@article{sleimann_implementation_2023,
	title = {Implementation of a clinical long-term follow-up database for adult childhood cancer survivors in {Germany}: a feasibility study at two specialised late effects clinics},
	issn = {1432-1335},
	shorttitle = {Implementation of a clinical long-term follow-up database for adult childhood cancer survivors in {Germany}},
	url = {https://doi.org/10.1007/s00432-023-05145-8},
	doi = {10.1007/s00432-023-05145-8},
	abstract = {Childhood cancer survivors (CCS) are at risk for increased morbidity and reduced quality of life associated with treatment-related late effects. In Germany, however, only a few of the more than 40,000 CCS registered in the German Childhood Cancer Registry (GCCR) currently benefit from adequate clinical long-term follow-up (LTFU) structures. To establish a comprehensive knowledge base on CCS’ long-term health in Germany, a database was developed in cooperation with the GCCR. Following a first evaluation phase at two German university centres, this database will be implemented more widely within Germany allowing longitudinal documentation of clinical LTFU data.},
	language = {en},
	urldate = {2023-07-18},
	journal = {Journal of Cancer Research and Clinical Oncology},
	author = {Sleimann, Madelaine and Balcerek, Magdalena and Cytera, Chirine and Richter, Franziska and Borgmann-Staudt, Anja and Wörmann, Bernhard and Kronziel, Lea Louisa and Calaminus, Gabriele and Kock-Schoppenhauer, Ann-Kristin and Grabow, Desiree and Baust, Katja and Neumann, Anke and Langer, Thorsten and Gebauer, Judith},
	month = jul,
	year = {2023},
	keywords = {Childhood cancer survivors, Epidemiology, Health, Late effects, Long-term follow-up, Quality of life},
}

@article{drenkhahn_waspweb_2023,
	title = {{WASP}—{A} {Web} {Application} to {Support} {Syntactically} and {Semantically} {Correct} {SNOMED} {CT} {Postcoordination}},
	volume = {13},
	issn = {2076-3417},
	url = {https://www.mdpi.com/2076-3417/13/10/6114},
	doi = {10.3390/app13106114},
	abstract = {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.},
	language = {en},
	number = {10},
	urldate = {2023-05-22},
	journal = {Applied Sciences},
	author = {Drenkhahn, Cora and Ohlsen, Tessa and Wiedekopf, Joshua and Ingenerf, Josef},
	month = may,
	year = {2023},
	pages = {6114},
}

@article{unberath_searching_2022,
	title = {Searching of {Clinical} {Trials} {Made} {Easier} in {cBioPortal} {Using} {Patients}' {Genetic} and {Clinical} {Profiles}},
	volume = {13},
	issn = {1869-0327},
	url = {http://www.thieme-connect.de/DOI/DOI?10.1055/s-0042-1743560},
	doi = {10.1055/s-0042-1743560},
	abstract = {Abstract
            Background Molecular tumor boards (MTBs) cope with the complexity of an increased usage of genome sequencing data in cancer treatment. As for most of these patients, guideline-based therapy options are exhausted, finding matching clinical trials is crucial. This search process is often performed manually and therefore time consuming and complex due to the heterogeneous and challenging dataset.
            Objectives In this study, a prototype for a search tool was developed to demonstrate how cBioPortal as a clinical and genomic patient data source can be integrated with ClinicalTrials.gov, a database of clinical studies to simplify the search for trials based on genetic and clinical data of a patient. The design of this tool should rest on the specific needs of MTB participants and the architecture of the integration should be as lightweight as possible and should not require manual curation of trial data in advance with the goal of quickly and easily finding a matching study.
            Methods Based on a requirements analysis, interviewing MTB experts, a prototype was developed. It was further refined using a user-centered development process with multiple feedback loops. Finally, the usability of the application was evaluated with user interviews including the thinking-aloud protocol and the system usability scale (SUS) questionnaire.
            Results The integration of ClinicalTrials.gov in cBioPortal is achieved by a new tab in the patient view where the genomic profile for the search is prefilled and additional parameters can be adjusted. These parameters are then used to query the application programming interface (API) of ClinicalTrials.gov. The returned search results subsequently are ranked and presented to the user. The evaluation of the application resulted in an SUS score of 83.5.
            Conclusion This work demonstrates the integration of cBioPortal with ClinicalTrials.gov to use clinical and genomic patient data to search for appropriate trials within an MTB.},
	language = {en},
	number = {02},
	urldate = {2022-03-31},
	journal = {Applied Clinical Informatics},
	author = {Unberath, Philipp and Mahlmeister, Lukas and Reimer, Niklas and Busch, Hauke and Boerries, Melanie and Christoph, Jan},
	month = mar,
	year = {2022},
	pages = {363--369},
}

