Background: To ensure interoperability, both structural and semantic standards must be followed. For exchanging medical data between information systems, the structural standard FHIR (Fast Healthcare Interoperability Resources) has recently gained popularity. Regarding semantic interoperability, the reference terminology SNOMED Clinical Terms (SNOMED CT), as a semantic standard, allows for postcoordination, offering advantages over many other vocabularies. These postcoordinated expressions (PCEs) make SNOMED CT an expressive and flexible interlingua, allowing for precise coding of medical facts. However, this comes at the cost of increased complexity, as well as challenges in storage and processing. Additionally, the boundary between semantic (terminology) and structural (information model) standards becomes blurred, leading to what is known as the TermInfo problem. Although often viewed critically, the TermInfo overlap can also be explored for its potential benefits, such as enabling flexible transformation of parts of PCEs. Objective: In this paper, an alternative solution for storing PCEs is presented, which involves combining them with the FHIR data model. Ultimately, all components of a PCE should be expressible solely through precoordinated concepts that are linked to the appropriate elements of the information model. Methods: The approach involves storing PCEs decomposed into their components in alignment with FHIR resources. By utilizing the Web Ontology Language (OWL) to generate an OWL ClassExpression, and combining it with an external reasoner and semantic similarity measures, a precoordinated SNOMED CT concept that most accurately describes the PCE is identified as a Superconcept. In addition, the nonmatching attribute relationships between the Superconcept and the PCE are identified as the “Delta.” Once SNOMED CT attributes are manually mapped to FHIR elements, FHIRPath expressions can be defined for both the Superconcept and the Delta, allowing the identified precoordinated codes to be stored within FHIR resources. Results: A web application called PCEtoFHIR was developed to implement this approach. In a validation process with 600 randomly selected precoordinated concepts, the formal correctness of the generated OWL ClassExpressions was verified. Additionally, 33 PCEs were used for two separate validation tests. Based on these validations, it was demonstrated that a previously proposed semantic similarity calculation is suitable for determining the Superconcept. Additionally, the 33 PCEs were used to confirm the correct functioning of the entire approach. Furthermore, the FHIR StructureMaps were reviewed and deemed meaningful by FHIR experts. Conclusions: PCEtoFHIR offers services to decompose PCEs for storage within FHIR resources. When creating structure mappings for specific subdomains of SNOMED CT concepts (eg, allergies) to desired FHIR profiles, the use of SNOMED CT Expression Templates has proven highly effective. Domain experts can create templates with appropriate mappings, which can then be easily reused in a constrained manner by end users.
@article{Ohlsen2024Decompositionpostcoordinated,author={Ohlsen, Tessa and Drenkhahn, Cora and Ingenerf, Josef},title={{PCEtoFHIR: Decomposition of Postcoordinated SNOMED CT Expressions for Storage as HL7 FHIR Resources}},year={2024},month=sep,day={17},volume={12},pages={e57853},issn={2291-9694},doi={10.2196/57853},publisher={JMIR Publications Inc.},language={en},journal={JMIR Med Inform},abbr={JMIR}}
📖
Referenzterminologie SNOMED CT
Interlingua zur Gewährleistung semantischer Interoperabilität in der Medizin
SNOMED CT wird zunehmend auch in Deutschland als wesentlicher Baustein innovativer digitaler Gesundheitsanwendungen verwendet. Sie gilt mit über 350.000 formal definierten Konzepten sowie mehrsprachigen Bezeichnungen als ausdrucksmächtigste internationale Referenzterminologie. Gleichwohl stellt die Einführung von SNOMED CT mit dem Potenzial zur Postkoordination „neuer Konzepte“ einen Paradigmenwechsel dar. Dieser geht einher mit vielfältigsten methodischen Grundlagen, die interessierten Anwendern und Software-Entwicklern vermittelt werden müssen, um den erwarteten Nutzen realisieren zu können. Dieses Buch soll hierzu einen Beitrag leisten.
