The life sciences industry is at a turning point. Ninety-seven percent of data generated by the healthcare sector goes unused. Despite the billions of dollars invested annually in generating, acquiring, and analyzing data—from clinical trials and real-world evidence to patient-generated data—many organizations remain constrained by one persistent challenge: data silos.
Data silos fragment the patient journey, preventing organizations from fully unlocking the value of their data and making informed, connected decisions.
Data silos in the life sciences industry stem from various factors, including fragmented data collection systems, proprietary data formats, and regulatory constraints. Many pharmaceutical and healthcare organizations collect vast amounts of data, but these datasets remain isolated due to differences in data structures, governance policies, and a lack of interoperability.
For example, a life sciences organization may collect multiple datasets that exist in stand alone silos, including:
Specialty pharmacy data
Clinical trial data
Hub support programs
Co-pay cards and patient assistance
Patient master lists
Marketing registrations
Sponsored genetic testing
Integrated data sets are critical to unlock deeper insights into patient journeys, treatment outcomes, and market dynamics
By adopting a secure framework for integrating disparate healthcare datasets while preserving patient privacy—known as a Linkable Data Infrastructure (LDI)—life sciences organizations can break down data silos and gain a more complete view of the healthcare landscape.
LDIs incorporate a privacy-preserving method to bring together proprietary, real-world, consumer ID, and other patient-level data.
Utilizing advanced linkage technology and privacy-enhancing solutions, LDIs provide life sciences companies with the capability to connect and analyze data across sources in a privacy-preserving manner, unlocking richer insights and driving more effective decision-making.
Implementing a Linkable Data Infrastructure: A Strategic Imperative
An LDI serves as the foundation for a more interconnected and insightful data ecosystem. Through the use of tokenization, which replaces personally identifiable information with unique, irreversible tokens, LDIs enable the secure linkage of datasets such as electronic health records (EHR), claims data, lab results, and specialty pharmacy data. This approach prioritizes patient privacy while facilitating a unified, patient-centric view of health data.
By deploying an LDI, life sciences organizations can overcome data silos and unlock valuable capabilities, including:
Comprehensive Patient Insights: Linked datasets provide a holistic view of patient journeys, enabling researchers and commercial teams to identify trends in treatment adherence, therapy effectiveness, and disease progression.
Optimized Market Access Strategies: Integrated data supports evidence-based discussions with payers, expediting the reimbursement process and improving patient access to therapies.
Enhanced Research and Development: The ability to connect clinical trial data with real-world evidence accelerates innovation, allowing pharmaceutical companies to validate drug efficacy and safety with greater precision.
Data-Driven Commercial Decision-Making: With a connected data infrastructure, organizations refine marketing strategies, streamline their data management strategies, and measure the impact of their commercial initiatives more effectively.
How to Maintain Privacy Compliance When Linking Health Data Sets
Prioritizing patient privacy while linking healthcare datasets requires a combination of secure data-handling techniques and robust privacy solutions. Two key components that enable privacy-centric data linkage are tokenization and privacy certification:
Tokenization for Privacy Protection: Tokenization replaces personally identifiable information (PII) with unique, irreversible tokens. This process supports the de-identification of sensitive health data while still enabling datasets to be securely linked across multiple sources. Since tokens are consistent across datasets, researchers and analysts can integrate patient records without revealing identities.
Privacy Certification for Risk Mitigation: Even with tokenization, linked datasets must undergo rigorous privacy assessments to ensure that the risk of re-identification remains low. Privacy certification solutions, such as Expert Determinations and statistical risk assessments, reduce risk that linked datasets might inadvertently expose patient identities. These privacy controls are critical in ensuring that data linkage efforts prioritize patient privacy, while still providing valuable insights for healthcare research and commercialization.
By combining tokenization and privacy certification, life sciences organizations can confidently link health data without compromising patient privacy. This approach enables a privacy-centric exchange of de-identified patient records, supporting more effective research, real-world evidence generation, and targeted healthcare interventions.
The ROI of Connected Data
The return on investment for organizations adopting an LDI extends across the therapeutic lifecycle, from early-stage research to post-market surveillance. Based on our actual use cases with top 20 life sciences organizations and industry projections, the power of connected data can drive:
Improved Adherence Rates: By understanding barriers like cost or adverse events, companies can achieve a 25% increase in medication adherence.
Optimized Data Spend: Consolidating redundant datasets saved one life sciences company more than $1.2M annually.
Impactful Marketing: More effective Google ad strategies in healthcare can realize up to 4x returns, helping drive incremental patient starts and reducing acquisition costs.
Revenue Growth: For products with low medication possession ratios, improving patient engagement and adherence can boost revenue by up to 10% by reaching the market's average compliance rate.
*ROI figures based on actual use cases seen in Datavant book of business with 18 of Top 20 Pharma and industry projections.
Real-World Success Stories
Data linkage has revolutionized operations for many life sciences organizations we work with. Below are examples of Datavant life sciences customers, showcasing the impact:
Filling Gaps in Therapy Adherence A top 20 pharmaceutical company sought to understand why a cohort of rare disease patients had not initiated therapy, despite completing start forms. By linking patient, specialty pharmacy, and claims data, they identified a cohort of patients who had never initiated prescribed therapy, and were empowered to analyze potential reasons, such as cost, access issues, or adverse events, while also tracking whether these patients opted for an alternative treatment.
Streamlining Data Procurement A life sciences firm reduced data vendor overlap by linking claims datasets. This consolidation has saved over $1.2 million annually, empowering the team to leverage its commercial investments more strategically.
Increased Funding for Research As part of a pilot program, a life sciences company sought a scalable solution to identify biomarkers for a specific disease population. With tokenization and real-world data connectivity, the organization identified more than 50,000 ICD-10 codes with statistically significant populations pertinent to its research. The work with Datavant empowered the organization to stratify patients using RWD, which enabled advanced patient journey modeling and control group creation — and ultimately helped secure a 10X increase in funding for the pilot program.
Building a Linkable Data Infrastructure: Key Considerations
Establishing an LDI is less about constructing something entirely new and more about strategically uniting existing resources and expertise. In our work with top pharmaceutical companies, the most successful approach prioritizes integration and efficiency over reinvention.
To establish an effective LDI, organizations must prioritize:
Privacy: A privacy-first foundation to linkage supports compliance with HIPAA, GDPR, and other regulatory frameworks when tokenized data is linked with other datasets.
Interoperability and diverse data sources: Adopting the industry’s ubiquitous token enhances access to data linkage sources, ideally from an ecosystem of more than 300 real-world data partners.
Proven best practices: Leveraging industry expertise, organizations should integrate first-party proprietary data (e.g., clinical trial outcomes, patient support data) with third-party and consumer datasets to create fit-for-purpose, actionable insights.
Scalability: A robust LDI should support future expansion, allowing organizations to incorporate new data types as the healthcare data ecosystem expands and new analytics capabilities develop.
The question isn’t whether life sciences organizations need a Linkable Data Infrastructure—it’s how well they can build and scale one
As the healthcare industry accounts for nearly 30 percent of the world’s total data volume, the demand for connected, actionable data is growing.
Organizations that embrace an LDI will not only streamline their data management strategies, but also gain a competitive advantage by delivering greater value for stakeholders — and better outcomes for patients.
A partnership with an industry expert like Datavant to design and scale LDIs ensures organizations maximize efficiency, proactively mitigate risks, and achieve sustainable differentiation.
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