Synthetic test and development data with a leading EMR and healthcare solutions

About the client

The company specializes in developing and supporting a proprietary electronic medical record (EMR) software application widely recognized for its comprehensive approach to healthcare data management. The software is built around a robust database management system, providing solutions for various aspects of patient care, including registration, scheduling, and clinical systems for healthcare professionals across different specialties. It also supports essential functions for lab technologists, pharmacists, and radiologists, in addition to handling complex billing systems for insurers. The application is widely used for patient access to medical records and billing, serving over 150 million patients. Many of the top-ranked hospitals and medical schools rely on this software for their electronic record systems. 

The situation

The organization faced numerous challenges due to the interdependency of applications across various platforms, in managing test data for a complex Service Oriented Architecture (SOA). 

These interconnected applications support multiple end-to-end business processes that span different systems, leading to significant data dependencies and complexities. Each application often consumes different data formats, complicating the testing processes, especially when critical dependent components are missing from some test environments.  

The presence of intricate business rules and the necessity for data processing across multiple functional areas further add to the data complexity. Managing multiple environments for projects, development, and testing, each with varying degrees of integration and data content, becomes a difficult task, especially within a hybrid traditional waterfall and Agile development model. 

Existing test data tools largely supported the needs of individual applications or business processes, but failed to consider the broader picture of interlinked systems. 

Developers worked with smaller copies of production environments to maintain efficiency, but these had to be manually dropped and restored by the QA teams after each test run. 

The solution

Facing significant challenges in test data management, the organization and the DevOps team recognized the need for third party solution to drive efficiency and support test data growth. Their key objectives included faster test data provisioning, enhanced automation, and improved database lifecycle management across multiple platforms. With around 50 environments running simultaneously, and the need to create or update environments frequently, the team needed a robust solution to streamline these processes. Previously, creating a new environment took up to 128 hours, and environment updates for pushing new code or refreshing after tests took 30 minutes. 

The introduction of an advanced test data management tool transformed their operations. 

The solution created database copies that were only a fraction of the original size, allowing for rapid creation, updating, and refreshing of environments. This change drastically reduced the time required to set up a new environment to as low as 2 hours, including all infrastructure components, and slashed update times to less than 5 minutes. 

Although their infrastructure was primarily SQL Server-based, the team also had products on Oracle and was exploring PostgreSQL for new services. The flexibility and capabilities of the new test data management solution not only supported their existing databases but also facilitated their expansion into PostgreSQL. This comprehensive approach enabled the technical team to efficiently manage their diverse database needs, significantly enhancing their operational agility and opening new growth opportunities. 

The new solution (i.e. Syntho) also solved their problem of maintaining data consistency and integrity across different systems and over different data generation jobs. The tool allowed them to de-identify/mask their data, while maintaining the ability to test and draw inferences across different systems.