A Generic Transformation Approach for Complex Laboratory Data Using the Fast Healthcare Interoperability Resources Mapping Language: Method Development and Implementation

Abstract

Background: Reaching a significant amount of interoperability between proprietary healthcare systems is an ubiquitous task in medical informatics, where communication servers are traditionally used for referring and transforming data from source to target systems. The Mirth Connect Server, which is an open-source communication server, offers in addition to the exchange functionality, also functions for the simultaneous manipulation of data. In recent times, the standard Fast Healthcare Interoperability Resources (FHIR) is becoming more and more prevalent in the German healthcare system. This standard specifies its own standardized mechanisms for transforming data structures in the form of StructureMaps and the FHIR Mapping Language.Objective: In this study, a generic approach will be developed, which allows to apply these formalized mapping rules defined by the FHIR Mapping Language in an exchangeable manner. A transformation engine is required to execute the mapping rules.Methods: FHIR natively defines resources to support conversion of instance data, the FHIR resource StructureMap. This resource encodes all information required to transform data from a source system into a target system. In our approach, this information is defined in an implementation-independent manner using the FHIR Mapping Language. Once the mapping has been defined, executable Mirth channels are automatically generated from the resources containing the mapping in form of JavaScript. These channels can be deployed to the Mirth Connect Server. Results:The resulting tool is called FML2Mirth, a Java-based transformer that derives Mirth channels from a given mapping based on the underlying StructureMaps that contain the detailed rules. The implementation of the translate functionality is guaranteed by the integration of a terminology server and to achieve conformity with existing profiles, validation via the FHIR validator is built in. The system is evaluated for its practical use by transforming LDTv.2 laboratory results into MIO lab reports according to NASHIP specifications and into to the HL7 Europe Laboratory Report. It is shown that the system can generate complex structures, but LDTv.2 lacks some information to fully comply with the specification. Conclusions:The tool for the auto-generation of Mirth channels was successfully presented. Initial tests have shown that it is feasible to use the complex structures of the mapping language in combination with a terminology server to transform instance data. Although the Mirth Server and FHIR are well established in the field of medical informatics, the combination offers space for more research, especially with regard to the FHIR Mapping Language. At the same time, it can be stated that the Mapping Language still has implementation short comings that can be compensated by Mirth Connect as a base technology. Clinical Trial: N/A