@article{wiedekopf_terminodiff_2022,
	title = {{TerminoDiff} - {Detecting} {Semantic} {Differences} in {HL7} {FHIR} {CodeSystems}},
	volume = {294},
	issn = {1879-8365},
	url = {https://doi.org/10.3233/SHTI220475},
	doi = {10.3233/SHTI220475},
	abstract = {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.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Wiedekopf, Joshua and Drenkhahn, Cora and Rosenau, Lorenz and Ulrich, Hannes and Kock-Schoppenhauer, Ann-Kristin and Ingenerf, Josef},
	month = may,
	year = {2022},
	pmid = {35612097},
	keywords = {Delivery of Health Care, Drug Packaging, Electronic Health Records, HL7 FHIR, Health Information Exchange, Health Level Seven, Metadata, Semantics, Terminology as Topic, Vocabulary},
	pages = {362--366},
}

@article{wiedekopf_termicron_2022,
	title = {{TermiCron} - {Bridging} the {Gap} {Between} {FHIR} {Terminology} {Servers} and {Metadata} {Repositories}},
	volume = {290},
	issn = {1879-8365},
	url = {https://doi.org/10.3233/SHTI220034},
	doi = {10.3233/SHTI220034},
	abstract = {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.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Wiedekopf, Joshua and Ulrich, Hannes and Drenkhahn, Cora and Kock-Schoppenhauer, Ann-Kristin and Ingenerf, Josef},
	month = jun,
	year = {2022},
	pmid = {35672973},
	keywords = {Delivery of Health Care, HL7 FHIR, Health Facilities, Metadata, Metadata Repository, Secondary Use, Semantics},
	pages = {71--75},
}

@article{ulrich_understanding_2022,
	title = {Understanding the {Nature} of {Metadata}: {Systematic} {Review}},
	volume = {24},
	shorttitle = {Understanding the {Nature} of {Metadata}},
	url = {https://www.jmir.org/2022/1/e25440},
	doi = {10.2196/25440},
	abstract = {Background: Metadata are created to describe the corresponding data in a detailed and unambiguous way and is used for various applications in different research areas, for example, data identification and classification. However, a clear definition of metadata is crucial for further use. Unfortunately, extensive experience with the processing and management of metadata has shown that the term “metadata” and its use is not always unambiguous.
Objective: This study aimed to understand the definition of metadata and the challenges resulting from metadata reuse.
Methods: A systematic literature search was performed in this study following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for reporting on systematic reviews. Five research questions were identified to streamline the review process, addressing metadata characteristics, metadata standards, use cases, and problems encountered. This review was preceded by a harmonization process to achieve a general understanding of the terms used.
Results: The harmonization process resulted in a clear set of definitions for metadata processing focusing on data integration. The following literature review was conducted by 10 reviewers with different backgrounds and using the harmonized definitions. This study included 81 peer-reviewed papers from the last decade after applying various filtering steps to identify the most relevant papers. The 5 research questions could be answered, resulting in a broad overview of the standards, use cases, problems, and corresponding solutions for the application of metadata in different research areas.
Conclusions: Metadata can be a powerful tool for identifying, describing, and processing information, but its meaningful creation is costly and challenging. This review process uncovered many standards, use cases, problems, and solutions for dealing with metadata. The presented harmonized definitions and the new schema have the potential to improve the classification and generation of metadata by creating a shared understanding of metadata and its context.},
	language = {EN},
	number = {1},
	urldate = {2022-01-12},
	journal = {Journal of Medical Internet Research},
	author = {Ulrich, Hannes and Kock-Schoppenhauer, Ann-Kristin and Deppenwiese, Noemi and Gött, Robert and Kern, Jori and Lablans, Martin and Majeed, Raphael W. and Stöhr, Mark R. and Stausberg, Jürgen and Varghese, Julian and Dugas, Martin and Ingenerf, Josef},
	month = jan,
	year = {2022},
	note = {Company: Journal of Medical Internet Research
Distributor: Journal of Medical Internet Research
Institution: Journal of Medical Internet Research
Label: Journal of Medical Internet Research
Publisher: JMIR Publications Inc., Toronto, Canada},
	keywords = {Humans, Metadata, Publications, Reference Standards, data classification, data identification, data integration, metadata, metadata definition, systematic review},
	pages = {e25440},
}

