Dr. rer. hum. biol. Ann-Kristin Kock-Schoppenhauer

Introduction: As part of the German Medical Informatics Initiative (MII) and Network University Medicine (NUM), a central research terminology service (TS) is provided by the Service Unit Terminology Services (SU-TermServ). This HL7 FHIR-based service depends on the timely and comprehensive availability of FHIR terminology resources to provide the necessary interactions for the distributed MII/NUM infrastructure. While German legislation has recently instituted a national terminology service for medical classifications and terminologies, the scope of the MII and NUM extends beyond routine patient care, encompassing the need for supplementary or specialized services and terminologies that are not commonly utilized elsewhere.

Methods: The SU-TermServ’s processes are based on established FHIR principles and the recently-proposed Canonical Resources Management Infrastructure Implementation Guide, which are outlined in this paper.

Results: The strategy and processes implemented within the project can deliver the needed resources both to the central FHIR terminology service, but also to the local data integration centers, in a transparent and consistent fashion. The service currently provides approximately 7000 resources to users via the standardized FHIR API.

Conclusion: The professionalized distribution and maintenance of these terminological resources and the provision of a powerful TS implementation aids both the development of the Core Data Set and the data integration centers, and ultimately biomedical researchers requesting access to this rich data.

To provide clinical data in distributed research architectures, a fundamental challenge involves defining and distributing suitable metadata within Metadata Repositories. Especially for structured data, data elements need to be bound against suitable terminologies; otherwise, other systems will only be able to interpret the data with complex and error-prone manual involvement. As current Metadata Repository implementations lack support for querying externally defined terminologies in FHIR terminology servers, we propose an intermediate solution that uses appropriate annotations on metadata elements to allow run-time Terminology Services mediated queries of that metadata. This allows a very clear separation of concerns between the two related systems, greatly simplifying terminological maintenance. The system performed well in a prototypical deployment.

The large variability of data models, specifications, and interpretations of data elements is particular to the healthcare domain. Achieving semantic interoperability is the first step to enable reuse of healthcare data. To ensure interoperability, metadata repositories (MDR) are increasingly used to manage data elements on a structural level, while terminology servers (TS) manage the ontologies, terminologies, coding systems and value sets on a semantic level. In practice, however, this strict separation is not always followed; instead, semantical information is stored and maintained directly in the MDR, as a link between both systems is missing. This may be reasonable up to a certain level of complexity, but it quickly reaches its limitations with increasing complexity. The goal of this approach is to combine both components in a compatible manner. We present TermiCron, a synchronization engine that provides synchronized value sets from TS in MDRs, including versioning and annotations. Prototypical results were shown for the terminology server Ontoserver and two established MDR systems. Bridging the semantic and structural gap between the two infrastructure components, this approach enables shared use of metadata and reuse of corresponding health information by establishing a clear separation of the two systems and thus serves to strengthen reuse as well as to increase quality.

While HL7 FHIR and its terminology package have seen a rapid uptake by the research community, in no small part due to the wide availability of tooling and resources, there are some areas where tool availability is still lacking. In particular, the comparison of terminological resources, which supports the work of terminologists and implementers alike, has not yet been sufficiently addressed. Hence, we present TerminoDiff, an application to semantically compare FHIR R4 CodeSystem resources. Our tool considers differences across all levels required, i.e. metadata and concept differences, as well as differences in the edge graph, and surfaces them in a visually digestible fashion.

Data integration and exchange are becoming more crucial with the increasing amount of distributed systems and ever-growing amounts of data. This need is also widely known in medical research and not yet comprehensively solved. Practical implementation steps will demonstrate the different challenges in the context of the National Medical Informatics Initiative in Germany. Top-down versus bottom-up approaches as general methods of standard-based data integration in healthcare will be discussed and illustrated in the process of building up Medical Data Integration Centers. As practical examples, the use cases Infection Control, Cardiology, and Molecular Tumor Board, will be presented. Finally, limitations that prevent the use of theoretically recommended data integration methods in the particular field of medical informatics are illustrated.

To ensure semantic interoperability within healthcare systems, using common, curated terminological systems to identify relevant concepts is of fundamental importance. The HL7 FHIR standard specifies means of modelling terminological systems and appropriate ways of accessing and querying these artefacts within a terminology server. Hence, initiatives towards healthcare interoperability like IHE specify not only software interfaces, but also common codes in the form of value sets and code systems. The way in which these coding tables are provided is not necessarily compatible to the current version of the HL7 FHIR specification and therefore cannot be used with current HL7 FHIR-based terminology servers. This work demonstrates a conversion of terminological resources specified by the Integrating the Healthcare Initiative in the ART-DECOR platform, partly available in HL7 FHIR, to ensure that they can be used within a HL7 FHIR-based terminological server. The approach itself can be used for other terminological resources specified within ART-DECOR but can also be used as the basis for other code-driven conversions of proprietary coding schemes.

The current movement in Medical Informatics towards comprehensive Electronic Health Records (EHRs) has enabled a wide range of secondary use cases for this data. However, due to a number of well-justified concerns and barriers, especially with regards to information privacy, access to real medical records by researchers is often not possible, and indeed not always required. An appealing alternative to the use of real patient data is the employment of a generator for realistic, yet synthetic, EHRs. However, we have identified a number of shortcomings in prior works, especially with regards to the adaptability of the projects to the requirements of the German healthcare system. Based on three case studies, we define a non-exhaustive list of requirements for an ideal generator project that can be used in a wide range of localities and settings, to address and enable future work in this regard.