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Academic Medical Center Defines Cloud Migration Strategy and Reduces TCO

About the Client

The client was a 1,200-bed academic medical center supporting complex clinical care, research, and teaching missions. Over time, the organization accumulated a large on-premises infrastructure footprint, resulting in rising costs, limited scalability, and slow access to analytics for population health and research initiatives.

Leadership wanted to modernize infrastructure using cloud-native services while maintaining data security, compliance, and operational continuity. To achieve this, the medical center engaged Zymr to define a comprehensive cloud migration strategy.

Key Outcomes

450 On-Prem Servers Consolidated into Cloud Strategy
37% Reduction in Total Cost of Ownership

Business Challenges

The environment included over 450 on-premises servers supporting clinical systems, research workloads, and administrative applications. Infrastructure sprawl increased operational cost and limited agility. Any migration strategy had to balance cost reduction with performance, data governance, and regulatory compliance. The organization also needed clarity on workload sequencing, data architecture, and cloud services that could support real-time analytics.

Business Impacts / Key Results Achieved

Zymr helped the academic medical center transition from infrastructure sprawl to a cloud-ready foundation. The strategy reduced costs, improved agility, and enabled advanced analytics while maintaining the security and compliance required in complex healthcare environments.

  • 450 On-Prem Servers Consolidated into Cloud Strategy
  • 37% Reduction in Total Cost of Ownership
  • Improved Scalability and Infrastructure Agility
  • Enabled Real-Time Population Health Analytics
  • Clear, Executable Cloud Migration Roadmap

Strategy and Solutions

Zymr developed a cloud-first migration and modernization strategy tailored to healthcare and academic requirements.

  • Infrastructure and Application Portfolio Assessment
    Evaluated 450 servers to classify workloads by criticality, risk, and cloud suitability.
  • AWS Migration Strategy and Sequencing
    Defined phased migration waves to minimize disruption to clinical and research operations.
  • HealthLake-Centric Data Architecture
    Designed a cloud data strategy leveraging AWS HealthLake for clinical and population health analytics.
  • Security and Compliance Alignment
    Incorporated healthcare-grade security, access controls, and auditability into the architecture.
  • Cost Optimization and TCO Modeling
    Modeled cost savings and operational efficiency gains from cloud consolidation.
  • Future Analytics Enablement
    Ensured the platform could support real-time population health and research analytics.
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