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Version: 3.1.3

Validator

Implementation Guide Validation​

The Validation feature of the Centaur® Data Platform plays a crucial role in ensuring the accuracy and conformance of FHIR® resources to predefined specifications, including HL7™ FHIR® Implementation Guides (IG). This process verifies that all incoming and curated data complies with healthcare interoperability standards, ensuring the data is fit for downstream use cases such as APIs, analytics, and clinical decision support.

Core Functions:​

  • FHIR® Resource Validation: The validation engine checks all FHIR® resources processed by the platform against the HL7™ FHIR® Implementation Guide (IG) specifications. This ensures that resources meet required standards for structure, cardinality, value domains, and code bindings.
  • IG Compliance: The validation component evaluates whether the incoming resources conform to FHIR® IG rules, providing additional assurances that the data is compliant with industry standards.
  • Error Detection: Any data that does not meet validation criteria is flagged, and the relevant errors are logged. These validation errors help users quickly identify and resolve issues in data quality or formatting.
How It Works:
  • Pre-Ingestion Validation: As data enters the Centaur® platform, it is first validated to ensure that it adheres to the required formats and specifications.
  • FHIR® Resource Structure Validation: The validation engine checks each FHIR® resource (e.g., Patient, Observation, Practitioner) to ensure that it contains all mandatory elements and follows the correct structure.
  • Validation Logging: Any errors detected during validation are logged with specific error codes, allowing users to easily identify and troubleshoot issues.

Benefits of the Validation Component:​

  • Data Quality Assurance: Ensures that all ingested data meets the necessary quality standards before further processing or ingestion into FHIR® servers.
  • Compliance: Helps healthcare organizations stay compliant with FHIR® R4 and USCDI standards, ensuring that their data is structured correctly for interoperability.
  • Error Resolution: Detailed logging and error codes make it easier to troubleshoot and correct issues, minimizing the risk of bad data entering downstream systems.

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