Google’s acquisition of FitBit has resulted in many great stories recounting the ins and outs of the fitness tracker and smartphone wars, Google’s troubled attempts to get a toehold in the wearables space, and the pending showdown with the Apple Watch. Commentators highlight the personal health data that Google will have access to through Fitbit as a regulatory and commercial risk–with FitBit users concerned that Google will now use their sensitive health information to strengthen its advertising business.
With this framing, it is possible to miss the central point of the acquisition: Google’s acquisition of FitBit is all about health data, and–specifically–about the path to the personal health record.
Here are my top 3 takeaways from the FitBit announcement.
A personal health record (PHR) is an electronic application through which you, the patient, can manage and maintain all of your health information in a private, secure and confidential environment. In contrast to an electronic health record (EHR), PHRs are focused on giving patients–rather than physicians–control of their health information. The argument for a PHR is that a patient is cared for by many healthcare providers and, therefore, no single EHR will provide a full picture of a patient’s health status. The PHR concept has been around for decades, but earnest attempts to create a PHR did not take off until the mid-2000s. Here are a few highlights from attempts from a decade ago:
All of these early attempts to create a PHR floundered. Ten years later, the market is giving the concept a second shot, with Google and Apple now making big bets in this direction (as well as patient portals from startups like Ciitizen and Picnic Health). There are good reasons to think that this time someone will succeed:
In short, there is more digitized health data than ever before, and there is more interoperable health data than ever before (though we still have a long way to go). This is causing the industry to take a second shot.
The $100 billion question is not whether Google or Apple will win the skirmish in wearables, which is a highly fragmented ~$25 billion market. The question is whether enough has changed in the last ten years to allow someone to succeed in the battle for the PHR, and who that winner will be.
Two challenges from a decade ago still are true today. First, the underlying business incentives to share data are often weak. Keeping data in one software product, platform or company is a way to drive patients to that particular product or company, and make it harder to switch. Health systems and health tech vendors often have incentives against data portability, which is why interoperability is being mandated by government initiatives (at CMS, HHS, etc.) rather than developing naturally in the market. Getting the incentives to share data right is critical because individual health data is extremely fragmented. Creating a PHR requires pulling data from a variety of sources, including electronic health records, claims, diagnostic labs, genetic tests, fitness trackers, and smartwatches. While there are technical and regulatory challenges to pulling this data together, the more daunting challenge is a commercial one.
Another challenge PHR is that there is yet to be an amazing patient-facing application for having all of your health records in one place. The flywheel of Google’s business is that its search capabilities are so valuable that it can passively gather data on its users’ interests and preferences, which can then be fed into the most effective advertising machine ever created. In health, there is no “search”. No one company has found a way to create so much value for patients that they can passively collect comprehensive health information and build products on top of that information.
Wearables and fitness trackers might be the closest that anyone has come to the valuable patient-facing application that starts to create a flywheel of attracting patient interest. Apple did not attempt to launch Apple Health Records until it had successfully rolled out the Apple Watch to tens of millions of customers. While FitBit has struggled to compete with Apple, the company now has 28 million active users who interact with the application to track their activity and sleep patterns. That positions Google and FitBit well to begin signing up new health data partnerships, and ingest other interoperable health data to enhance the value of the product for users.
On a three year horizon, the success or failure of the FitBit acquisition will not hinge on its role as a fitness tracker. It will hinge on Google’s ability to evolve the product toward a PHR that tens or hundreds of millions of active users find valuable.
It is still an open question whether companies can develop the amazing application that allows the PHR to take off and unlocks an enormous market for personalized health data. Bridging from fitness tracking to a general PHR is not trivial, and other companies (Backpack, Ciitizen, Picnic Health, etc.) are going at the problem more directly.
