The Challenge

Disconnected systems and delayed insights

As one of the largest PBMs in the U.S., the company manages millions of prescription drug claims, coordinates with hundreds of pharmacy partners, and works with dozens of health plans and pharmaceutical manufacturers. But its legacy infrastructure couldn’t keep up with the increasing demand for timely, trustworthy data.

Business teams–across areas like clinical services, formulary and rebate management, compliance, and member engagement–relied on manual data extracts and outdated reporting tools. Each team had its own version of the truth, and getting a clear, timely view of performance metrics, such as formulary adherence or rebate yield, was difficult and slow.

The PBM needed a unified analytics platform that could:

• Ingest large volumes of structured and semi-structured data from internal and partner systems
• Improve data quality and governance
• Enable real-time dashboards and ad hoc analysis
• Support machine learning to detect fraud, forecast spend, and optimize programs

The Solution

A modern analytics platform built on AWS

AHEAD collaborated with the PBM’s IT and analytics teams to design and implement a secure, cloud-native data platform powered by AWS.

Data Ingestion & Storage

Using AWS Database Migration Service, AWS DataSync, and Amazon AppFlow, the PBM rapidly ingested data from internal databases, SaaS applications, and partner systems. All data was landed in Amazon S3, the foundation of the new enterprise data lake.

Data Governance & Cataloging

AWS Lake Formation enabled secure, role-based access and centralized governance. Data was cataloged for discoverability and made available for query across multiple analytics services.

Data Preparation & Transformation

With AWS Glue, AWS Glue DataBrew, and Amazon EMR, the PBM built repeatable ETL pipelines to clean and transform prescription claims, rebate data, and formulary lists. Business analysts could explore and refine data sets without relying on engineering teams.

Streaming & Real-Time Data

For scenarios like real-time claims adjudication or fraud detection, the PBM used Amazon Kinesis and Amazon Managed Streaming for Apache Kafka to process streaming data feeds and trigger alerts within seconds.

Analytics & BI

Teams across compliance, clinical operations, and finance use Amazon Athena and Amazon Redshift Spectrum to query data directly from S3. Executives and analysts rely on Amazon QuickSight for self-service dashboards that track formulary efficiency, rebate capture, member adherence, and more.

Machine Learning & AI

Using Amazon SageMaker and Amazon AI services, the PBM began piloting predictive models to detect fraudulent claims, forecast rebate revenue, and identify members at risk for non-adherence.

Business Outcomes

Scalable, Secure, and Insight-Driven

1. Unified View of Data

   Claims, rebate, and member data are now consolidated in a central lake, eliminating silos and manual reconciliation.

2. Faster Decision-Making

   What once took days is now available in minutes—real-time dashboards and selfservice queries have improved agility.

3. Improved Compliance and Audit Readiness

   With AWS Lake Formation, access is secure and auditable, meeting HIPAA and other regulatory requirements.

4. AI-Enabled Innovation

   Predictive models now support proactive strategies to reduce fraud, optimize formulary mix, and improve member outcomes.

5. Scalable Architecture

   The platform easily scales to handle seasonal peaks in claims volume, while reducing total cost of ownership.