Centralized Data Warehouse for a Multi-Site Hospital: Case Study
About the Client
- Industry: Healthcare (Hospital)
- Location: Saudi Arabia
- Organization Size: 5 hospitals with 1,000+ employees across clinical, administrative, and support services
- Primary Focus: Centralizing patient and operational data, ensuring compliance, and optimizing resource allocation
Client Requirements and Challenges
- Data Fragmentation Across Hospitals
Each hospital operated independently, with siloed data from EHRs, billing systems, and diagnostic tools, leading to duplication and inefficiencies. - Compliance with Regional and Global Regulations
The client needed to comply with Saudi-specific SeHE standards, in addition to HIPAA, for protecting sensitive patient data. - Delayed Operational Insights
Management struggled to access real-time data for decisions like staff allocation, patient flow, and financial performance. - Inconsistent Reporting
Reports for compliance and operational KPIs were generated manually, leading to inconsistencies and delays. - Scalability Challenges
The existing systems couldn’t scale to meet the growing data needs as patient numbers increased across multiple locations.
Solution Overview
Bioteknika implemented a centralized PostgreSQL-based data warehouse with automated ETL workflows, role-based access controls, and advanced reporting features. This solution provided a unified platform for operational and clinical data, ensuring compliance and efficiency.
Solution Details
1. Centralized Data Warehouse with PostgreSQL
- Deployed PostgreSQL on a hybrid setup (on-premise with optional cloud backup) to store and manage data from all five hospitals.
- Unified EHR, billing, and diagnostic data into a single platform, ensuring consistency and accessibility.
- Designed data models tailored to SeHE and HIPAA requirements for compliance.
2. ETL Automation with Apache NiFi
- Developed ETL pipelines to automate data ingestion, transformation, and validation from various systems.
- Ensured real-time synchronization across hospitals using HL7 and FHIR standards for interoperability.
- Reduced manual data entry errors and accelerated data consolidation processes by 70%.
3. Real-Time Reporting and Dashboards
- Integrated Apache Superset as an on-premise reporting solution to provide real-time dashboards for patient metrics, financial performance, and resource allocation.
- Customized Views for Stakeholders:
- Executives: High-level KPIs, financial insights, and strategic decision-making data.
- Clinical Teams: Patient flow, treatment outcomes, and actionable insights for care delivery.
- Admin Teams: Resource utilization, staff scheduling, and operational efficiency metrics.
- Advanced Visualization: Offered interactive charts and drill-down capabilities to explore detailed data effortlessly.
- Scalable and User-Friendly: Designed to handle growing data volumes while enabling non-technical staff to independently navigate and utilize dashboards.
4. Compliance and Security
- Encryption: Implemented AES-256 encryption for data at rest and TLS 1.3 for secure data transmission.
- Role-Based Access Control (RBAC): Defined granular user roles to restrict data visibility based on responsibilities.
- Audit Trails: Configured ELK Stack to log data access and modification activities for regulatory audits.
5. Scalability Optimization
• Used table partitioning to enhance query performance for large datasets.
• Designed the architecture to scale horizontally as the hospital system added new locations.
Key Outcomes
1. Faster Insights for Decision-Making
Real-time dashboards enabled management to make data-driven decisions on staff allocation and resource planning.
2. Streamlined Compliance
The centralized system met SeHE and HIPAA requirements, reducing the risk of penalties for non-compliance.
3. Enhanced Operational Efficiency
Reports that previously took days to generate were now available instantly, saving time for administrative teams.
4. Cost Savings
Eliminated the need for third-party data consolidation tools, reducing IT costs by 25%.
5. Scalable Infrastructure
The system supported the addition of two new hospital locations with minimal adjustments.
Technology Stack
- Data Warehouse: PostgreSQL
- ETL Processes: Apache NiFi
- Microsoft Presidio for data anonymization
- Reporting Tool: Superset (on-premise)
- Integration Standards: HL7, FHIR
- Security: AES-256 encryption, TLS 1.3, ELK Stack for audit trails
- Consent Management: Integrated module for patient approvals
Implementation Timeline
1. Week 1–2: Stakeholder consultations and architecture design
2. Week 3–5: ETL development and system setup
3. Week 6–8: Data migration and testing
4. Week 9–10: Dashboard customization and user training
5. Week 11: Full deployment and post-launch support
Client Feedback: “Bioteknika’s data warehouse has completely transformed how we operate across our network of hospitals. The centralized system is intuitive and reliable, helping us meet compliance and optimize resources efficiently.” — COO, Multi-Site Hospital System
