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A Generic Transformation Approach for Complex Laboratory Data Using the Fast Healthcare Interoperability Resources

Jesse Kruse1, Joshua Wiedekopf2,3, Ann-Kristin Kock-Schoppenhauer2

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Summary
This summary is machine-generated.

This study introduces FML2Mirth, a tool that automates Mirth channel generation for healthcare data transformation using FHIR mapping language. It enables efficient interoperability between proprietary systems, enhancing medical informatics workflows.

Keywords:
FHIRFHIR mapping languageHISStructureMapsdata scienceelectronic health recordelectronic healthcare recordhealth care systemhealth information systemhealthcare systeminformation systemlaboratory datamappingstandardization

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Area of Science:

  • Medical Informatics
  • Health Data Interoperability
  • Healthcare System Integration

Background:

  • Achieving interoperability between proprietary healthcare systems is a significant challenge in medical informatics.
  • Communication servers are traditionally used for data exchange and transformation.
  • Fast Healthcare Interoperability Resources (FHIR) and its mapping language (FML) are increasingly prevalent standards for healthcare data transformation.

Purpose of the Study:

  • To develop a generic approach for applying declarative mapping rules defined using FML in an exchangeable manner.
  • To create a transformation engine capable of executing FML mapping rules.
  • To automate the generation of Mirth channels for data transformation.

Main Methods:

  • FHIR StructureMap resources were used to define mapping rules in an implementation-independent manner using FML.
  • A Java-based transformer, FML2Mirth, was developed to automatically generate Mirth channels from these FHIR StructureMap resources.
  • The system integrated a terminology server for translation functionality and FHIR validator for conformity checks.

Main Results:

  • The FML2Mirth tool successfully generated Mirth channels from declarative mapping rules.
  • The system demonstrated the feasibility of transforming instance data using FML and a terminology server.
  • Evaluation showed the system could generate complex structures, though some data limitations were noted.

Conclusions:

  • The auto-generation of Mirth channels using FML2Mirth was successfully demonstrated.
  • The combination of Mirth Connect and FHIR offers potential for further research in healthcare data transformation.
  • Implementation-specific shortcomings of FML can be addressed by leveraging Mirth Connect's capabilities.