@book{ingenerf_drenkhahn_referenzterminologie_2023,author={Ingenerf, Josef and Drenkhahn, Cora},title={Referenzterminologie SNOMED CT},subtitle={Interlingua zur Gewährleistung semantischer Interoperabilität in der Medizin},publisher={Springer Vieweg},year={2023},doi={10.1007/978-3-658-35562-3},isbn={978-3-658-35562-3},language={de}}
2024
The FHIR Terminology Module and its Implications for the Use of Coded Data in Modern Data Integration
Gesundheit – gemeinsam. Kooperationstagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS), Deutschen Gesellschaft für Sozialmedizin und Prävention (DGSMP), Deutschen Gesellschaft für Epidemiologie (DGEpi), Deutschen Gesellschaft für Medizinische Soziologie (DGMS) und der Deutschen Gesellschaft für Public Health (DGPH) Sep 2024
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.
@article{Wiedekopf2024TerminologyModule,title={{The FHIR Terminology Module and its Implications for the Use of Coded Data in Modern Data Integration}},author={Wiedekopf, Joshua and Ingenerf, Josef},journal={{Gesundheit – gemeinsam. Kooperationstagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS), Deutschen Gesellschaft für Sozialmedizin und Prävention (DGSMP), Deutschen Gesellschaft für Epidemiologie (DGEpi), Deutschen Gesellschaft für Medizinische Soziologie (DGMS) und der Deutschen Gesellschaft für Public Health (DGPH)}},conference={GMDS 2024},year={2024},month=sep,language={en},doi={10.3205/24gmds008}}
JMIR
PCEtoFHIR: Decomposition of Postcoordinated SNOMED CT Expressions for Storage as HL7 FHIR Resources
Background: To ensure interoperability, both structural and semantic standards must be followed. For exchanging medical data between information systems, the structural standard FHIR (Fast Healthcare Interoperability Resources) has recently gained popularity. Regarding semantic interoperability, the reference terminology SNOMED Clinical Terms (SNOMED CT), as a semantic standard, allows for postcoordination, offering advantages over many other vocabularies. These postcoordinated expressions (PCEs) make SNOMED CT an expressive and flexible interlingua, allowing for precise coding of medical facts. However, this comes at the cost of increased complexity, as well as challenges in storage and processing. Additionally, the boundary between semantic (terminology) and structural (information model) standards becomes blurred, leading to what is known as the TermInfo problem. Although often viewed critically, the TermInfo overlap can also be explored for its potential benefits, such as enabling flexible transformation of parts of PCEs. Objective: In this paper, an alternative solution for storing PCEs is presented, which involves combining them with the FHIR data model. Ultimately, all components of a PCE should be expressible solely through precoordinated concepts that are linked to the appropriate elements of the information model. Methods: The approach involves storing PCEs decomposed into their components in alignment with FHIR resources. By utilizing the Web Ontology Language (OWL) to generate an OWL ClassExpression, and combining it with an external reasoner and semantic similarity measures, a precoordinated SNOMED CT concept that most accurately describes the PCE is identified as a Superconcept. In addition, the nonmatching attribute relationships between the Superconcept and the PCE are identified as the “Delta.” Once SNOMED CT attributes are manually mapped to FHIR elements, FHIRPath expressions can be defined for both the Superconcept and the Delta, allowing the identified precoordinated codes to be stored within FHIR resources. Results: A web application called PCEtoFHIR was developed to implement this approach. In a validation process with 600 randomly selected precoordinated concepts, the formal correctness of the generated OWL ClassExpressions was verified. Additionally, 33 PCEs were used for two separate validation tests. Based on these validations, it was demonstrated that a previously proposed semantic similarity calculation is suitable for determining the Superconcept. Additionally, the 33 PCEs were used to confirm the correct functioning of the entire approach. Furthermore, the FHIR StructureMaps were reviewed and deemed meaningful by FHIR experts. Conclusions: PCEtoFHIR offers services to decompose PCEs for storage within FHIR resources. When creating structure mappings for specific subdomains of SNOMED CT concepts (eg, allergies) to desired FHIR profiles, the use of SNOMED CT Expression Templates has proven highly effective. Domain experts can create templates with appropriate mappings, which can then be easily reused in a constrained manner by end users.
