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Building A Unified Benefits Data Repository for Real-Time Eligibility and Enrollment Processing

Authors

Murugan Ambalakannu

Director Consulting Services, CGI (US)

Article Information

DOI: 10.51583/IJLTEMAS.2026.15020000084

Subject Category: Cloud Computin

Volume/Issue: 15/2 | Page No: 949-958

Publication Timeline

Submitted: 2026-03-19

Published: 2026-03-19

Abstract

The establishment of a Unified Client Database (CDB) system and the associated ePRO program has dramatically improved the efficiency of benefits administration for organizations. This client-centric approach provided the Technical Lead from the Engineering Group with the ability to create an end-to-end data framework using normalized, metadata-driven design that supports intricate multi-client benefit structures, secured ETL/API connections to ensure seamless integration of enrolment, human resource and claims systems with robust data governance through automated data validation, audit logging and version control. The platform was developed for a cloud-based environment with the use of Redshift to support analytics and AWS S3 to serve as the archive for the repository of data, supported with telemetry dashboards to enable real-time visibility into the health of synchronization and ingestion latency. Implementing the platform has resulted in near real-time downstream integration with the subsequent increase in the timeliness and accuracy of data which has reduced the number of manual reconciliation errors by greater than 25% while improving compliance controls. In alignment with the trend towards the utilization of data-based automation within enterprise EPM Modernization, the CDB platform enables organizations to onboard clients quicker, achieve greater operational transparency and provide a scalable foundation for future cloud services. The next phase of enhancements will seek to evolve the CDB platform into a fully automated cloud-based ecosystem, including developments related to AI-based anomaly detection; enhanced capabilities to expand on serverless microservices; and advanced analytics using Redshift to provide predictive insight regarding benefit-related usage.

Keywords

Unified Client Database (CDB) system, Cloud-Based Environment, EPM Modernization, Serverless Microservices

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References

1. “Challenges and Opportunities of Big Data in Health Care: A Systematic Review”, Clemens Scott Kruse, Rishi Goswamy, Yesha Raval, Sarah Marawi, 2016 Nov 21, https://doi.org/10.2196/medinform.5359. [Google Scholar] [Crossref]

2. "How to Deal with the Challenges of Benefits Administration", November 18th, 2021, https://www.obsidianhr.com/how-to-deal-with-the-challenges-of-benefits-administration/. [Google Scholar] [Crossref]

3. “The Benefits of Client Database Management for Service Businesses”, Kirsten McNeice, December 17, 2020, https://www.accelo.com/crm/client-database-management-benefits. [Google Scholar] [Crossref]

4. “Developing a Relational Database for Best Practice Data Management: The TEAM-UP Database”, Jenny Alderden, Phoebe D Sharkey, Susan M Kennerly, Sanjay Ghosh, Ryan S Barrett, Susan D Horn, Sayoni Ghosh, Tracey L Yap, 2023 Feb 1, https://doi.org/10.1097/CIN.0000000000001011. [Google Scholar] [Crossref]

5. "A Framework for Data Quality - FCSM-20-04", September 2020, https://nces.ed.gov/fcsm/pdf/FCSM.20.04_A_Framework_for_Data_Quality.pdf. [Google Scholar] [Crossref]

6. "The data-driven enterprise of 2025", January 28, 2022, https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-data-driven-enterprise-of-2025. [Google Scholar] [Crossref]

7. "A systematic literature review towards a conceptual framework for enablers and barriers of an enterprise data science strategy", Rajesh Chidananda Reddy, Biplab Bhattacharjee, Debasisha Mishra, Anandadeep Mandal, 2022, https://ideas.repec.org/a/spr/infsem/v20y2022i1d10.1007_s10257-02200550-x.html. [Google Scholar] [Crossref]

8. "Factors Influencing Master Data Quality: A Systematic Review", Azira Ibrahim, Ibrahim Mohamed, [Google Scholar] [Crossref]

9. Nurhizam Safie Mohd Satar, 2021, https://thesai.org/Downloads/Volume12No2/Paper_24Factors_Influencing_Master_Data_ Quality.pdf. [Google Scholar] [Crossref]

10. “A systematic literature review on data quality assessment”, Oumaima Reda, Naoual Chaouni Benabdellah, Ahmed Zellou, 2023, ISSN: 2302-9285, DOI: 10.11591/eei.v12i6.5667. [Google Scholar] [Crossref]

11. “Quality assessment of real-world data repositories across the data life cycle: A literature review”, SiawTeng Liaw, Jason Guan Nan Guo, Sameera Ansari, Jitendra Jonnagaddala, Myron Anthony Godinho, Alder Jose Borelli Jr, Simon de Lusignan, Daniel Capurro, Harshana Liyanage 2, Navreet Bhattal, Vicki Bennett, Jaclyn Chan, Michael G Kahn, 2021 Jan 26, https://doi.org/10.1093/jamia/ocaa340. [Google Scholar] [Crossref]

12. "Secure data movement across Amazon S3 and Amazon Redshift using role chaining and ASSUMEROLE", Sudipta Mitra, Lisa Matacotta, Michelle Deng, Jared Cook, 28 APR 2022, https://aws.amazon.com/blogs/big-data/secure-data-movement-across-amazon-s3-and-amazon-redshiftusing-role-chaining-and-assumerole/. [Google Scholar] [Crossref]

13. “Improve clinical trial outcomes by using AWS technologies”, Mayank Thakkar, Deven Atnoor, 11 APR 2019, https://aws.amazon.com/blogs/big-data/improve-clinical-trial-outcomes-by-using-awstechnologies/. [Google Scholar] [Crossref]

14. "ETL orchestration using the Amazon Redshift Data API and AWS Step Functions with AWS SDK integration", Jason Pedreza, Bipin Pandey, David Zhang, 02 MAR 2022, https://aws.amazon.com/blogs/big-data/etl-orchestration-using-the-amazon-redshift-data-api-and-awsstep-functions-with-aws-sdk-integration/. [Google Scholar] [Crossref]

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