@article{ulrich_proposal_2022,
	title = {Proposal of {Semantic} {Annotation} for {German} {Metadata} {Using} {Bidirectional} {Recurrent} {Neural} {Networks}},
	url = {https://ebooks.iospress.nl/doi/10.3233/SHTI220474},
	doi = {10.3233/SHTI220474},
	urldate = {2022-08-16},
	journal = {Challenges of Trustable AI and Added-Value on Health},
	author = {Ulrich, Hannes and Uzunova, Hristina and Handels, Heinz and Ingenerf, Josef},
	year = {2022},
	note = {Publisher: IOS Press},
	pages = {357--361},
}

@article{gruendner_architecture_2022,
	title = {Architecture for a feasibility query portal for distributed {COVID}-19 {Fast} {Healthcare} {Interoperability} {Resources} ({FHIR}) patient data repositories: {Design} and {Implementation} {Study}},
	issn = {2291-9694},
	shorttitle = {Architecture for a feasibility query portal for distributed {COVID}-19 {Fast} {Healthcare} {Interoperability} {Resources} ({FHIR}) patient data repositories},
	url = {https://doi.org/10.2196/36709},
	doi = {10.2196/36709},
	abstract = {BACKGROUND: An essential step in any medical research project after having identified the research question is to find out if there are enough patients available for a study and where to find them. Pursuing digital feasibility queries on available patient data registries has proven to be an excellent way of reusing existing real world data sources. To support multicentric research, these feasibility queries should be designed and implemented to run across multiple sites and securely access local data. Working across hospitals usually also means working with different data formats and vocabularies. Recently, the Fast Healthcare Interoperability Resources (FHIR) standard has been developed by HL7 to address this concern and describe patient data in a standardized format. The Medical Informatics Initiative (MII) in Germany has committed to this standard and created Data Integration Centers, which convert existing data into the FHIR format at each hospital. This partially solves the interoperability problem, however a distributed feasibility query platform for the FHIR standard is still missing.
OBJECTIVE: This study describes the design and implementation of the components involved in creating a cross-hospital feasibility query platform for researchers based on FHIR resources. This effort is part of a larger COVID-19 data exchange platform (CODEX) and is designed to be scalable for a broad range of patient data.
METHODS: We analyzed and designed the abstract components necessary for a distributed feasibility query. This included a user interface for creating the query, a backend with an ontology and terminology service, a middleware for query distribution and a FHIR feasibility query execution service.
RESULTS: We implemented the components identified in the methods. The resulting solution was distributed to 33 German university hospitals. The functionality of the comprehensive network infrastructure was demonstrated using a test dataset based on the German Corona Consensus Dataset (GECCO). A performance test using specifically created synthetic data revealed the applicability of our solution to datasets containing millions of FHIR resources. The solution can be easily deployed across the hospitals and supports feasibility queries, combining multiple inclusion and exclusion criteria using standard Health Level Seven (HL7) query languages such as the Clinical Quality Language (CQL) and FHIR Search. Developing a platform based on multiple microservices allowed us to create an extendable platform and support multiple HL7 query languages and middleware components to allow integration with future directions of the Medical Informatics Initiative.
CONCLUSIONS: We designed and implemented a feasibility platform for distributed feasibility queries, which works directly on FHIR formatted data and distributed it across 33 university hospitals in Germany. We showed that developing a feasibility platform directly on the FHIR standard is feasible.
CLINICALTRIAL:},
	language = {eng},
	journal = {JMIR medical informatics},
	author = {Gruendner, Julian and Deppenwiese, Noemi and Folz, Michael and Köhler, Thomas and Kroll, Björn and Prokosch, Hans-Ulrich and Rosenau, Lorenz and Rühle, Mathias and Scheidl, Marc-Anton and Schüttler, Christina and Sedlmayr, Brita and Twrdik, Alexander and Kiel, Alexander and Majeed, Raphael W.},
	month = apr,
	year = {2022},
	pmid = {35486893},
}

@article{ohlsen_mapping_2022,
	title = {Mapping of {ICD}-{O} {Tuples} to {OncoTree} {Codes} {Using} {SNOMED} {CT} {Post}-{Coordination}},
	volume = {294},
	issn = {1879-8365},
	url = {https://doi.org/10.3233/SHTI220464},
	doi = {10.3233/SHTI220464},
	abstract = {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 \% 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.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Ohlsen, Tessa and Kruse, Valerie and Krupar, Rosemarie and Banach, Alexandra and Ingenerf, Josef and Drenkhahn, Cora},
	month = may,
	year = {2022},
	pmid = {35612082},
	keywords = {Germany, HL7 FHIR, ICD-O, International Classification of Diseases, Medical Oncology, OncoTree, Ontoserver, SNOMED CT, Systematized Nomenclature of Medicine, post-coordination, terminology server},
	pages = {307--311},
}

