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Background

To improve their data management and analytics capabilities, a Medicaid health plan decided to enhance their existing Enterprise Data Warehouse (EDW) by integrating additional data sources and optimizing performance.

Challenge

The health plan faced several challenges in managing and analyzing their diverse data:

  1. Integrating multiple data sources into the existing EDW
  2. Meeting strict service level agreements (SLAs) for data load times
  3. Incorporating additional data sources for comprehensive analysis
  4. Optimizing performance to handle large volumes of data efficiently

Solution

To address these challenges, the health plan implemented enhancements to their Enterprise Data Warehouse solution with the following features:

    1. Integration of medical claims, pharmacy claims, and membership data
    2. Performance optimization techniques
    3. Incorporation of additional data sources
    4. Improved ETL (Extract, Transform, Load) processes

Implementation

The implementation process involved several key steps:

  1. Data integration: Medical claims, pharmacy claims, and membership data were successfully integrated into the existing EDW.
  2. Performance optimization: Collaborative efforts were undertaken to improve runtime efficiency.
  3. Additional data sources: Capitation, Pharmacy tiers, and Health Risk Assessment data were incorporated into the EDW.
  4. SLA monitoring: Processes were established to track and meet service level agreements for data load times.

Results:

The enhancement of the EDW yielded significant improvements:

1

Improved efficiency

A 30% improvement in runtime efficiency was achieved through optimization efforts.
2

SLA compliance

The system consistently met service level agreements, with only a minimal number of days where load times fell short of expectations.
3

Comprehensive data integration

Successfully integrated data from various sources, including Capitation, Pharmacy tiers, and Health Risk Assessment data.
4

Enhanced analytics capabilities

The integrated data enabled more comprehensive analysis for downstream projects.

Conclusion:

The enhancement of the Enterprise Data Warehouse for the health plan has significantly improved their data management and analytics capabilities. By successfully integrating diverse data sources, optimizing performance, and consistently meeting SLAs, the health plan has enhanced its ability to make data-driven decisions and improve services for Californians seeking health insurance. The enhanced EDW now serves as a robust foundation for various downstream projects, enabling more comprehensive and efficient healthcare analytics to support their mission of providing affordable, high-quality health insurance options.