Our client is a Fortune 500 health care provider and the largest provider of kidney care services in the U.S., leading in clinical quality and innovation for 20 years. The company treats patients with chronic kidney failure and end stage renal disease. Through these efforts, our client has also become the largest provider of home dialysis in the country.
Business Challenge
Our client was faced with a number of business needs that prompted them to search for a new solution:
- Possibility to use a single application in all the clinics
- Single login IDs
- Ensuring easy system and data accessibility
- Avoiding data redundancy
- Easy training of new teammates
- Role based menus/modules
- System generated worklist of patients who need attention
- IT focused on individual roles
To meet their business needs our client introduced a new innovative centralized solution developed to replace the existing hosted in clinics set of core applications. The platform was developed based on DB2.
The platform’s estimated support load includes 3,000 clinics, 200,000 patients, 100M orders (critical volume), and 57,000 users (1,000 concurrent users).
However, our client’s architecture could not support business expected SLA for performance. Challenges included:
- Data quality and integrity
- System stability
- Performance at scale
- Time to business value delivery
- Disaster recovery
- Operational cost efficiency
To address these challenges, our client decided to transfer the platform from its datacenters to Google Cloud and from DB2 to Google Spanner.
SoftServe was consulted to implement a PoC to move data to Google Spanner to set up our client’s system and prove that performance could support all 3,000 clinics.
The platform features capabilities that can address implementation challenges including:
- Ability to use the platform in all clinics
- Horizontally scalable Cloud Spanner
- Manageable utilization and scalability of Google Cloud
- Security protection capabilities of Google Cloud
- System health monitoring and stability support
- Data analytics capabilities essential for predictive medicine



