In today’s healthcare landscape, social determinants of health (SDOH) are increasingly critical for life sciences companies, payers, and providers alike.
SDOH describes the conditions in which people are born, grow, live, work, and age. These factors have a significant impact on overall health outcomes and can help us understand the root causes of health disparities. SDOH data consists of information related to:
By integrating SDOH data with clinical, claims, and other real-world data, organizations can better understand the social drivers of health outcomes, address disparities, and deliver targeted interventions.
When it comes to linking SDOH data with other real-world datasets, there are innovative approaches that can unlock greater efficiency in the privacy analysis of linked datasets.
This blog post will explore approaches, particularly through state de-identification, that can empower life sciences organizations to leverage SDOH data effectively while supporting stringent privacy standards, and how providers and payers can tap into SDOH data to close gaps in care.
By integrating SDOH data with clinical and other real-world data, life sciences companies can uncover deeper insights into population health, address gaps in care, and develop more effective therapies. The Datavant ecosystem, for example, has more than 300 real-world data partners and provides access and connectivity to a multitude of data sources, including: SDOH, clinical, specialty pharmacy, and claims data; patient records; and radiology images.
To increase efficiency in analysis of linked datasets, Datavant has introduced a method for datasets to proactively align to state-specific de-identification standards. State de-identification on a demographic dataset helps data organizations to comply with current state-specific privacy regulations by de-identifying datasets according to state standards, which may differ from HIPAA’s national requirements. This process lends an additional layer of security in sharing sensitive data by supporting state-level privacy controls.
SDOH data is a natural fit to proactively undergo state de-identification. The types of attributes in SDOH data are specifically covered by state privacy regulations, and since SDOH data is not health data, it is not governed by HIPAA (unless it’s linked with health data).
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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