@article{Ohlsen2024Decompositionpostcoordinated,author={Ohlsen, Tessa and Drenkhahn, Cora and Ingenerf, Josef},title={{PCEtoFHIR: Decomposition of Postcoordinated SNOMED CT Expressions for Storage as HL7 FHIR Resources}},year={2024},month=sep,day={17},volume={12},pages={e57853},issn={2291-9694},doi={10.2196/57853},publisher={JMIR Publications Inc.},language={en},journal={JMIR Med Inform},abbr={JMIR}}
SHTI
Reformatted Crosswalk-Tables Between Annual ICD-10-Versions for Cross Version Data Analysis
The International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) is internationally used for coding diagnoses, with the ICD-10 German Modification (GM) being prescribed for morbidity coding in Germany. ICD-10-GM is subject to annual revisions. This can lead to backward compatibility issues leading to undesirable consequences for cross-version data analysis. A study of annual crosswalk-tables concerning 21 ICD-10-GM versions showed that the ratio of difficult transitions from an older to a newer version (0.89 %) and vice versa (0.48 %) is not particularly significant but should nevertheless not be neglected. In this paper we present two solutions (Neo4J database and FHIR ConceptMaps) for the automated handling of different ICD-10-GM versions.
@article{Ohlsen2024CrosswalkTables,doi={10.3233/SHTI240652},url={https://doi.org/10.3233/SHTI240652},year={2024},month=aug,publisher={{IOS} Press},author={Ohlsen, Tessa and Wiedekopf, Joshua and Ingenerf, Josef},title={Reformatted Crosswalk-Tables Between Annual ICD-10-Versions for Cross Version Data Analysis},journal={Studies in Health Technology and Informatics},conference={Medical Informatics Europe 2024},language={en},abbr={SHTI}}
JMIR
Uncovering Harmonization Potential in Health Care Data Through Iterative Refinement of Fast Healthcare Interoperability Resources Profiles Based on Retrospective Discrepancy Analysis: Case Study
Background: Cross-institutional interoperability between health care providers remains a recurring challenge worldwide. The German Medical Informatics Initiative, a collaboration of 37 university hospitals in Germany, aims to enable interoperability between partner sites by defining Fast Healthcare Interoperability Resources (FHIR) profiles for the cross-institutional exchange of health care data, the Core Data Set (CDS). The current CDS and its extension modules define elements representing patients’ health care records. All university hospitals in Germany have made significant progress in providing routine data in a standardized format based on the CDS. In addition, the central research platform for health, the German Portal for Medical Research Data feasibility tool, allows medical researchers to query the available CDS data items across many participating hospitals. Objective: In this study, we aimed to evaluate a novel approach of combining the current top-down generated FHIR profiles with the bottom-up generated knowledge gained by the analysis of respective instance data. This allowed us to derive options for iteratively refining FHIR profiles using the information obtained from a discrepancy analysis. Methods: We developed an FHIR validation pipeline and opted to derive more restrictive profiles from the original CDS profiles. This decision was driven by the need to align more closely with the specific assumptions and requirements of the central feasibility platform’s search ontology. While the original CDS profiles offer a generic framework adaptable for a broad spectrum of medical informatics use cases, they lack the specificity to model the nuanced criteria essential for medical researchers. A key example of this is the necessity to represent specific laboratory codings and values interdependencies accurately. The validation results allow us to identify discrepancies between the instance data at the clinical sites and the profiles specified by the feasibility platform and addressed in the future. Results: A total of 20 university hospitals participated in this study. Historical factors, lack of harmonization, a wide range of source systems, and case sensitivity of coding are some of the causes for the discrepancies identified. While in our case study, Conditions, Procedures, and Medications have a high degree of uniformity in the coding of instance data due to legislative requirements for billing in Germany, we found that laboratory values pose a significant data harmonization challenge due to their interdependency between coding and value. Conclusions: While the CDS achieves interoperability, different challenges for federated data access arise, requiring more specificity in the profiles to make assumptions on the instance data. We further argue that further harmonization of the instance data can significantly lower required retrospective harmonization efforts. We recognize that discrepancies cannot be resolved solely at the clinical site; therefore, our findings have a wide range of implications and will require action on multiple levels and by various stakeholders.
