HL7 ADT Ingestion Platform
Real-time Hospital Alert Observability
Architected and managed high-performance clinical data pipelines processing real-time HL7 feeds for multiple HIE networks, enabling immediate admission tracking and care coordination.
Business Problem
Real-time patient admission tracking was fragmented across diverse vendors, making care coordination for high-risk populations slow and reactive.
Technical Challenges
Handling high-concurrency TCP/IP HL7 streams from multiple HIE sources with zero message loss and implementing real-time observability for silent failures.
Architecture
An event-driven architecture combining Python-based TCP listeners and a NestJS-powered observability layer, persisting data into a normalized SQL Server schema.
Implementation
Standardized ingestion for an extensive variety of data formats from major vendors like Experian, PointClickCare, and Bamboo Health. Implemented a robust file lifecycle management system.
Scalability
Processes high volumes of clinical events daily with sub-second latency across distributed environments.
Results / Impact
Enabled real-time ER alerts for broad patient populations and established a high-fidelity longitudinal view for population health analytics.
Lessons Learned
In real-time healthcare data, observability is as critical as ingestion. Systems must be designed to alert proactively on feed silence.
Interested in the technical implementation?
Let's discuss how this architecture can be applied to your specific healthcare challenges.