ETL in healthcare has long been riddled with limitations. Traditional ETL processes rely on developers manually defining thousands of transformation rules such as:
if (code == “185349003”) then visit_occurrence_table
if (code == “38341003”) then condition_occurrence_table
While these rules function, they create maintenance nightmares, introduce inconsistencies, and demand constant updates. As healthcare data grows in volume and complexity, a new approach is needed—one that makes ETL healthcare pipelines intelligent and self-sustaining.
Domain-based routing is a paradigm shift in ETL healthcare systems. It transforms static, syntax-based transformations into semantic-driven workflows that leverage the built-in classification of medical terminology standards to automatically determine where each data point belongs.
Medical codes like SNOMED CT and LOINC aren’t just identifiers—they carry metadata that classifies the data into domains such as “Visit”, “Measurement”, or “Condition”. This embedded intelligence is crucial for modern ETL healthcare strategies.
🔸 Code: 185349003
🔸 Description: “Encounter for check up”
🔸 Domain: Visit
🔸 Destination: visit_occurrence table
🔸 Code: 33747-0
🔸 Description: “Glucose [Mass/volume] in Blood”
🔸 Domain: Measurement
🔸 Destination: measurement table
By utilizing domain metadata, semantic routing eliminates the need for hand-coded transformation logic, revolutionizing ETL in healthcare data management.
The OHDSI collaborative maintains Athena, a robust vocabulary service with over 6 million standardized medical concepts across:
🔸 SNOMED CT
🔸 LOINC
🔸 RxNorm
🔸 ICD-10
🔸 CPT
Each concept in Athena contains OMOP-specific metadata, including a domain_id, which allows ETL healthcare platforms to route data accurately without manual effort.
Traditional ETL healthcare systems are often limited by one-to-one mappings. Domain-based routing enables a one-to-many transformation model. For instance, a single FHIR resource for a physical exam may contain:
🔸 Visit code (SNOMED: 185349003) → visit_occurrence
🔸 Hypertension diagnosis (SNOMED: 38341003) → condition_occurrence
🔸 Blood pressure measurement (LOINC: 8480-6) → measurement
This approach allows ETL healthcare pipelines to create multiple analytical records from a single source—improving both completeness and usability.
The semantic routing engine processes data in four stages:
This architecture enables faster, more accurate, and easier-to-maintain ETL healthcare infrastructure.
Semantic routing delivers powerful advantages:
🔸 >2000 records/sec throughput
🔸 Parallel processing and vocabulary caching
🔸 Automated duplicate resolution
🔸 Consistent and accurate mappings
🔸 Full data lineage and quality controls
Unlike traditional systems, this method future-proofs your ETL healthcare pipelines against evolving vocabularies and standards.
By building transformation logic on standard vocabularies:
🔸 Mappings remain consistent across time and systems
🔸 Unmapped codes are automatically flagged
🔸 Version-independent logic supports all OMOP CDM versions
🔸 Vendor-agnostic design works with any FHIR-compliant EHR
This elevates ETL healthcare workflows from being purely operational to becoming analytical and insight-ready.
Domain-based routing isn’t just a technical improvement—it’s a strategic evolution. As healthcare organizations race to turn operational data into real-world evidence, this approach ensures that ETL in healthcare becomes automated, semantic-aware, and scalable.
Before adopting domain-based routing, evaluate:
🔸 Coverage of vocabularies for your use cases
🔸 Volume of FHIR resource processing
🔸 Quality standards for research-readiness
🔸 Integration complexity with your current ETL healthcare architecture
The domain-based routing methodology transforms the way ETL healthcare systems operate. Instead of endlessly rewriting brittle transformation logic, healthcare organizations can now adopt an intelligent, standards-driven approach that scales with minimal maintenance.
This blog is inspired by open-source contributions from the FHIR Analytics community and thought leaders like Carl Anderson, who continue to push the boundaries of semantic interoperability in healthcare.
Domain-based routing is a semantic-driven approach to data transformation that uses medical terminology metadata (like SNOMED, LOINC, RxNorm) to determine where data should be routed in a target data model such as OMOP, eliminating the need for hard-coded mapping rules.
Traditional ETL relies on manually hard-coded transformation rules, which are error-prone, difficult to maintain, and inflexible in the face of evolving medical terminologies. This leads to high maintenance costs and potential data quality issues.
Standardized codes like SNOMED and LOINC include domain metadata (e.g., “Condition”, “Measurement”) that specify their clinical context. Domain-based routing engines use this metadata to automatically determine the correct OMOP CDM table for each code.
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