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Enhanced the existing MDM process and saved investment costs by upgrading to AWS

 

Client Background

The client is a major health insurance provider in New York State. It provides various health insurance plans under Medicaid, Medicare and commercial line of business.

Challenges

  • Build a process to push transactional system data to AWS S3
  • Migrate away from MuleSoft services
  • Build an application to convert provider data to XPF file to update FACETS data
  • Build a solution to convert member related domains from Facets to JSON and the pushing to Kafka
  • Migrate from Medmeasure to QI tool for generating HEDIS measures for health plan ratings
  • Generate required extracts to support and perform analysis for Value Based payment initiative
  • Enhance the existing MDM process to add EDW data as a source
  • Build data pipeline for clinical analytics

Solutions

  • Developed a DataStage job using AWS CLI commands to push data into the AWS S3 buckets from different sources such as Sybase, Greenplum & Oracle
  • Performed all the file operations such as insert, list & delete into the S3 buckets and for incremental runs
  • Analyzed all the MuleSoft services and migrated to Golang and ETL services using DataStage
  • Developed .NET application for XPF file generation
  • Created stored procedure for getting the member details from Facets and mapping the fields in .NET to create a JSON message and push to Kafka
  • Developed ETL jobs using DataStage and stored procedures to generate extracts for QI tool and VBP initiatives
  • Developed Informatica ETL and MDM Hub Jobs to include EDW Data as source in the MDM process
  • Developed tables and scripts to load data into EDW for Clinical Analytics

Tools & Technologies

Greenplum, .Net Framework, SQL Server, IBM InfoSphere, Information Builders Webfocus, Sybase IQ

Key benefits

  • Achieved sync between local storage and AWS identification of data marts that need to operate on top of AWS bucket for business analysis
  • Saved Mule infrastructure upgrade investment which resulted in achieved better performance through ETL and GO
  • Enabled business to meet the submission mandates/timelines, monthly incremental and outreach runs for 2020 with QI tool
  • Enabled business to identify and use the golden records from EDW data and consume it in downstream system across the organization
  • Enabled business to build clinical dashboards and reports
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