Datavant powers the largest network of health data in the world. Our mission is to connect the world’s health data to improve patient outcomes, and we’ve made significant progress toward that goal: our partner ecosystem includes over 500 real-world data sources, covering all the major claims data sources, EHR data, SDOH data and novel data types such as genomics data and imaging.
With such a vast landscape, finding the right data partner is no simple task. Datavant today released Assess and Segment Builder, advanced feasibility tools within Switchboard that reduce the friction in health data exchange.
Fifteen years ago, the limit of a health data analysis might have been using prescription data to understand which providers were prescribing a certain therapeutic, or claims data to conduct an outcomes study. Today, the availability of additional data types like EHR, lab, and social determinants of health (SDOH) data, along with new providers, and traditional data types such as claims and prescription data, means more choice of data provider than ever. Additionally, the ability to link different data types using a common patient token means more powerful analyses and more context on the patient journey. Instead of just knowing what therapeutic a patient is on, you can understand why or why not patients are adhering to a treatment. This is only one example of how the healthcare data landscape has changed in recent years.
Two opposing forces that make navigating the health data landscape difficult for startups and industry giants alike are expansion and fragmentation. As novel data sources expand in availability, there is an increased demand for advanced analytics and data-driven insights. At the same time, this causes data fragmentation across institutions, burdening companies seeking to leverage the full breadth of available data. Preserving patient privacy is a final consideration in any health data exchange that has historically limited the utility of aggregated datasets.
The challenges are steep, but the insights gained have the potential to unlock significant improvements in patient outcomes. Such insights will be accelerated by having advanced tools to find and leverage the proliferating number of specialized data sources.
Datavant recently outlined Four Challenges the Health Data Ecosystem Needs to Solve in 2023, based on conversations with our Product Council. This group is comprised of privacy experts, health data super users, and thought leaders in healthcare.
Navigating the expanding landscape of health data is one of the key challenges outlined by the Product Council. To solve this challenge, they highlighted the role technology can play in helping facilitate dataset exploration, overlap comparison, and data segmentation. Today we are thrilled to announce the launch of Assess and Segment Builder, two new tools within the Datavant Switchboard that will unlock these capabilities for our customers.
Assessment of a potential partner’s dataset is a critical step in the health data exchange process. It’s common for companies to invest significant internal resources just to answer basic questions needed to vet a possible partner. Now with Assess and Segment Builder, these questions can be answered faster, in a neutral environment where multiple parties are involved, and without leaving the Datavant Switchboard which makes uploading and distributing datasets easier.
Assess is a toolkit that enables you to quickly understand patient counts within your own datasets or calculate the overlap across multiple datasets. With Assess, you can understand the data you have: quickly pull baseline feasibility counts for a customer’s request, or make sense of data across internal silos that may have formed due to mergers or acquisitions. Customers looking to form partnerships for academic or governmental research, clinical trials, employee health outcomes, or other research purposes can quickly evaluate the overlap or unique composition of multiple datasets to build the desired patient cohort. Assess contains four different types of reports that can be used independently or alongside each other for a variety of use cases.
Segment Builder is a tool that allows you to create a subset of a parent dataset using customizable join and filter criteria. With Segment Builder, you can create a segment that only contains the specific data you need (like breaking out patients from specific states, or with certain ICD codes). These subsets of your parent dataset can then be shared with a partner for distribution. You can also use your segments in Assess for feasibility analysis with other datasets, or to gather further insights on your own data.
With Segment Builder, you no longer need to re-upload individual cohorts or segments, and can instead upload your data once and create segments within Switchboard’s secure, private environment.
Before Segment Builder, I had to individually upload 12 different monthly datasets. Now I can just upload my entire parent dataset once, and in a fraction of the time, I can create 12 different segments by specifying my own filter criteria. I’m looking forward to finding other efficiencies with this tool that will help streamline our data workflows.”
— Brian M., Senior Director of Engineering
The Datavant Switchboard is used by top pharma companies, data analytics companies, employers, non-profit and academic institutions, payers, and providers to compliantly exchange health data across a range of use cases.
To explore how feasibility tools could accelerate your data partnerships, contact our team today.
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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