@article{Rosenau2024UncoveringHarmonizationPotential,author={Rosenau, Lorenz and Behrend, Paul and Wiedekopf, Joshua and Gruendner, Julian and Ingenerf, Josef},title={{Uncovering Harmonization Potential in Health Care Data Through Iterative Refinement of Fast Healthcare Interoperability Resources Profiles Based on Retrospective Discrepancy Analysis: Case Study}},journal={JMIR Med Inform},year={2024},month=jul,day={23},volume={12},pages={e57005},issn={2291-9694},doi={10.2196/57005},publisher={JMIR Publications Inc.},language={en},abbr={JMIR}}
📖
Integration von Wearables und Nutzung von digitalen Biomarkern zur Diagnostik und Therapie im Gesundheitswesen
@incollection{ciortuz_2024_integration_biomarkers,location={Wiesbaden},title={Integration von Wearables und Nutzung von digitalen Biomarkern zur Diagnostik und Therapie im Gesundheitswesen},isbn={978-3-658-43235-5 978-3-658-43236-2},url={https://link.springer.com/10.1007/978-3-658-43236-2_31},pages={323--336},booktitle={Health Data Management},publisher={Springer Fachmedien Wiesbaden},author={Ciortuz, Gabriela and Wiedekopf, Joshua and Fudickar, Sebastian},editor={Henke, Viola and Hülsken, Gregor and Schneider, Henning and Varghese, Julian},urldate={2024-03-26},date={2024-03},language={de},doi={10.1007/978-3-658-43236-2_31}}
2023
SHTI
Mettertron ⎼ Bridging Metadata Repositories and Terminology Servers
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.
@article{schladetzky_wiedekopf_mettertron_2023,title={{Mettertron ⎼ Bridging Metadata Repositories and Terminology Servers}},author={Schladetzky, Jan and Kock-Schoppenhauer, Ann-Kristin and Drenkhahn, Cora and Ingenerf, Josef and Wiedekopf, Joshua},journal={Studies in Health Informatics and Technology},conference={GMDS 2023},inpress={1},year={2023},month=sep,abbr={SHTI},language={en},doi={10.3233/SHTI230721}}
Appl Sci
WASP—A Web Application to Support Syntactically and Semantically Correct SNOMED CT Postcoordination
Expressive clinical terminologies are of utmost importance for achieving a semantically interoperable data exchange and reuse in healthcare. SNOMED CT, widely respected as the most comprehensive terminology in medicine, provides formal concept definitions based on description logic which not only allows for advanced querying of SNOMED-CT-coded data but also for flexibly augmenting its 350,000 concepts by allowing a controlled combination of these. This ability for postcoordination largely increases the expressivity of the terminology but correlates with an intrinsic complexity. Complicated by the current lack of tooling support, postcoordination is widely either ignored or applied in an error-prone way. To help facilitate the adoption of postcoordination, we implemented a web application that guides users through the creation of postcoordinated expressions (PCEs) while ensuring adherence to syntactic and semantic constraints. Our approach was largely facilitated by making use of the extensive SNOMED CT specifications as well as advanced HL7 FHIR Terminology Services. Qualitative evaluations confirmed the usability of the developed application and the correctness of the PCEs created with it.
@article{drenkhahn_wasp_2023,title={{WASP—A Web Application to Support Syntactically and Semantically Correct SNOMED CT Postcoordination}},author={Drenkhahn, Cora and Ohlsen, Tessa and Wiedekopf, Joshua and Ingenerf, Josef},volume={13},issn={2076-3417},doi={https://doi.org/10.3390/app13106114},number={10},journal={Applied Sciences},publisher={MDPI AG},year={2023},month=may,pages={6114},language={en},tool={wasp},abbr={Appl Sci}}
SHTI
Performance Benchmarking of FHIR Terminology Operations in ETL Jobs
Interoperability in healthcare cannot be achieved without mapping local data to standardized terminology. In this paper, we investigate the performance of different approaches for implementing HL7 FHIR Terminology Module operations using a benchmarking methodology, to gather evidence on the benefits and pitfalls of these methods in terms of performance from the point-of-view of a terminology client. The approaches perform very differently, while having a local client-side cache for all operations is of supreme importance. The results of our investigation show that careful consideration of the integration environment, potential bottlenecks, and implementation strategies is required.