@article{bastian_ubtfatxn7l3_2022,
	title = {{UBTF}::{ATXN7L3} gene fusion defines novel {B} cell precursor {ALL} subtype with {CDX2} expression and need for intensified treatment},
	issn = {0887-6924, 1476-5551},
	shorttitle = {{UBTF}},
	url = {https://www.nature.com/articles/s41375-022-01557-6},
	doi = {10.1038/s41375-022-01557-6},
	language = {en},
	urldate = {2022-04-12},
	journal = {Leukemia},
	author = {Bastian, Lorenz and Hartmann, Alina M. and Beder, Thomas and Hänzelmann, Sonja and Kässens, Jan and Bultmann, Miriam and Hoeppner, Marc P. and Franzenburg, Sören and Wittig, Michael and Franke, Andre and Nagel, Inga and Spielmann, Malte and Reimer, Niklas and Busch, Hauke and Schwartz, Stefan and Steffen, Björn and Viardot, Andreas and Döhner, Konstanze and Kondakci, Mustafa and Wulf, Gerald and Wendelin, Knut and Renzelmann, Andrea and Kiani, Alexander and Trautmann, Heiko and Neumann, Martin and Gökbuget, Nicola and Brüggemann, Monika and Baldus, Claudia D.},
	month = apr,
	year = {2022},
}

@article{rosenau_generation_2022,
	title = {Generation of a {Fast} {Healthcare} {Interoperability} {Resources} ({FHIR})-based {Ontology} for {Federated} {Feasibility} {Queries} in the {Context} of {COVID}-19: {Feasibility} {Study}},
	volume = {10},
	issn = {2291-9694},
	shorttitle = {Generation of a {Fast} {Healthcare} {Interoperability} {Resources} ({FHIR})-based {Ontology} for {Federated} {Feasibility} {Queries} in the {Context} of {COVID}-19},
	url = {https://doi.org/10.2196/35789},
	doi = {10.2196/35789},
	abstract = {BACKGROUND: The COVID-19 pandemic highlighted the importance of making research data from all German hospitals available to scientists to respond to current and future pandemics promptly. The heterogeneous data originating from proprietary systems at hospitals' sites must be harmonized and accessible. The German Corona Consensus Dataset (GECCO) specifies how data for COVID-19 patients will be standardized in Fast Healthcare Interoperability Resources (FHIR) profiles across German hospitals. However, given the complexity of the FHIR standard, the data harmonization is not sufficient to make the data accessible. A simplified visual representation is needed to reduce the technical burden, while allowing feasibility queries.
OBJECTIVE: This study investigates how a search ontology can be automatically generated using FHIR profiles and a terminology server. Furthermore, it describes how this ontology can be used in a user interface (UI) and how a mapping and a terminology tree created together with the ontology can translate user input into FHIR queries.
METHODS: We used the FHIR profiles from the GECCO data set combined with a terminology server to generate an ontology and the required mapping files for the translation. We analyzed the profiles and identified search criteria for the visual representation. In this process, we reduced the complex profiles to code value pairs for improved usability. We enriched our ontology with the necessary information to display it in a UI. We also developed an intermediate query language to transform the queries from the UI to federated FHIR requests. Separation of concerns resulted in discrepancies between the criteria used in the intermediate query format and the target query language. Therefore, a mapping was created to reintroduce all information relevant for creating the query in its target language. Further, we generated a tree representation of the ontology hierarchy, which allows resolving child concepts in the process.
RESULTS: In the scope of this project, 82 (99\%) of 83 elements defined in the GECCO profile were successfully implemented. We verified our solution based on an independently developed test patient. A discrepancy between the test data and the criteria was found in 6 cases due to different versions used to generate the test data and the UI profiles, the support for specific code systems, and the evaluation of postcoordinated Systematized Nomenclature of Medicine (SNOMED) codes. Our results highlight the need for governance mechanisms for version changes, concept mapping between values from different code systems encoding the same concept, and support for different unit dimensions.
CONCLUSIONS: We developed an automatic process to generate ontology and mapping files for FHIR-formatted data. Our tests found that this process works for most of our chosen FHIR profile criteria. The process established here works directly with FHIR profiles and a terminology server, making it extendable to other FHIR profiles and demonstrating that automatic ontology generation on FHIR profiles is feasible.},
	language = {eng},
	number = {4},
	journal = {JMIR medical informatics},
	author = {Rosenau, Lorenz and Majeed, Raphael W. and Ingenerf, Josef and Kiel, Alexander and Kroll, Björn and Köhler, Thomas and Prokosch, Hans-Ulrich and Gruendner, Julian},
	month = apr,
	year = {2022},
        pmid = {35380548},
        pages = {e35789},
}