Assuming that winners do emerge, we predict that they will have a few key characteristics:
If Google’s acquisition of FitBit is approved by regulators, Google will be well positioned for this battle. We will then see continued fierce competition in the wearables and other personal health information markets. But the more interesting question is who will reshape today’s competitive dynamics to get us to the PHR and to integrated health information more broadly.
(Conflict note: While Datavant is not in the personal health record market, we partner with many of the companies listed here on adjacent problems around protecting data privacy and creating data liquidity.)
Thanks to Shahir Kassam-Adams and Bob Borek for their support developing this piece.
AnalyticsIQ, a marketing data and analytics company, recently adopted Datavant’s state de-identification process to enhance the privacy of its SDOH datasets. By undergoing this privacy analysis prior to linking its data with other datasets, AnalyticsIQ has taken an extra step that could contribute to a more efficient Expert Determination (which is required when its data is linked with others in Datavant’s ecosystem).
AnalyticsIQ’s decision to adopt state de-identification standards underscores the importance of privacy in the data ecosystem. By addressing privacy challenges head-on, AnalyticsIQ and similar partners are poised to lead clinical research forward, providing datasets that are not only compliant with privacy requirements, but also ready for seamless integration into larger datasets.
"Stakeholders across the industry are seeking swift, secure access to high-quality, privacy-compliant SDOH data to drive efficiencies and improve patient outcomes,” says Christine Lee, head of health strategy and partnerships at AnalyticsIQ.
“By collaborating with Datavant to proactively perform state de-identification and Expert Determination on our consumer dataset, we help minimize potentially time-consuming steps upfront and enable partners to leverage actionable insights when they need them most. This approach underscores our commitment to supporting healthcare innovation while upholding the highest standards of privacy and compliance."
As the regulatory landscape continues to evolve, Datavant’s state de-identification product offers an innovative tool for privacy officers and data custodians alike. By addressing both state-specific and HIPAA requirements, companies can stay ahead of regulatory demands and build trust across data partners and end-users. For life sciences organizations, this can lead to faster, more reliable access to the datasets they need to drive research and innovation while supporting high privacy standards.
As life sciences companies increasingly rely on SDOH data to drive insights, the need for privacy-preserving solutions grows. Data ecosystems like Datavant’s, which link real-world datasets while safeguarding privacy, are critical to driving innovation in healthcare. By integrating state de-identified SDOH data, life sciences can gain a more comprehensive view of patient populations, uncover social factors that impact health outcomes, and ultimately guide clinical research that improves health.
Both payers and providers are increasingly utilizing SDOH data to enhance care delivery and improve health equity. By incorporating SDOH data into their strategies, both groups aim to deliver more personalized care, address disparities, and better understand the social factors affecting patient outcomes.
Payers increasingly leverage SDOH data to meet health equity requirements and enhance care delivery:
Payers’ consideration of SDOH underscores their commitment to improving health equity, delivering targeted care, and addressing disparities for vulnerable populations.
Capital District Physicians’ Health Plan (CDPHP) incorporated SDOH, partnering with Papa, to combat loneliness and isolation in older adults, families, and other vulnerable populations. CDPHP aimed to address:
By integrating SDOH data, CDPHP enhanced their services to deliver comprehensive care for its Medicare Advantage members.
Value-based care organizations face challenges in fully understanding their patient panels. SDOH data significantly assists providers to address these challenges and improve patient care. Here are some examples of how:
By leveraging SDOH data, providers gain a more comprehensive understanding of their patient population, leading to more targeted and personalized care interventions.
While accessing SDOH data offers significant advantages, challenges can arise from:
To overcome these challenges, providers must have robust data integration strategies, standardization efforts, and access to health data ecosystems to ensure comprehensive and timely access to SDOH data.
With Datavant, healthcare organizations are securely accessing SDOH data, and further enhancing the efficiency of their datasets through state de-identification capabilities - empowering stakeholders across the industry to make data-driven decisions that drive care forward.
Explore how Datavant can be your health data logistics partner.
Contact us
.svg)
