind.
Second, value lies in having a critical mass of data, so that it is solidly representative by being broad enough or longitudinal enough.
Third, the data should be unique or at least possess some proprietary aspect, through the data itself or a creative linkage of multiple sources, or through proprietary analytics.
Fourth, the data should be organized and structured such that it is easy to manipulate and analyze.
Finally, the data should come with access rights so that it can be shared with or sold to third-party organizations without violating privacy laws such as HIPAA controls on data sharing in the US.
Three promising business models
Healthcare’s fragmented market, along with the strict privacy controls in many countries, makes it challenging to create longitudinal data that is sufficiently holistic, including clinical claims and pharmaceutical data.
Successful companies don’t worry about building an elegant, perfectly scoped data set. Instead, they have improvised with scrappy, sometimes manual approaches to generate value from proprietary data. Companies are taking three promising tacks:
The core data provider. One option is to buy a traditional data company whose core business in its simplest form is to create and sell data. Such companies often have a beachhead of data into which investors can tuck other interesting data sources. Even when the data is not highly proprietary, its use and linkage to other data can make it valuable.
For instance, Advent acquired Definitive Healthcare, which has assembled and continuously refreshes a leading provider database incorporating links to other industry data, such as claims, that customers value for a range of uses.
The shape shifter. Other companies have realized that their core business is generating critical data that they could either use to transform their business model—as Netflix did—or resell for a different use case.
Flatiron Health, a healthcare technology and services company, illustrates this tack. Flatiron had an electronic medical records (EMR) platform designed for oncology care that touched 2.1 million active patient records as of 2018 and had longitudinal data. Pharma companies were interested in applying the data to several use cases ranging from smarter R&D to reducing control groups required in clinical trials. Because the EMR data was not clean, Flatiron invested heavy scrubbing to turn unstructured data—low-resolution PDF lab reports, audio files and digital copies of handwritten notes—into structured data. Once Flatiron completed the scrubbing, it could sell a unique data set that served a clear need at a specific customer phase within pharma oncology R&D.
The analyzer. A third option is to buy an analytics-oriented data company. Individual data sources may or may not be interesting commercially, but when pulled together and subject to proprietary analytics could yield rich value. Aetion, for example, serves as a bridge between pharma companies and payers, which need to agree on the real-world efficacy of a given treatment to support outcomes-based pricing agreements. Aetion’s analysis provides a neutral and credible third-party perspective.
While the promise of healthcare data is intriguing, not all data has equal value. Due diligence should make a holistic assessment, including use cases and completeness of the data as well as whether investors can articulate the need for potential customers.
As data increasingly becomes top of mind for PE investors, there are a few things that best-in-class investors are starting to do:
- weigh the trade-offs of investing in a core data provider;
- assess the existing portfolio to understand hidden monetization opportunities or a business model that pivot data would enable;
- as part of diligence on new assets, think holistically about whether there is a data monetization play that could be made, or a business model pivot that data would enable; and
- do diligence on whether data could disrupt an industry, so that investors are not blindsided by a Netflix-like insurgent.
Investors will need to play both defensively and offensively in their data investments, and they should think expansively. Monetizing the wealth of healthcare data entails scrappy, hands-on work to polish data diamonds in the rough.