@article{vogl_luma_2022,
	title = {{LUMA}: {A} {Mapping} {Assistant} for {Standardizing} the {Units} of {LOINC}-{Coded} {Laboratory} {Tests}},
	volume = {12},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {2076-3417},
	shorttitle = {{LUMA}},
	url = {https://www.mdpi.com/2076-3417/12/12/5848},
	doi = {10.3390/app12125848},
	abstract = {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.},
	language = {en},
	number = {12},
	urldate = {2022-06-08},
	journal = {Applied Sciences},
	author = {Vogl, Kai and Ingenerf, Josef and Kramer, Jan and Chantraine, Christine and Drenkhahn, Cora},
	month = jan,
	year = {2022},
	note = {Number: 12
Publisher: Multidisciplinary Digital Publishing Institute},
	keywords = {HL7 FHIR, LOINC, RELMA, REST, UCUM, mapping, standardization},
	pages = {5848},
}

@article{wulff_transformation_2021,
	title = {Transformation of microbiology data into a standardised data representation using {OpenEHR}},
	volume = {11},
	copyright = {2021 The Author(s)},
	issn = {2045-2322},
	url = {https://www.nature.com/articles/s41598-021-89796-y},
	doi = {10.1038/s41598-021-89796-y},
	abstract = {The spread of multidrug resistant organisms (MDRO) is a global healthcare challenge. Nosocomial outbreaks caused by MDRO are an important contributor to this threat. Computer-based applications facilitating outbreak detection can be essential to address this issue. To allow application reusability across institutions, the various heterogeneous microbiology data representations needs to be transformed into standardised, unambiguous data models. In this work, we present a multi-centric standardisation approach by using openEHR as modelling standard. Data models have been consented in a multicentre and international approach. Participating sites integrated microbiology reports from primary source systems into an openEHR-based data platform. For evaluation, we implemented a prototypical application, compared the transformed data with original reports and conducted automated data quality checks. We were able to develop standardised and interoperable microbiology data models. The publicly available data models can be used across institutions to transform real-life microbiology reports into standardised representations. The implementation of a proof-of-principle and quality control application demonstrated that the new formats as well as the integration processes are feasible. Holistic transformation of microbiological data into standardised openEHR based formats is feasible in a real-life multicentre setting and lays the foundation for developing cross-institutional, automated outbreak detection systems.},
	language = {en},
	number = {1},
	urldate = {2021-07-14},
	journal = {Scientific Reports},
	author = {Wulff, Antje and Baier, Claas and Ballout, Sarah and Tute, Erik and Sommer, Kim Katrin and Kaase, Martin and Sargeant, Anneka and Drenkhahn, Cora and Schlüter, Dirk and Marschollek, Michael and Scheithauer, Simone},
	month = may,
	year = {2021},
	note = {Bandiera\_abtest: a
Cc\_license\_type: cc\_by
Cg\_type: Nature Research Journals
Number: 1
Primary\_atype: Research
Publisher: Nature Publishing Group
Subject\_term: Computational biology and bioinformatics;Microbiology
Subject\_term\_id: computational-biology-and-bioinformatics;microbiology},
	pages = {10556},
}

@inproceedings{simon_provision_2021,
	location = {Luebeck},
	title = {Provision of sensitive clinical and biobank data for research in compliance with data protection regulations},
	isbn = {978-3-945954-65-2},
	series = {Student Conference Proceedings},
	abstract = {The Interdisciplinary Center for Biobanking-Lübeck is a centralized biobank operating at the Campus Lübeck. They pro-vide a clinical research infrastructure which enables a researcher to search for patient and sample data in pseudonymizedform.  An approved data protection concept exists for the process and is in routine use.  The established process is time-consuming and requires many manual steps. Extensions and necessary adaptations on the process are difficult due to theimplemented architecture and techniques.  The aim of this project is to renew and improve the process of provision ofpseudonymized data to researchers, without the need to change the data protection concept. The first step was to analyseand describe the existing process in detail. Next resulted in a Selection, Pseudonymisation and Synchronisation Pipeline({SPSP}), which extends the existing infrastructure and fulfils all aspects of the data protection concept.},
	publisher = {Infinite Science Publishing},
	author = {Simon, Friedrich and Kock-Schoppenhauer, Ann-Kristin and Ulrich, Hannes and Oberländer, Martina and Maushagen, Regina and Friedemann, Flügge and Ingenerf, Josef},
	year = {2021},
}

