Cloud-Based Healthcare Data Pipeline Modernization and Validation System

The client faces difficulties maintaining on-premise healthcare data systems that support clinical, financial, and operational data integration. These solutions are resource-intensive, inflexible, and costly to scale, leading to challenges in ensuring data accuracy, integrity, and compliance while supporting clinical decision-making and insurance calculations.

A large healthcare performance improvement organization providing SaaS analytics and operational solutions for clinical and administrative data management.

• Migrate existing on-premise healthcare data pipelines to a scalable, cost-efficient cloud architecture, increasing system flexibility and reducing operational costs.
• Ensure seamless migration of data pipelines while preserving existing business logic and functional capabilities.
• Enhance clinical data validation processes to improve accuracy, integrity, and regulatory compliance.
• Develop robust, scalable data processing workflows capable of handling peak loads and enabling advanced analytics and reporting.
• Implement automated deployment and continuous integration processes to improve resource utilization and reduce deployment time.

• Migration of existing ETL/ELT pipelines from on-premise to a cloud platform (e.g., Azure or equivalent).
• Implementation of multitenant, scalable architecture capable of withstanding peak processing loads.
• Conversion and optimization of data processing scripts (e.g., PySpark) to cloud-native environments (e.g., Databricks).
• Integration of automated build and deployment pipelines using CI/CD tools (e.g., Azure DevOps, Octopus Deploy).
• Development of data validation rules and monitoring to ensure data quality and compliance.
• Implementation of a centralized data warehouse (e.g., Delta Lake) for storing historical and processed clinical, financial, and operational data.
• Development of dashboards or reporting tools to support clinical and financial performance analysis.

• Source healthcare databases and clinical systems for data ingestion
• Financial and operational reporting systems
• Regulatory compliance systems for data validation and security testing

• Support for high concurrency and peak loads, with resistance to performance degradation during surges.
• Robust data security, compliance with healthcare regulations (e.g., HIPAA), and encryption in transit and at rest.
• High availability and disaster recovery capabilities to ensure continuous operation.
• Automated deployment pipelines to minimize downtime and ensure consistent environments.

The project aims to enable the client to deliver cost-effective, scalable healthcare data solutions that improve patient outcomes and operational efficiency. Expected outcomes include reduced infrastructure and maintenance costs, improved data accuracy and compliance, and enhanced analytics capabilities leading to better clinical and financial decision-making.