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A Data Transformation Methodology to Create Findable, Accessible, Interoperable, and Reusable Health Data: Software

A Anil Sinaci1, Mert Gencturk1,2, Huseyin Alper Teoman1,2

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This study introduces a new method and tool for transforming health data into HL7 FHIR, enhancing data sharing. The approach successfully makes data Findable, Accessible, and Interoperable, aligning with FAIR principles.

Keywords:
FAIR principlesFindable, Accessible, Interoperable, and Reusable principlesHL7 FHIRHealth Level 7 Fast Healthcare Interoperability Resourceshealth data sharinghealth data transformationsecondary use

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Area of Science:

  • Health Informatics
  • Data Science
  • Biomedical Data Standards

Background:

  • Sharing health data faces significant technical, ethical, and regulatory hurdles.
  • The Findable, Accessible, Interoperable, and Reusable (FAIR) principles aim to improve data interoperability.
  • Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) is a key standard for health data exchange.

Purpose of the Study:

  • To develop a methodology and tool for extracting, transforming, and loading health data into HL7 FHIR repositories.
  • To ensure transformed data adheres to FAIR principles, increasing compliance and facilitating data sharing.
  • To address technical barriers hindering the sharing of existing health datasets.

Main Methods:

  • Developed an automated approach that processes FHIR endpoint capabilities for user-guided mapping configuration.
  • Implemented code system mappings for terminology translation using FHIR resources.
  • Integrated automatic validation checks for FHIR resource creation to ensure data integrity.

Main Results:

  • Achieved maximum FAIR Data Maturity Model levels (5/5) for Findable, Accessible, and Interoperable criteria.
  • Reached level 3/5 for Reusability, demonstrating significant FAIR compliance.
  • Successfully transformed health datasets into HL7 FHIR without data utility loss, validated across two institutions.

Conclusions:

  • The developed data transformation approach unlocks the value of siloed health data for FAIR sharing.
  • The method ensures transformed HL7 FHIR data meets FAIR principles, facilitating integration with research networks.
  • Supports institutional migration to HL7 FHIR, promoting standardized and efficient health data exchange.