@incollection{rohrig_providing_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},
	abstract = {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.},
	urldate = {2021-09-28},
	booktitle = {Studies in {Health} {Technology} and {Informatics}},
	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},
	month = sep,
	year = {2021},
	doi = {10.3233/SHTI210550},
}

@article{rajput_perspectives_2021,
	title = {Perspectives and {Obstacles} for {Transforming} {Terminologies} into {FHIR} {CodeSystems} {Exemplified} by {Alpha}-{ID}},
	volume = {281},
	issn = {1879-8365},
	doi = {10.3233/SHTI210151},
	abstract = {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.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Rajput, Abdul-Mateen and Drenkhahn, Cora},
	year = {2021},
	pmid = {34042736},
	keywords = {Alpha-ID, FHIR Code System, HiGHmed, ICD-10-GM, Ontoserver, Semantic Interoperability, Terminology Server},
	pages = {213--217},
}

@article{banach_aperitif_2021,
	title = {{APERITIF} - {Automatic} {Patient} {Recruiting} for {Clinical} {Trials} {Based} on {HL7} {FHIR}},
	volume = {281},
	issn = {1879-8365},
	doi = {10.3233/SHTI210120},
	abstract = {Clinical trials are carried out to prove the safety and effectiveness of new interventions and therapies. As diseases and their causes continue to become more specific, so do inclusion and exclusion criteria for trials. Patient recruitment has always been a challenge, but with medical progress, it becomes increasingly difficult to achieve the necessary number of cases. In Germany, the Medical Informatics Initiative is planning to use the central application and registration office to conduct feasibility analyses at an early stage and thus to identify suitable project partners. This approach aims to technically adapt/integrate the envisioned infrastructure in such a way that it can be used for trial case number estimation for the planning of multicenter clinical trials. We have developed a fully automated solution called APERITIF that can identify the number of eligible patients based on free-text eligibility criteria, taking into account the MII core data set and based on the FHIR standard. The evaluation showed a precision of 62.64 \% for inclusion criteria and a precision of 66.45 \% for exclusion criteria.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Banach, Alexandra and Ulrich, Hannes and Kroll, Björn and Kiel, Alexander and Ingenerf, Josef and Kock-Schoppenhauer, Ann-Kristin},
	month = may,
	year = {2021},
	pmid = {34042705},
	keywords = {CQL, Electronic Health Records, FHIR, Germany, Humans, Medical Informatics, NLP, clinical trials, patient recruitment},
	pages = {58--62},
}

@incollection{rohrig_one_2021,
	title = {One Conference, Three Proceedings – Which Papers Should I Submit and How? A Publication Strategy for Young Scientists Regarding the {GMDS} Annual Conference and Beyond (Editorial)},
	isbn = {978-1-64368-206-8 978-1-64368-207-5},
	url = {https://ebooks.iospress.nl/doi/10.3233/SHTI210535},
	shorttitle = {One Conference, Three Proceedings – Which Papers Should I Submit and How?},
	abstract = {The primary intention of any scientific work is to share the gained knowledge and to contribute to the knowledge and progress in the scientific domain. The wide range of journals and conferences, each with specific submission requirements, can be difficult to navigate, especially for young scientists without extensive experience. But a suitable publication strategy can be helpful, especially at the beginning of a scientific career. Using the annual conference of the German Association for Medical Informatics, Biometry and Epidemiology ({GMDS}) e.V. as an example, this editorial highlights fundamental differences, advantages and disadvantages, as well as assistance in selecting the right form of submission.},
	booktitle = {Studies in Health Technology and Informatics},
	publisher = {{IOS} Press},
	author = {Schreiweis, Björn and Kock-Schoppenhauer, Ann-Kristin},
	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},
	urldate = {2021-09-22},
	doi = {10.3233/SHTI210535},
}

