CASE STUDY

Disrupting the Pharmacy Benefit Management Market

Customer Overview

RxSense LLC is a US pharmacy benefit management (PBM) company headquartered in Boston with offices in New York, New Jersey, and Florida.

The company partners with its clients to provide the highest quality prescription healthcare services at the lowest price.

As a PBM responsible for developing and maintaining formularies, contracting with pharmacies, negotiating discounts and rebates with drug manufacturers, and processing and paying prescription drug claims, RxSense’s ability to access and manage large amounts of data is critical.

1998

Founded

$3B+

Annual managed pharmacy program drug spend.

Expertise in Digital Services & Industry Leading Tools

Business Goals

Digital Transformation

upgrade IT infrastructure to support new market demands

Higher Service Levels

address new and increasing customer requirements

Streamline Operations

make the company more agile and efficient

The Challenge

With more than 20 years as a forward-thinking health and technology industry leader, RxSense had experienced first-hand, the pain of being tied to antiquated, traditional PBM legacy systems – long implementation timelines, plan design changes requiring IT and development teams, black-box pricing and more.

The company wanted to fundamentally change its business model to solve these challenges and more with a new cloud-based enterprise platform solution that would simplify pharmacy benefit design, management, and execution in an infinitely scalable environment, including the underlying databases and analytic tools.

In traditional systems, RxSense would have needed to purchase more and more databases to keep up with expanding datasets and users. In addition, the limitations of traditional database architectures made each successive expansion progressively less effective.

To design a platform and analytic environment that delivers on the promise of expanded data access and insight, RxSense believed that it had to completely discard traditional data architectures like its existing Microsoft SQL solution and look at more flexible, affordable and scalable solutions based in the cloud.

The Solution

RxSense’s IT team engaged with Infostretch’s digital engineering team to help diagnose and solve for the best path forward.

Infostretch’s extensive digital skillset, and specific experience in healthcare was an important factor in the decision.

After working with the RxSense team, and taking into account all the factors involved, the Infostretch team recommended a cloud-based data warehouse and data analytics solution built on AWS and Snowflake.

Not only would this approach be able to handle and scale easily with RxSense’s growing data management needs, it would also enable RxSense to automate many of the manual business functions which were core to the problem.

The scope of Infostretch’s engagement included:

  • Ideation and blueprinting of their revised workflows with a complete Proof of Concept of the future state user experience and underlying architecture to support the scale RxSense required
  • Seamless migration from Microsoft SQL to AWS
  • Assistance employing DevSecOPs and Cloud Native process to bring efficiency and scale to its PBM operations
  • Development of an implementation wizard with a new, flexible, affordable and scalable architecture and analytic environment that delivered on the promise of expanded data access and insight
  • Automation of key business functions such as invoicing and margin calculation, eliminating expensive manual efforts and errors
  • Providing RxSense clients with access to real-time performance data to better understand and manage their business

After completing the initial project discovery phase and a proof of concept, Infostretch laid out a five step execution plan for RxSense

1

Migration of Legacy ETL to Matillion Jobs

2

Migration of Data Analytics Reports
pointing to Snowflake

3

Automate Invoice Margin Calculation

4

Real-Time Data Ingestion into Data Warehouse

5

Providing Technical Support

1. Migration of Legacy ETL to Matillion Jobs

Existing ETL jobs were being implemented using Microsoft SSIS and Informatica ETL.

With the new solution, all jobs had to be migrated to Matillion Jobs to extract, transform and load data into Snowflake. This included around 60+ jobs to be migrated to support different business functions.

Key steps included:

Identifying Data Sources

Understanding existing implementation

Implementing Matillion Jobs

Testing Jobs

2. Creation of data analytics reports
pointing to snowflake

Approximately 25+ reports were developed to point to Snowflake Data Warehouse.

Core activities included:

Understanding existing queries used for reporting

Migrating queries to support Snowflake syntax

Validating reports

3. Automation of Invoice Margin Calculation

Price management was a key service provided by RxSense including the calculation of invoice margins.

To date this had been a manual process – with contract rules maintained in Excel spreadsheets and invoice margins calculated by finance personnel for each contractor every 15 days. Infostretch developed a custom module using Matillion Jobs – automating the entire process from calculating the Pharmacy invoicing margin to sending invoices to contractors.

Developing the module included:

Understanding and incorporating invoice calculation rules

Design and implement the UI Portal to manage the rules

Prepare Snowflake queries to calculate invoice pharmacy rules the rules

Implementing Matillion Jobs the rules

4. Real-Time Data Ingestion into Data Warehouse

Existing jobs were transferring data on a daily basis.

As a result, there were no real-time updates being made to the data warehouse or in the reports. To mitigate this issue, Infostretch has reduced from daily transfers to twice an hour (or every 30 minute) jobs and is working on a proof of concept where Infostretch enables records to be streamed from RxSense’s transaction database system to a Kafka messaging system and ingested into the Snowflake data warehouse system.

This phase involved:

1

Implementing CDC mechanism

2

Configuring Source Kafka Connector the rules

3

Implementing transformation jobs the rules

4

Configuring Sink Kafka Connector – Snowflake the rules

5. Providing Technical Support

In parallel to the four phases above, Infostretch provided (and continues to provide) technical support for each implemented component.

Technical Achievements & Outcomes

Increased
Revenues

50% revenue growth within first 12 months

Higher Service
Levels

Reduced customer on-boarding time – from 90 days to a few hours

Faster Cycle Time,
Reduced Costs

Increased automation, agility and scale; easy access to performance data

About Infostretch

Infostretch leverages a proven combination of technology, processes, and expertise to help enterprises accelerate the execution of their digital strategy. We deliver faster and more effectively by unifying expert professional services and best practices with pre-built software frameworks and products. Our 1,000+ development, testing and integration specialists have deep capabilities in DevOps, QE, app development, Cloud, AI, IoT and mobility.