Executive Summary
When slow data reporting threatened patient care and rising costs strained operations, a leading U.S. healthcare payer tech company managing complex Medicare and Medicaid populations, on behalf of their large payer clients, needed a way out.
Managing 2,000+ nurse practitioners who visited patients, assessed their health, and routed reports to payers for comprehensive clinical profile, our client needed a robust system to handle massive clinical datasets across members, providers, claims, HRAs from multiple sources.
PalTech engineered a custom data lakehouse that unified fragmented sources, eliminated costly third-party dependencies, and delivered real-time insights through Power BI and Generative AI-driven augmented analytics for decision making. The result: faster insights, lower costs, and a data ecosystem built for scale.
Business Problem
Data bottlenecks were putting patients and operations at risk
A leading healthcare payer tech company serving payers with high-risk populations across the U.S. and Puerto Rico found itself tangled in data complexity. Reports dragged due to outdated systems, while operational costs ballooned from reliance on third-party vendor driven on ground operations of nurses.
Their existing 20-25 Tableau reports were slow, limited in scalability, and lacked customization, making it difficult to meet operational needs. Our client’s existing tools couldn’t keep up with the growing demand for rapid, reliable data.
Every delay threatened the quality of personalized care analytics they promised to payers—a risk they couldn’t afford. Without a centralized, scalable reporting system, they faced rising costs, operational bottlenecks, and frustrated stakeholders demanding timely, accurate data.
For a company built on timely, high-touch care, solving this data challenge was mission-critical.
Solution Implemented
PalTech built a data powerhouse with a scalable lakehouse, automated pipelines, and AI driven augmented reporting
To solve these challenges, the healthcare payer tech company chose PalTech for its deep expertise in designing scalable, high-performance data solutions. PalTech’s track record with complex data structures and multi-technology integration made them the ideal partner. Understanding the client’s need for speed, accuracy, and cost efficiency, PalTech built a comprehensive data lakehouse from the ground up, integrating multiple data sources into a single, reliable platform.
The solution addressed the client’s scalability issues, eliminated dependency on third-party vendors, and ensured seamless reporting through Power BI and augmented analytics feed. Every step was meticulously planned, from data integration to user access, ensuring a future-proof system.
Solution Implementation:
Medallion Architecture
- Structured the data architecture into bronze, silver, and gold layers, ensuring raw data is processed into high-quality, real-time insights for payers. This multi-tiered approach optimized performance, improved data governance, and accelerated AI-driven decision-making.
Canonical Data Model
- Standardized payer data across multiple systems, enabling seamless data interoperability, automated processing, and consistency across all reporting layers.
Unified Data lakehouse
- Consolidated disparate sources, optimized data flow, and accelerated query performance with precision-engineered indexing.
AI driven augment analytics
- Created customized feeds to top management with descriptive analytics with clear identification of key KPIs from data and recommended steps to act immediately to improve decision making.
Automated Data Pipelines
- Deployed Azure Data Factory, Databricks, and SSIS for seamless real-time and batch data processing with intelligent error handling.
Optimized Datamarts
- Built centralized fact tables with smart partitioning for rapid data retrieval.
Robust Scheduling System
- Managed 25M+ records per load with custom SQL Agent Jobs for prioritized execution, tracking job statuses and alerting for failures or dependencies through a custom scheduler.
Proactive Monitoring and Alerts
- Introduced centralized logging and real-time alerts, strengthening data governance and compliance.
Enhanced Power BI Experience
- Secured data access with role-based controls, ensured real-time data refresh via APIs, and offered customizable visuals like Azure Maps for granular insights.
Benefits Achieved
Unlocked speed, security, and a future-ready data platform
PalTech’s tailored solution delivered immediate and lasting benefits. The payer tech cut operational costs and boosted operational agility with automated workflows. Built for growth, the new system scaled effortlessly with evolving data needs while ensuring airtight security and easy user access.
Key Benefits:
● Reduced Costs: Third-party reporting fees were eliminated, significantly lowering operational expenses.
● Real-Time Insights: Instant access to AI driven descriptive analytics augmented feed has transformed decision-making speed.
● Streamlined Operations: Automation minimized manual processes, reducing errors and freeing up resources.
● Scalable Architecture: Designed to handle expanding data volumes without performance dips.
● Fortified Security: Advanced role-based controls ensured data integrity and compliance.
● Enhanced User Experience: A seamless platform provided stakeholders with quick, reliable access to data when they needed it most.
With consistent report migrations, proactive updates, and ongoing support, PalTech equipped the provider with the tools to thrive in a data-driven future.
Key Features
Third-party reporting fees were eliminated, significantly lowering operational expenses.
Instant access to AI driven descriptive analytics augmented feed has transformed decision-making speed.
Automation minimized manual processes, reducing errors and freeing up resources.
Designed to handle expanding data volumes without performance dips.
Advanced role-based controls ensured data integrity and compliance.
A seamless platform provided stakeholders with quick, reliable access to data when they needed it most.
Technology Stack
