Canada
Puerto Rico
USA
Belgium
France
UK
India
Client Background
The client is a leading healthcare provider in the US.
Client Need
The client sought an Enterprise Imaging Network to optimize medical imaging data and improve clinical, financial, and operational outcomes. Key challenges include:
Limited capital and operational budgets
Stringent regulations and mandates for data archiving, sharing, retention policies, and auditing
Increased threat of data breaches and limited IT resources created significant security vulnerabilities
Lack of expertise to stay updated with rapid technological advancements to adopt AI and machine learning
Solution
Architected to host diverse, multi-service applications, the GCP platform uses Kubernetes clusters (and optionally, VMs) for deployment
Automated via Jenkins-executed CI/CD pipelines and built workflows
Developed on GCP with a C#/.NET Core microservice architecture, all services are monitored by the cloud operations team using Grafana and Stackdriver, with PagerDuty for alerts
Realized Benefits
Effortless handling of massive imaging volumes, including 1.16B+ studies, 230M+ patients, 1TB of data, and 96B+ images annually
Enhance delivery to 25% of U.S. hospitals and 3,300+ imaging facilities globally, including 100+ multi-hospital systems
Future-proofed cloud native architecture for the era of Big Data and AI
Tools & Technologies
Google Cloud Platform
DevOps
Visual Studio Team Foundation Server
Kubernetes
HashiCorp Tettaform
Jenkins
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