@incollection{rohrig_openehr_2021,
	title = {{openEHR} {Mapper} – {A} {Tool} to {Fuse} {Clinical} and {Genomic} {Data} {Using} the {openEHR} {Standard}},
	isbn = {978-1-64368-176-4 978-1-64368-177-1},
	url = {https://ebooks.iospress.nl/doi/10.3233/SHTI210055},
	abstract = {Precision medicine is an emerging and important field for health care. Molecular tumor boards use a combination of clinical and molecular data, such as somatic tumor mutations to decide on personalized therapies for patients who have run out of standard treatment options. Personalized treatment decisions require clinical data from the hospital information system and mutation data to be accessible in a structured way. Here we introduce an open data platform to meet these requirements. We use the openEHR standard to create an expert-curated data model that is stored in a vendor-neutral format. Clinical and molecular patient data is integrated into cBioPortal, a warehousing solution for cancer genomic studies that is extended for use in clinical routine for molecular tumor boards. For data integration, we developed openEHR Mapper, a tool that allows to (i) process input data, (ii) communicate with the openEHR repository, and (iii) export the data to cBioPortal. We benchmarked the mapper performance using XML and JSON as serialization format and added caching capabilities as well as multi-threading to the openEHR Mapper.},
	urldate = {2021-05-29},
	booktitle = {Studies in {Health} {Technology} and {Informatics}},
	publisher = {IOS Press},
	author = {Reimer, Niklas and Ulrich, Hannes and Busch, Hauke and Kock-Schoppenhauer, Ann-Kristin and Ingenerf, Josef},
	editor = {Röhrig, Rainer and Beißbarth, Tim and Brannath, Werner and Prokosch, Hans-Ulrich and Schmidtmann, Irene and Stolpe, Susanne and Zapf, Antonia},
	month = may,
	year = {2021},
	doi = {10.3233/SHTI210055},
}

@article{ulrich_hands_2021,
	title = {Hands on the {Medical} {Informatics} {Initiative} {Core} {Data} {Set} - {Lessons} {Learned} from {Converting} the {MIMIC}-{IV}},
	volume = {283},
	issn = {1879-8365},
	doi = {10.3233/SHTI210549},
	abstract = {With the steady increase in the connectivity of the healthcare system, new requirements and challenges are emerging. In addition to the seamless exchange of data between service providers on a national level, the local legacy data must also meet the new requirements. For this purpose, the applications used must be tested securely and sufficiently. However, the availability of suitable and realistic test data is not always given. Therefore, this study deals with the creation of test data based on real electronic health record data provided by the Medical Information Mart for Intensive Care (MIMIC-IV) database. In addition to converting the data to the current FHIR R4, conversion to the core data sets of the German Medical Informatics Initiative was also presented and made available. The test data was generated to simulate a legacy data transfer. Moreover, four different FHIR servers were tested for performance. This study is the first step toward comparable test scenarios around shared datasets and promotes comparability among providers on a national level.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Ulrich, Hannes and Behrend, Paul and Wiedekopf, Joshua and Drenkhahn, Cora and Kock-Schoppenhauer, Ann-Kristin and Ingenerf, Josef},
	month = sep,
	year = {2021},
	pmid = {34545827},
	keywords = {Data Integration, Delivery of Health Care, Electronic Health Records, HL7 FHIR, Information Dissemination, MIMIC-IV, Medical Informatics},
	pages = {119--126},
}

@incollection{mantas_fhirspark_2021,
	title = {{FhirSpark} – {Implementing} a {Mediation} {Layer} to {Bring} {FHIR} to the {cBioPortal} for {Cancer} {Genomics}},
	isbn = {978-1-64368-184-9 978-1-64368-185-6},
	url = {https://ebooks.iospress.nl/doi/10.3233/SHTI210169},
	abstract = {cBioPortal is a commonly used data warehousing solution for genomic cancer studies. The software is being extended for patient care application in a molecular tumor board by the MIRACUM consortium within the Medical Informatics Initiative Germany. A key feature for this use case is the ability to enter therapy recommendations for individual patients, which requires interoperability with the hospital information system. A RESTful interface between cBioPortal and an external mediation layer was selected from the different implementation options. It achieves interoperability by using a FHIR capable server to store data and applying the HL7 FHIR Genomics Reporting implementation guide. For systems not supporting the FHIR standard, the well-established HL7 Version 2 standard is available as a fallback export format.},
	urldate = {2021-05-29},
	booktitle = {Studies in {Health} {Technology} and {Informatics}},
	publisher = {IOS Press},
	author = {Reimer, Niklas and Unberath, Philipp and Busch, Hauke and Ingenerf, Josef},
	editor = {Mantas, John and Stoicu-Tivadar, Lăcrămioara and Chronaki, Catherine and Hasman, Arie and Weber, Patrick and Gallos, Parisis and Crişan-Vida, Mihaela and Zoulias, Emmanouil and Chirila, Oana Sorina},
	month = may,
	year = {2021},
	doi = {10.3233/SHTI210169},
}

@inproceedings{banach_evaluating_2021,
	address = {Berlin},
	title = {Evaluating {Automated} {Methods} for {Metadata} {Quality} in {Healthcare}},
	copyright = {This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License.},
	doi = {10.3205/20gmds192},
	language = {engl},
	publisher = {German Medical Science GMS Publishing House},
	author = {Banach, Alexandra and Kock-Schoppenhauer, Ann-Kristin and Ulrich, Hannes and Ingenerf, Josef},
	month = feb,
	year = {2021},
	keywords = {ISO 11179, evaluation, metadata},
	pages = {DocAbstr. 221},
}

