HIS Integration Consulting
Healthcare organizations operate multiple clinical and administrative systems that were not designed to work together. Making them interoperate — reliably, in real time, without data loss — is one of the hardest problems in health IT. We design and implement integrations that hold up in production.
Why HIS integrations fail
Most integration problems are not caused by bad technology choices. They are caused by the absence of a clear integration design before implementation starts.
Point-to-point connections that multiply
When each new system gets connected directly to every other system, the number of integration paths grows faster than the team can maintain them. A change to one system breaks connections in unpredictable ways.
Data that gets out of sync
Patient data spread across multiple systems becomes inconsistent over time. Duplicated records, conflicting values, and incomplete information are symptoms of integration that was designed for the happy path and not for the real world.
No standards, no documentation
Integrations built without a standards-based architecture are hard to debug, impossible to hand over, and require the original developer to maintain them. When that person leaves, the integration becomes a liability.
How we help
We cover both dimensions of HIS integration: service integration, where systems exchange information in real time to support clinical processes, and data integration, where the goal is to consolidate, synchronize, or analyze data across systems.
Service Integration
We design and implement integrations that allow two or more systems to exchange information in real time during clinical workflows — a patient admission, a medication prescription, an order to a lab or imaging system. We work with HL7 v2, FHIR R4, REST APIs, and messaging platforms, and design the interface contracts that make each connection maintainable and replaceable.
Data Centralization
When an organization has data spread across multiple disconnected systems, we design a centralization strategy: identify the authoritative source for each data element, define the target model, design the transformation and loading processes, and implement them. The result is a single source of truth that other systems can query without touching each upstream system directly.
Data Synchronization
When multiple databases need to remain consistent without consolidating into one, we design synchronization processes: detect what changed, in which system, determine the direction and rules for propagating the change, and execute updates without creating conflicts or data loss. We document sync behavior so the team can operate and extend it independently.
ETL for Analytics
When the business needs consolidated data for indicators, reporting, or a data warehouse, we design the extraction, transformation, and loading pipeline. This includes identifying the right data sources, mapping to a common model, ensuring data quality (completeness, uniqueness, consistency), and loading to the destination. We account for ongoing updates, not just the initial load.
Integration Architecture Design
Before any integration is built, we design the overall integration architecture: which pattern to use (point-to-point, hub-and-spoke, message bus), how data flows between systems, where transformations happen, and how failures are handled. A well-designed integration architecture means each new connection follows a predictable pattern instead of becoming its own project.
Integration Testing and QA
We design and execute test plans that verify integrations behave correctly under real conditions — including edge cases, error paths, and concurrent updates. We use protocol-level analysis tools to inspect what systems are actually sending and receiving, not just what they claim to send and receive.
Do you have any questions?
Let us know how we can help you.