Leobit
Hospital Information System
Discovery phase and proof of concept that helped our customer validate a complete, compliant migration of historical medical data to Oracle Cloud
ABOUT the project
- Client:
- Nationwide Hospital System
- Industry:
- Healthcare
- Solution:
- Discovery Phase and PoC
Services:
Technologies:
This project focused on resolving a critical gap in a hospital system’s data infrastructure. The client had previously attempted to migrate historical patient data from MS SQL to Oracle, but the process was incomplete. As a result, large volumes of important medical records remained inaccessible.
Leobit’s role was to assess the situation, define a clear migration strategy, and validate it through a Proof of Concept. The goal was to ensure that all historical data could be reliably transferred, structured, and made searchable within the Oracle ecosystem.
The biggest challenge was not the migration itself, but understanding the client’s fragmented data landscape and turning it into a clear, executable strategy. Through the discovery phase and Proof of Concept, we were able to validate a scalable Oracle-native solution and give the client a solid foundation for future development.
Customer
The customer is a nationwide hospital network serving the entire country’s population. It operates multiple facilities, including a hospital and urgent care centers, and manages large volumes of clinical and operational data. Their systems store critical patient information such as admissions, vitals, procedures, and lab results across several disconnected databases.
Business Challenge
The core issue stemmed from an incomplete migration of historical data from MS SQL to Oracle. As a result, critical medical records, including patient vitals, procedures, and dialysis results, were either partially available or completely inaccessible.
This created serious compliance and legal risks, as the hospital could not reliably retrieve historical patient data when required. What the client needed was not just a technical migration but a clear, end-to-end approach to restore access to all historical data and ensure it remained searchable and reliable going forward.
Why Leobit
The customer chose Leobit since the project required a team that could quickly analyze an unclear data landscape, define a realistic migration scope, and move from planning to validation without delays. With experience in data migration and Oracle-based solutions, Leobit was able to structure the discovery process and design a solution aligned with the client’s existing ecosystem.
Project
in detail
Leobit conducted a detailed analysis of the customer’s database to identify issues and outline a clear migration plan.
Leobit provided a complete set of deliverables that would allow the client to continue independently. This included detailed technical documentation, migration scripts, orchestration pipelines, and a full analysis of the existing databases and their structure. All materials were prepared to support the client’s internal team in building the application layer on top of the migrated data.
Discovery phase
The project began with a discovery phase that lasted four to five weeks. During this period, the team worked closely with the client to analyze all existing databases and understand the full scope of the migration. Since the client lacked a complete picture of their data, this step was essential.
We examined six databases used across two facilities and documented the types of data stored in each of them, including patient admissions, vital signs, procedural records, and specialized datasets such as dialysis results. Based on this analysis, we defined the migration scope, outlined the architecture, and estimated the effort required for each phase of the project.
Solution design
Following the discovery phase, we designed an end-to-end migration approach based on Oracle Cloud Infrastructure and Oracle Autonomous Database. The solution was designed to align with the client’s existing Oracle ecosystem and support future scalability. The approach focused on transferring all historical data into a centralized environment while preserving its structure. It also included planning for post-migration optimization, ensuring that the data would remain fast and easy to query once migrated.
Proof of Concept
To validate the proposed solution, we implemented a Proof of Concept. Instead of migrating all systems at once, we selected one of the six databases and executed the full migration pipeline. This involved extracting data from MS SQL, transferring it to Oracle Cloud, and loading it into the Autonomous Database. The process also included orchestration of data flows and initial optimization steps to improve performance and accessibility.
The Proof of Concept confirmed that the migration approach worked in practice. The data was successfully transferred, structured, and made accessible within the new environment in less than 4 weeks. This demonstrated that a full-scale migration could be completed using the same approach. The client gained confidence in both the technical solution and the overall migration strategy.
Technology Solutions
- Choosing Oracle Cloud Infrastructure (OCI) as the target cloud environment for scalable and secure data storage.
- Using Oracle Autonomous Database as the central repository for all migrated historical data.
- Designing an orchestration framework to manage and automate data migration workflows.
- Preparing data modeling and schema design aligned with Oracle-native architecture.
- Designing indexing and partitioning strategies to optimize query performance and data retrieval.
- Performing infrastructure setup and deployment within the client’s Oracle ecosystem.
- Writing technical documentation and migration scripts to support further development by the client’s internal team.
Value Delivered
- Fully covered the discovery phase in 4 weeks.
- Restored a clear path to accessing critical historical patient data required for compliance and legal needs.
- Validated a complete, Oracle-native migration approach through a working Proof of Concept.
- Reduced project risk by testing the full migration pipeline before full-scale implementation.
- Provided full visibility into the client’s data landscape, which was previously unclear and fragmented.
- Delivered a scalable architecture aligned with the client’s existing Oracle ecosystem.