@article{wiedekopf_benchmarking_2023,doi={10.3233/shti230244},url={https://doi.org/10.3233/shti230244},year={2023},month=may,publisher={{IOS} Press},author={Wiedekopf, Joshua and Drenkhahn, Cora and Ingenerf, Josef},title={Performance Benchmarking of {FHIR} Terminology Operations in {ETL} Jobs},journal={Studies in Health Technology and Informatics},conference={Medical Informatics Europe 2023},language={en},slides={mie2023/benchmarking_mie2023_v2_1_0.pdf},abbr={SHTI}}
SHTI
Breaking Barriers for Interoperability: A Reference Implementation of CSV-FHIR Transformation Using Open-Source Tools
FHIR is a widely accepted interoperability standard for exchanging medical data, but data transformation from the primary health information systems into FHIR is usually challenging and requires advanced technical skills and infrastructure. There is a critical need for low-cost solutions, and using Mirth Connect as an open-source tool provides this opportunity. We developed a reference implementation to transform data from CSV (the most common data format) into FHIR resources using Mirth Connect without any advanced technical resources or programming skills. This reference implementation is tested successfully for both quality and performance, and it enables reproducing and improving the implemented approach by healthcare providers to transform raw data into FHIR resources. For ensuring replicability, the used channel, mapping, and templates are available publicly on GitHub (https://github.com/alkarkoukly/CSV-FHIR-Transformer).
@article{alkarkoukly_csv-fhir_2023,doi={10.3233/shti230061},url={https://doi.org/10.3233/shti230061},year={2023},month=may,publisher={{IOS} Press},author={Alkarkoukly, Samer and Kamal, Md. Mostafa and Beyan, Oya},title={Breaking Barriers for Interoperability: A Reference Implementation of {CSV}-{FHIR} Transformation Using Open-Source Tools},journal={Studies in Health Technology and Informatics},conference={Medical Informatics Europe 2023},language={en},slides={mie2023/Breaking_Barriers_for_Interoperability_2023_05_24.pdf},abbr={SHTI}}
Die neue zentrale Service Unit Terminological Services (SU-TermServ) der MII
@article{sutermserv2023miracumjournal,author={Ingenerf, Josef and Wiedekopf, Joshua and Beyer, Andreas and Adnan, Muhammad and Marschollek, Michael and Haarbrandt, Birger},journal={MIRACUM DIFUTURE Journal},title={Die neue zentrale Service Unit Terminological Services (SU-TermServ) der MII},year={2023},month=apr,language={de},pdf={20230505-MIRACUM_Journal-SU-TermServ.pdf},url={https://www.miracum.org/2023/04/24/erstes-miracum-difuture-journal-veroeffentlicht}}
JAMIA
MIMIC-IV on FHIR: converting a decade of in-patient data into an exchangeable, interoperable format
Alex M Bennett, Hannes Ulrich, Philip Damme, Joshua Wiedekopf, und Alistair E W Johnson
Journal of the American Medical Informatics Association Jan 2023
Convert the Medical Information Mart for Intensive Care (MIMIC)-IV database into Health Level 7 Fast Healthcare Interoperability Resources (FHIR). Additionally, generate and publish an openly available demo of the resources, and create a FHIR Implementation Guide to support and clarify the usage of MIMIC-IV on FHIR.FHIR profiles and terminology system of MIMIC-IV were modeled from the base FHIR R4 resources. Data and terminology were reorganized from the relational structure into FHIR according to the profiles. Resources generated were validated for conformance with the FHIR profiles. Finally, FHIR resources were published as newline delimited JSON files and the profiles were packaged into an implementation guide.The modeling of MIMIC-IV in FHIR resulted in 25 profiles, 2 extensions, 35 ValueSets, and 34 CodeSystems. An implementation guide encompassing the FHIR modeling can be accessed at mimic.mit.edu/fhir/mimic. The generated demo dataset contained 100 patients and over 915 000 resources. The full dataset contained 315 000 patients covering approximately 5 840 000 resources. The final datasets in NDJSON format are accessible on PhysioNet.Our work highlights the challenges and benefits of generating a real-world FHIR store. The challenges arise from terminology mapping and profiling modeling decisions. The benefits come from the extensively validated openly accessible data created as a result of the modeling work.The newly created MIMIC-IV on FHIR provides one of the first accessible deidentified critical care FHIR datasets. The extensive real-world data found in MIMIC-IV on FHIR will be invaluable for research and the development of healthcare applications.
