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Data Mapping and Translation in
EDI System Generating EDI-834

How A3Logics helped a client to achive a streamlined and efficient benefits data exchange process.

OVERVIEW

Our client a large healthcare organization wrestled with inconsistent benefits data from various internal systems. This made generating EDI-834 files difficult and error-prone. They required a solution that ensured HIPAA compliance and streamlined data exchange. Using Java, A3Logics was able to create a unified data model, a robust mapping engine, and secure data handling.

CHALLENGES
  • Diverse Data Sources: The organization faced challenges with benefits enrolment data coming from various internal systems, each with its unique structure for employee benefits information.
  • Inconsistent Data Formats: Enrolment data for benefit plans like Medical, Dental, Vision, Life, STD, LTD, FSA, HAS, and others can be in Inconsistent data formats because it is populated from different enrolment systems leading to difficulties in mapping and translation.
  • HIPAA Compliance: The organization needed to ensure that the EDI system complied with HIPAA regulations, which mandate secure and private health information exchange.
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OUR SOLUTIONS
  • -Unified Data Model: Implemented a unified data model that served as a central representation of employee benefits data. This model facilitated standardized data across all internal systems.
  • -Data Mapping and Transformation Engine: Developed a robust data mapping and transformation engine using Java to translate data from different sources to the standardized format required for EDI-834.
  • -HIPAA-Compliant Security Measures: Implemented strong encryption, access controls, and audit trails to ensure the security and privacy of sensitive health information, aligning with HIPAA compliance requirements.
RESULTS ACHIEVED
  • – Data Mapping Accuracy: Achieved a 99.5% accuracy rate in data mapping and translation, significantly reducing errors in EDI-834 files.
  • – Real-Time Processing Time: Reduced processing time for EDI-834 generation to less than 2 minutes for a typical batch of employee benefits data updates.
  • – HIPAA Compliance Audit: Successfully passed a third-party audit confirming compliance with HIPAA regulations regarding data security and privacy.
TECH STACK
  • -Programming Language: Java
  • -Data Modeling: Unified data model for benefits information
  • -Data Mapping and Transformation: Custom Java-based engine
  • -Security: Encryption, access controls, audit trails
CONCLUSION

The implementation of a Java-based EDI system successfully addressed the challenges related to data mapping and translation for EDI-834 generation. By unifying data models, developing a robust transformation engine, and ensuring HIPAA compliance, the organization achieved a streamlined and efficient benefits data exchange process. The solution not only improved data accuracy but also enhanced the organization’s ability to respond to changes in benefits information promptly. This case study demonstrates the effectiveness of a well-designed Java-based EDI system in overcoming data mapping and translation challenges in the context of healthcare benefits administration.