Health Equity
Creating a more equitable system for the health of America.
Organization: Blue Cross Blue Shield Association
Role: Solutions Architect
Team size: 50
Project overview: Designed and delivered the data infrastructure to equip all Blue Cross Blue Shield health systems with standardized, granular demographic data — the foundation for identifying and eliminating health disparities across millions of American patients.
Mission Statement
Everyone should have access to affordable, high-quality health care regardless of race, ethnicity, national origin, sex, gender identity, sexual orientation, disability, or age.
“Your health shouldn’t depend on the color of your skin, where you live or how much money you make. But for too many Americans, those factors stand in the way of achieving good health and well-being.”
- Blue Cross Blue Shield Association
Solution
You can't fix what you can't measure. The BCBS National Health Equity Strategy starts with data — standardized, reliable, and granular enough to reveal disparities that aggregated numbers hide.
“Data is foundational to understanding disparities in health and to measuring our progress in eliminating them.”
- Blue Cross Blue Shield Association
My role was to build the system that makes that data real: designing the architecture, leading the delivery, and ensuring the platform could scale across dozens of independent BCBS organizations without sacrificing consistency or patient privacy.
Technical Details
As Solutions Architect, I owned the full project lifecycle — from business case and system assessment through architecture, proof-of-concept, implementation, and delivery. I led teams of domain experts and technologists, balancing the technical complexity of a distributed data platform with the operational reality of organizations at very different levels of technical maturity.
Key deliverables:
• ETL framework processing thousands of vendor data feeds covering millions of patients
• Scalable compute architecture using data partitioning and pipeline-based processing
• Distributed computation, caching, and queue-based design to meet strict performance and reliability SLAs
• Replacement of legacy systems that required extensive manual operation and maintenance
• Generative AI integration for business rule-to-code transformation\
• Business self-service capabilities enabling non-developers to make software changes independently
• Patient privacy and security controls embedded throughout the architecture)
• Generative AI for business rule to code transformation
• Built on the Ab Initio software stack for large-scale data processing and analytics
Result
The platform gave BCBS organizations something they didn't have before: the ability to see their patients clearly enough to act. One early example — Independence Blue Cross used the combined data to identify disparities in maternal health outcomes across specific ZIP codes in Philadelphia, then partnered with Cayaba Care to deploy maternity navigators for at-risk women throughout and beyond their pregnancies. That kind of targeted intervention isn't possible without the data infrastructure to surface it.