Building a High-Performance Data Warehouse for 1.7 million Claims a Day
A leading medical clearinghouse in the U.S. healthcare ecosystem, processing over 1.5 million claims daily for a wide range of providers and payers.
The Need
The customer wanted to deliver data-driven insights to two primary audiences:
- End customer (providers): To help them analyze adjudicated claims, shorten their revenue cycles, reduce rejection claims, and manage denials.
- Internal sales and marketing teams: To analyze claims data and customer service requests with the goal of enhancing service offerings, identifying cross-sell opportunities, and driving strategic decision-making.
The customer’s existing system which ran on a large transactional database, introduced performance bottlenecks, and limited the scope for real-time/multi-dimensional analytics and reporting capabilities.
Therefore, the customer wanted to design and develop a robust data warehouse solution that supports high-volume processing and advanced reporting needs.
The Challenge
- Future-Proofing: The data warehouse had to be built so that it accommodates evolving reporting requirements and anticipated data growth.
- Anonymization: Claims data shared with the internal sales team had to be de-identified to avoid PHI (Protected Health Information) violations.
- Performance Optimization: ETL processes had to be highly tuned to handle massive data volumes efficiently.
- Changing Requirements: Continuous collaboration was needed to handle frequent changes in reporting needs from multiple stakeholders.
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