@article{bennet_mimic_2023,doi={10.1093/jamia/ocad002},url={https://doi.org/10.1093/jamia/ocad002},year={2023},month=jan,publisher={Oxford University Press ({OUP})},author={Bennett, Alex M and Ulrich, Hannes and van Damme, Philip and Wiedekopf, Joshua and Johnson, Alistair E W},title={{MIMIC}-{IV} on {FHIR}: converting a decade of in-patient data into an exchangeable, interoperable format},journal={Journal of the American Medical Informatics Association},language={en},abbr={JAMIA}}
📖
Referenzterminologie SNOMED CT
Interlingua zur Gewährleistung semantischer Interoperabilität in der Medizin
SNOMED CT wird zunehmend auch in Deutschland als wesentlicher Baustein innovativer digitaler Gesundheitsanwendungen verwendet. Sie gilt mit über 350.000 formal definierten Konzepten sowie mehrsprachigen Bezeichnungen als ausdrucksmächtigste internationale Referenzterminologie. Gleichwohl stellt die Einführung von SNOMED CT mit dem Potenzial zur Postkoordination „neuer Konzepte“ einen Paradigmenwechsel dar. Dieser geht einher mit vielfältigsten methodischen Grundlagen, die interessierten Anwendern und Software-Entwicklern vermittelt werden müssen, um den erwarteten Nutzen realisieren zu können. Dieses Buch soll hierzu einen Beitrag leisten.
@book{ingenerf_drenkhahn_referenzterminologie_2023,author={Ingenerf, Josef and Drenkhahn, Cora},title={Referenzterminologie SNOMED CT},subtitle={Interlingua zur Gewährleistung semantischer Interoperabilität in der Medizin},publisher={Springer Vieweg},year={2023},doi={10.1007/978-3-658-35562-3},isbn={978-3-658-35562-3},language={de}}
2022
SHTI
TermiCron – Bridging the Gap Between FHIR Terminology Servers and Metadata Repositories
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.
@article{wiedekopf_termicron_2022,author={Wiedekopf, Joshua and Ulrich, Hannes and Drenkhahn, Cora and Kock-Schoppenhauer, Ann-Kristin and Ingenerf, Josef},journal={Studies in Health Technology and Informatics},conference={{MEDINFO} 2021},publisher={{IOS} Press},title={{TermiCron} {\textendash} Bridging the Gap Between {FHIR} Terminology Servers and Metadata Repositories},year={2022},month=jun,doi={10.3233/shti220034},slides={medinfo2021/TermiCron_v1.pdf},recording={https://www.youtube.com/watch?v=7L08Sh-1XxY},language={en},abbr={SHTI}}
Appl Sci
LUMA: A Mapping Assistant for Standardizing the Units of LOINC-Coded Laboratory Tests
The coding system Unified Code for Units of Measure (UCUM) serves the unambiguous electronic communication of physical quantities and their measurements and has faced a slow uptake. Despite being closely related to popular healthcare standards such as LOINC, laboratories still majorly report results using proprietary unit terms. Currently available methods helping users create mappings between their units and UCUM are not flexible and automated enough to be of great use in trying to remedy this. We propose the “LOINC to UCUM Mapping Assistant” (LUMA) as a tool able to overcome the drawbacks of existing approaches while being more accessible even to inexperienced users. By mapping LOINC’s Property axis to representations within UCUM reflecting its semantics, we were able to formalize the association between the two. An HL7 FHIR back-end provides LUMA with UCUM unit recommendations sourced from existing lookup tables simply by providing it with a LOINC code. Additionally, the mappings users created may be used to perform unit conversions from proprietary units to UCUM. The tool was evaluated with five participants from the LADR laboratory network in Germany, who valued the streamlined approach to creating the mappings and particularly emphasized the utility of being able to perform unit conversions within the tool.
@article{vogl_luma_2022,author={Vogl, Kai and Ingenerf, Josef and Kramer, Jan and Chantraine, Christine and Drenkhahn, Cora},title={LUMA: A Mapping Assistant for Standardizing the Units of LOINC-Coded Laboratory Tests},journal={Applied Sciences},volume={12},month=jun,year={2022},number={12},article-number={5848},url={https://www.mdpi.com/2076-3417/12/12/5848},issn={2076-3417},doi={10.3390/app12125848},language={en},abbr={Appl Sci}}
SHTI
TerminoDiff – Detecting Semantic Differences in HL7 FHIR CodeSystems
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.
