Key results
Reduced reporting latency from over 3 hours to under 30 minutes.
Centralized data from more than 10 source systems into a cloud-native platform.
Enabled live operational insights across all sites.
Established the foundation for future staffing and resource optimization.
About the Client
A US based growing healthcare group operating outpatient clinics, urgent care centers, and diagnostic labs. The organization needed a unified analytics and reporting system to consolidate data from billing, scheduling, and patient engagement systems.
Key Challenges
Regional data silos across EHR, billing, and scheduling tools
Inconsistent formats and manual report creation delayed decision-making
No centralized visibility into patient volumes, provider utilization, or revenue metrics
Our Approach
- Designed a HIPAA-compliant cloud data platform on Microsoft Azure
- Used Azure Data Factory for scalable pipeline orchestration across multiple systems
- Leveraged Python for custom transformation logic and clinical data normalization
Implemented Solution
Cloud Infrastructure Setup
- Deployed Azure Synapse Analytics as the central cloud data warehouse
- Configured secure access, encryption, and compliance-ready infrastructure
- Built cost-efficient, scalable storage and compute tiers
Data Integration & Automation
- Used Azure Data Factory to ingest data from EHRs (Epic, Athenahealth), billing, and scheduling systems
- Developed Python scripts for standardizing patient records, service types, and financial mappings
- Enabled automated pipelines with data quality checks, error logging, and recovery
Reporting & Access Layer
- Organized data by subject areas: visits, billing, scheduling, provider utilization
- Created Power BI dashboards for clinical ops, revenue cycle, and executive teams
- Provided self-serve access and user-level data permissions
Technologies Used




