3.5 years ago, I founded Datavant to connect the world’s health data to improve patient outcomes. Today, we are announcing the combination of Ciox and Datavant — our biggest step forward to become the neutral, trusted, ubiquitous infrastructure powering the exchange of data across healthcare. This post outlines our vision for the combination and the possibilities we hope to unlock for patients, researchers, and the industry.
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Anyone who has ever visited a doctor knows that the health data ecosystem is broken. As a fairly simple patient, there are at least 100 institutions that have some snapshot of my health data: for example, I’ve visited a dozen physicians; I’ve seen a handful of specialists; I’ve had at least 10 different insurers; I’ve received genetic testing; I’ve received prescriptions and vaccines from dozens of pharmacies. Today, nobody in healthcare has a holistic view of the patient’s journey across these touchpoints — not the patient, not the patient’s doctor, and certainly not researchers and the analytics community.
This is a hard problem to solve: there are tens of thousands of institutions in the US that hold patient data, and they each have different incentives and challenges involved in exchanging data. There is an immense amount of friction involved in the exchange of data:
Despite the challenges, this is a problem that must be solved, and in fact is one of the biggest opportunities to improve healthcare. When founding Datavant, as an outsider to the healthcare industry, I took a step back and asked the question “given all the advancement in technology and data of the last 30 years, why haven’t patient outcomes improved (and why hasn’t technology changed healthcare the way every other industry has changed over the last few decades)?”
I believe that the answer is that the data is too fragmented. It is simply too difficult to answer as basic a question as “what percentage of patients who were treated with X medication are still alive 5 years later” or “is X drug safe during pregnancy.” If we can’t answer the basic questions due to data fragmentation, we certainly aren’t at a stage of development where AI and advanced analytics can transform the industry.
If we can solve the health data fragmentation challenge, we can unlock a health data economy over the next decade that uses health data to solve the following types of questions while empowering the patient and their providers with the information they need to direct their care:
To unlock this data economy, Datavant will focus exclusively on removing friction from the exchange of data: we are not in the business of monetizing data, and we are not an analytics company. Instead, we will power thousands of data businesses and analytics companies that benefit from a connected data ecosystem.
The last decade has seen the rise of middleware companies across a number of industries that help make interoperability across applications seamless. To build this for the healthcare industry, there are four traits we must have:
The most successful middleware company in history is VISA. VISA is embedded in the majority of transactions, but it is not the front-end of any transactions and doesn’t actually have relationships with consumers. Its ubiquity removes a point of friction for every merchant, and for every consumer. As a result, it powers a huge percentage of commerce, and makes money by taking a small fee on every transaction.
We aim to parallel the VISA model: powering an ecosystem of thousands of companies around us, and creating the foundational middleware powering the health data economy.
In 3.5 years, I am extremely proud of what Datavant has built: we power the largest de-identified data ecosystem in healthcare; we support data connectivity for hundreds of providers, payers, health analytics companies,Life Sciences companies, and government institutions exchanging data; and we’ve built an incredible team and culture that is the foundation for us to solve data fragmentation over the next several decades.
Fundamentally, we have come at the data fragmentation challenge from the de-identified data exchange perspective: making it safe and easy to exchange data in de-identified contexts for analytical purposes.
Enter Ciox. Ciox has been solving the identified data challenge: for a given patient, pulling all the medical records across institutions that the patient has visited. Historically, this has been a manual process, requiring deep last-mile relationships with providers and payers to get access to all the data. Ciox is the leader in this business, and manages billions of health data transactions a year on behalf of patients, providers, health systems and payers. Ciox technology and staff power all medical record access on behalf of 40% of health systems, and can access patient records for 100% of health systems as needed.
Together, our technology gives us deep relationships with the largest ecosystem of healthcare institutions in the United States. The combination of these two businesses unlocks the ability of all stakeholders to securely and privately exchange health data: powering patients, researchers, patient registries, public health agencies, clinical trial sponsors,Life Sciences companies, payers, providers, health analytics companies, and patient-facing apps.
We could finally give the health industry the data density it has lacked to power true transformation, and we can create the technology to ultimately make data access and exchange a safe, one-click process by patients and their healthcare institutions.
The time has come for a renaissance of data in healthcare. As we succeed in reducing the friction for data exchange, we will power thousands of companies in our ecosystem to build solutions that transform disease research, reimagine public health disease surveillance, improve clinical trials, and unlock personalized medicine.
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We are on a quest to connect the world’s healthcare data. It is the biggest data problem of our generation and an opportunity to save lives. We look forward to unlocking a data-driven future of healthcare.
PS – if this resonates with you, we’re hiring!
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.
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