@article{wiedekopf_terminodiff_2022,author={Wiedekopf, Joshua and Drenkhahn, Cora and Rosenau, Lorenz and Ulrich, Hannes and Kock-Schoppenhauer, Ann-Kristin and Ingenerf, Josef},journal={Studies in Health Technology and Informatics},conference={Medical Informatics Europe 2022},publisher={{IOS} Press},title={{TerminoDiff} {\textendash} Detecting Semantic Differences in {HL}7 {FHIR} {CodeSystems}},year={2022},month=may,doi={10.3233/shti220475},language={en},slides={mie2022/TerminoDiff-MIE-2022-JoshuaWiedekopf-1.1.pdf},abbr={SHTI}}
SHTI
Mapping of ICD-O tuples to OncoTree codes using SNOMED CT post-coordination
Around 500,000 oncological diseases are diagnosed in Germany every year which are documented using the International Classification of Diseases for Oncology (ICD-O). Apart from this, another classification for oncology, OncoTree, is often used for the integration of new research findings in oncology. For this purpose, a semi-automatic mapping of ICD-O tuples to OncoTree codes was developed. The implementation uses a FHIR terminology server, pre-coordinated or post-coordinated SNOMED CT expressions, and subsumption testing. Various validations have been applied. The results were compared with reference data of scientific papers and manually evaluated by a senior pathologist, confirming the applicability of SNOMED CT in general and its post-coordinated expressions in particular as a viable intermediate mapping step. Resulting in an agreement of 84,00 percent between the newly developed approach and the manual mapping, it becomes obvious that the present approach has the potential to be used in everyday medical practice.
@article{ohlsen_mapping_2022,title={Mapping of ICD-O tuples to OncoTree codes using SNOMED CT post-coordination},journal={Studies in Health Technology and Informatics},conference={Medical Informatics Europe 2022},volume={294},year={2022},month=may,pages={307--311},issn={1879-8365},doi={10.3233/SHTI220464},author={Ohlsen, Tessa and Kruse, Valerie and Krupar, Rosemarie and Banach, Alexandra and Ingenerf, Josef and Drenkhahn, Cora M.},language={en},abbr={SHTI}}
2021
lost in translation? semantische standardisierung!
Immer mehr Daten aus der Krankenversorgung werden digital abgelegt und bergen damit einen Schatz an verborgenen Erkenntnissen für Qualitäts- sicherung und Forschung. Jedoch unterbinden fehlende semantische Standardisierung und Mängel derzeit genutzter Codiersysteme deren zielführende Auswertbarkeit. Soll dieser Wissensschatz zukünftig gehoben werden, ist eine bedeutungserhaltende Codierung mit den im Folgenden thematisierten Terminologien wie LOINC oder SNOMED CT unum- gänglich. In Kombination mit dem international aufstrebenden FHIR-Standard entstehen aktuell vielversprechende interoperable Softwarelösungen. Wir möchten aufzeigen, warum sich die Investition in die Verwendung von Codes aus anspruchsvolleren Terminologien lohnt.
@article{drenkhahn_lost_2021,title={lost in translation? semantische standardisierung!},journal={gesundhyte.de},volume={14},number={14},year={2021},month=dec,pages={25{\textendash}28},url={https://www.systembiologie.de/lw_resource/datapool/systemfiles/elements/files/D344CA9772B73013E0537E695E8653F9/live/document/PTJ-009_gesundhyte_14_2021_dt_WEB-ISSN_2702-2552_211215_WEB.pdf},author={Drenkhahn, Cora M. and Ingenerf, Josef},language={de}}
Medical Data Engineering - Theory and Practice
Ann-Kristin Kock-Schoppenhauer, Björn Schreiweis, Hannes Ulrich, Niklas Reimer, Joshua Wiedekopf, Benjamin Kinast, Hauke Busch, Björn Bergh, und Josef Ingenerf
Advances in Model and Data Engineering in the Digitalization Era Oct 2021
Herausgeber: Ladjel Bellatreche, George Chernishev, Antonio Corral, Samir Ouchani, und Jüri Vain
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.
