Humana Healthcare Research modernizes medical insight with real-time, research-grade data

The challenge: fragmented data and delayed insight

Humana Healthcare Research operated in a legacy environment, with 30 years of historical data stored in SAS that was no longer suited to modern data science needs. While powerful in its time, the platform lacked essential capabilities for reproducible, collaborative research, including version control, shared logic, and transparent lineage.

Accessing historical data for longitudinal studies was complex and unreliable, despite the organization’s need to analyze trends across decades. Even more limiting was a six-week delay between data generation and availability, which significantly slowed research cycles and reduced the relevance of findings in fast-moving clinical and policy contexts.

These challenges were compounded by scale and security. Billions of medical and pharmacy claims flowed through tightly controlled environments designed to protect sensitive health data. While necessary, this infrastructure made it difficult to adopt new technologies or evolve existing processes. The result was an environment where data volume and velocity outpaced the tools used to manage them.

Without a new approach, the organization risked falling behind its own research ambitions.

The approach: agile, compliant data transformation with VaultSpeed

To overcome these constraints, Humana Healthcare Research partnered with VaultSpeed, with 7Rivers supporting implementation. The goal was not simply to modernize infrastructure, but to create a governed, research-grade data foundation that could scale with both data volume and scientific ambition.

VaultSpeed’s metadata-driven automation enabled Humana to unify 7 core data sources, including medical claims, pharmacy claims, member profiles, laboratory results, and EMRs, into a single, governed Data Vault architecture. Automation replaced manual pipeline development, dramatically reducing development time while ensuring healthcare-grade compliance and data consistency.

Just as importantly, analytical logic that was previously embedded in isolated scripts or lost over time is now preserved, versioned, and auditable. This ensures reproducibility, a cornerstone of credible medical research.

In less than three months, the foundational platform was nearing completion. The next phase introduces Change Data Capture mechanisms, enabling near-real-time detection of updates across billions of records and eliminating the six-week data lag that had previously constrained research.

From platform to proof: high-value research use cases

The implementation was designed around strategic research priorities, not abstract technical milestones. One of the first major data products focused on pharmacy claims, one of the most sensitive and time-critical domains in U.S. healthcare.

When prescriptions are issued, pharmacies must receive insurer approval within seconds. Historically, this data was difficult to analyze in near real time due to the limitations of legacy systems. With VaultSpeed, Humana can now ingest, structure, and govern this data so researchers can analyze approval patterns, identify coverage gaps, detect potential fraud, and evaluate treatment effectiveness with far greater speed and confidence.

Another key use case involves identifying rare or complex diagnoses that are not well represented by standard ICD codes. For example, Humana researchers developed enhanced logic to distinguish between small-cell and non-small-cell lung cancer, a critical differentiation for oncology research. VaultSpeed ensures this logic is preserved, versioned, auditable, and reusable, enabling it to be shared internally and licensed externally without losing fidelity.

Sepsis detection is also a high-priority initiative. By aligning laboratory results, diagnosis codes, and medical procedures into a single, time-aware dataset, researchers aim to enable earlier and more accurate risk detection, with full lineage and reproducibility built in from the start.

As new opportunities emerge, additional data sources are being integrated organically, prioritized based on research value and readiness. The platform continues to expand as both IT and research teams identify new ways to use trusted data.

As Jonathan K., Director of Data Offering, described the moment,

“We’re about to push the button.” That activation marks the first production release of the Raw Vault and a step change in data agility.

The impact: from six-week delays to real-time research

The introduction of VaultSpeed fundamentally changed how data is accessed and used within Humana Healthcare Research. Data availability moved from a six-week delay to near real-time access, allowing researchers to work with the most current information possible.

Pipeline creation shifted from manual, labor-intensive development to automated workflows, reducing error and accelerating delivery. Analytical logic that was previously difficult to trace or reuse is now governed, transparent, and preserved, strengthening trust in research outcomes.

The Data Vault architecture provides reliable access to decades of historical data, enabling longitudinal studies that track patient outcomes over 30-year periods. Data definitions are harmonized across sources, ensuring consistency across analyses and research teams.

With automation handling complexity, researchers and data teams can focus on higher-value scientific inquiry rather than data preparation.

The takeaway: a new standard for research-grade data

VaultSpeed has become a foundational part of Humana Healthcare Research’s data strategy. The organization is not just modernizing tools, but redefining how healthcare research is conducted at scale.

With a governed, automated, and real-time data foundation in place, Humana Healthcare Research is positioned as a research-grade data provider for the broader healthcare community, capable of delivering insights that can meaningfully influence patient care and health policy.