Case Study

Transforming Proprietary Medical Data to FHIR at Millions of Records a Minute

The organization got interoperable, standards-based data at production scale, unlocking every downstream system that speaks FHIR.

Industry

Healthcare & Life Sciences

Services We offer

Data Engineering

Healthcare Interoperability

Cloud & Kubernetes

APIs

About the client

A healthcare technology company standardizing data across its ecosystem.

Problem Statement

Medical data arrived in proprietary formats that no downstream system could reason about, and it arrived fast. The organization needed it converted to standard HL7 FHIR at a throughput measured in millions of records per minute.

The Challenges

Throughput without backpressure

Streaming ingestion on Kafka and Pub/Sub with GKE auto-scaling kept transformation keeping pace with millions of records a minute.

Conformance, not approximation

Output had to be genuinely FHIR-conformant so downstream systems could trust it.

Approach

We built a streaming, horizontally scalable pipeline:

A FHIR transformation engine at the core
Scalable ingestion on Apache Kafka and Google Pub/Sub
An API gateway (Apigee) and a caching layer
Auto-scaling infrastructure on Google Kubernetes Engine writing to a managed FHIR store

The Solution

Proprietary payloads stream in, are transformed to conformant FHIR, and land in a managed FHIR store, with the cluster scaling to keep pace at peak. Kotlin and Spring Boot services carry the transformation logic, with OpenEMR in the loop.

The impact we delivered

1M+/min

Records transformed to FHIR

Problem Statement

The Challenges

Throughput without backpressure

Streaming ingestion on Kafka and Pub/Sub with GKE auto-scaling kept transformation keeping pace with millions of records a minute.

Conformance, not approximation

Output had to be genuinely FHIR-conformant so downstream systems could trust it.

Approach

We built a streaming, horizontally scalable pipeline:

A FHIR transformation engine at the core
Scalable ingestion on Apache Kafka and Google Pub/Sub
An API gateway (Apigee) and a caching layer
Auto-scaling infrastructure on Google Kubernetes Engine writing to a managed FHIR store

The Solution

The impact we delivered

1M+/min

Records transformed to FHIR

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Get Detailed Case Study

Transforming Proprietary Medical Data to FHIR at Millions of Records a Minute

A streaming transformation engine that converts proprietary medical formats into standard HL7 FHIR at scale, with auto-scaling ingestion on Kubernetes and a managed FHIR store.

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