@article{kockschopp_medical_2021,location={Cham},title={Medical Data Engineering - Theory and Practice},volume={1481},isbn={978-3-030-87656-2 978-3-030-87657-9},url={https://link.springer.com/10.1007/978-3-030-87657-9_21},pages={269--284},journal={Advances in Model and Data Engineering in the Digitalization Era},publisher={Springer International Publishing},author={Kock-Schoppenhauer, Ann-Kristin and Schreiweis, Björn and Ulrich, Hannes and Reimer, Niklas and Wiedekopf, Joshua and Kinast, Benjamin and Busch, Hauke and Bergh, Björn and Ingenerf, Josef},editor={Bellatreche, Ladjel and Chernishev, George and Corral, Antonio and Ouchani, Samir and Vain, Jüri},year={2021},month=oct,langid={english},doi={10.1007/978-3-030-87657-9_21},note={Series Title: Communications in Computer and Information Science},language={en}}
SHTI
Providing ART-DECOR ValueSets via FHIR Terminology Servers - A Technical Report
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.
@article{wiedekopf_artdecor_2021,title={Providing {ART}-{DECOR} {ValueSets} via {FHIR} Terminology Servers - A Technical Report},isbn={978-1-64368-206-8 978-1-64368-207-5},url={https://ebooks.iospress.nl/doi/10.3233/SHTI210550},journal={Studies in Health Technology and Informatics},conference={GMDS 2021},publisher={{IOS} Press},author={Wiedekopf, Joshua and Drenkhahn, Cora and Ulrich, Hannes and Kock-Schoppenhauer, Ann-Kristin and Ingenerf, Josef},editor={Röhrig, Rainer and Beißbarth, Tim and König, Jochem and Ose, Claudia and Rauch, Geraldine and Sax, Ulrich and Schreiweis, Björn and Sedlmayr, Martin},year={2021},month=sep,doi={10.3233/SHTI210550},slides={gmds2021/artdecor-gmds2021.pdf},language={en},abbr={SHTI}}
SHTI
Desiderata for a Synthetic Clinical Data Generator
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.
@article{wiedekopf_desiderata_2021,doi={10.3233/shti210122},url={https://doi.org/10.3233/shti210122},year={2021},month=may,publisher={{IOS} Press},author={Wiedekopf, Joshua and Ulrich, Hannes and Essenwanger, Andrea and Kiel, Alexander and Kock-Schoppenhauer, Ann-Kristin and Ingenerf, Josef},title={Desiderata for a Synthetic Clinical Data Generator},booktitle={Studies in Health Technology and Informatics},recording={https://www.youtube.com/watch?v=pBsV9mvya88},conference={Medical Informatics Europe 2021},language={en},abbr={SHTI}}
SHTI
Perspectives and Obstacles for Transforming Terminologies into FHIR CodeSystems Exemplified by Alpha-ID
The terminology services, defined as part of the emerging FHIR standard, yield a promising approach to finally achieve a common handling of coding systems needed for semantic interoperability. As a precondition, legacy terminology data must be transformed into FHIR-compatible resources whereby varying source formats make a manual case-by-case solution impracticable. In this work, the practicability of using CSIRO’s Ontoserver and the related Snapper tool as support of the transformation process were evaluated by applying them to the German Alpha-ID terminology.
@article{drenkhahn_perspectives_2021,title={Perspectives and Obstacles for Transforming Terminologies into FHIR CodeSystems Exemplified by Alpha-ID},journal={Studies in Health Technology and Informatics},volume={281},year={2021},pages={213-217},doi={https://doi.org/10.3233/SHTI210151},conference={GMDS 2021},author={Rajput, Abdul-Mateen and Drenkhahn, Cora M.},language={en},abbr={SHTI}}
2020
Using FHIR terminology services-based tools for mapping of local microbiological pathogen terms to SNOMED CT at a German university hospital
@inproceedings{drenkhahn_using_2020,title={Using {FHIR} terminology services-based tools for mapping of local microbiological pathogen terms to {SNOMED} {CT} at a German university hospital},booktitle={16. {DVMD}-Fachtagung},author={Drenkhahn, Cora and Burmester, Sebastian and Ballout, Sarah and Ulrich, Hannes and Wiedekopf, Joshua and Ingenerf, Josef},year={2020},month=oct,language={en}}
