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Client Background
A leading health-tech company providing digital platforms for U.S. Health Plans, Providers, and Hospitals sought to strengthen patient engagement and modernize operational workflows. Their goal was to enhance eligibility checking, improve referral coordination, and create a more resilient, scalable ecosystem for their Patient Engagement Suite (PES).
Client Need
Develop PES to strengthen provider–patient interaction
Enhance eligibility verification for accurate and fast coverage validation
Improve referral workflows for streamlined provider coordination
Add Assurance digital biller features for scheduling, prescription management, and information retrieval
Build a best-in-class referral navigator to maximize provider revenue
Enable real-time data exchange between the PES and Luma Health
Integrate existing microservices with Luma APIs
Build a real-time eligibility engine for the PES
Solution
End-to-End Integration Framework
- Built a PES Integrator to seamlessly synchronize data with Luma Health
- Implemented pre-/post-processor workflows enabling real-time eligibility checks
Cloud-Native Architecture
- Designed and deployed a microservices-based architecture
- Leveraged Terraform and Google Apigee for infrastructure automation and API management
- Implemented serverless functions for scalable, cost-efficient operations
Data Governance, Logging & Resilience
- Built a Data Access Event Logging Library for auditability and traceability
- Created a Data Disaster Recovery Playbook for AWS RDS, strengthening database resilience
Platform Quality & Security
- Developed automated test frameworks using K6 and Newman
- Conducted structured audit cycles and proactively remediated security issues prior to launch
Agile Delivery & Engineering Scale
- Established three independent Scrum teams, enabling parallel development
- Implemented a Team Knowledge Funnel and asynchronous communication model to streamline collaboration
Realized Benefits
Reduced AWS RDS MTTR by 75%, improving system resilience
Delivered a fully scalable PES architecture with 17 components, 6 libraries, 22 microservices, and 28 Lambdas
Launched a real-time eligibility engine with 4 components, 2 libraries, 14 microservices, and 16 Lambdas
Remediated 14 security defects before GA to ensure a secure launch
Achieved high availability, observability, and DR capabilities
Scaled engineering capacity through three autonomous Scrum teams
Tools & Technologies
Terraform
Google Apigee
AWS
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