@article{wiedekopf_desiderata_2021,
	title = {Desiderata for a {Synthetic} {Clinical} {Data} {Generator}},
	volume = {281},
	issn = {1879-8365},
	doi = {10.3233/SHTI210122},
	abstract = {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.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Wiedekopf, Joshua and Ulrich, Hannes and Essenwanger, Andrea and Kiel, Alexander and Kock-Schoppenhauer, Ann-Kristin and Ingenerf, Josef},
	month = may,
	year = {2021},
	pmid = {34042707},
	keywords = {Electronic Health Records, Humans, Medical Informatics, Privacy, RS-EHR, Realistic Synthetic Electronic Health Records, Requirements, Secondary Use, Synthetic Data},
	pages = {68--72},
}

@inproceedings{banach_benefits_2021,
	address = {Kiel},
	title = {Benefits of {MII} {Core} {Dataset} and {HL7} {FHIR}-{Based} {Tooling} for {Automated} {Recruiting} {Purposes}},
	copyright = {This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License.},
	doi = {10.3205/21gmds027},
	language = {engl},
	publisher = {German Medical Science GMS Publishing House},
	author = {Banach, Alexandra and Ulrich, Hannes and Kroll, Björn and Kiel, Alexander and Ingenerf, Josef and Kock-Schoppenhauer, Ann-Kristin},
	month = sep,
	year = {2021},
	keywords = {CQL, FHIR, NLP, clinical trials, patient recruitment},
	pages = {DocAbstr. 125},
}

@article{sax_highmed_2021,
	title = {{HiGHmed} {Medical} {Data} {Integration} {Centers} and their {Different} {Architecture} {Designs} ({Workshop})},
	copyright = {Creative Commons Attribution 4.0 International},
	url = {https://www.egms.de/en/meetings/gmds2021/21gmds122.shtml},
	doi = {10.3205/21GMDS122},
	abstract = {Introduction: The collaborative efforts of the German Medical Informatics Initiative (MII) [ref:1] [BS1] especially on methods of informed consent and information model standardization [ref:1] pave the way on making healthcare data findable and accessible for research [for full text, please go to the a.m. URL]},
	language = {en},
	urldate = {2021-09-30},
	author = {Sax, Ulrich and Ortmann, Stefan and Gietzelt, Matthias and Kock-Schoppenhauer, Ann-Kristin and Schreiweis, Björn and Ertl, Maximilian and Sedlmayr, Martin and Kesztyues, Tibor and Eils, Roland and Krefting, Dagmar},
	month = sep,
	year = {2021},
	note = {Medium: text/html
Publisher: German Medical Science GMS Publishing House},
	keywords = {Architecture, Data Integration Center, FOS: Civil engineering, HiGHmed, Interoperability, Medicine and health},
}

@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},
	url = {https://dvmd.de/wp-content/uploads/2020/11/A-148.pdf},
	eventtitle = {16. {DVMD}-Fachtagung, Leipzig, 25. bis 26. Februar 2021},
	author = {Drenkhahn, Cora and Burmester, Sebastian and Ballout, Sarah and Ulrich, Hannes and Wiedekopf, Joshua and Ingenerf, Josef},
	year = {2020},
}

@inproceedings{drenkhahn_loinc_2020,
	title = {The {LOINC} {Content} {Model} and {Its} {Limitations} of {Usage} in the {Laboratory} {Domain}},
	volume = {270},
	doi = {10.3233/SHTI200198},
	abstract = {To unambiguously encode the semantic meaning of laboratory tests, the LOINC terminology is widely used. With regard to the constantly changing and diverse requirements of the laboratory domain, LOINC's long-established content model and related publications are reviewed conjointly, revealing some obstacles for flexible adaptation in terms of new or varying application needs as well as issues regarding the comprehensive reusability of lab data. In a concise overview, four specific limitations are identified that require adaptation or the usage of other terminologies.},
	language = {eng},
	booktitle = {Studies in {Health} {Technology} and {Informatics}},
	author = {Drenkhahn, Cora and Ingenerf, Josef},
	month = jun,
	year = {2020},
	pmid = {32570422},
	keywords = {Clinical Laboratory, Semantic Interoperability, Terminologies},
	pages = {437--442},
}

@article{rajput_standardizing_2020,
	title = {Standardizing the Unit of Measurements in {LOINC}-Coded Laboratory Tests Can Significantly Improve Semantic Interoperability},
	url = {https://ebooks.iospress.nl/doi/10.3233/SHTI200733},
	doi = {10.3233/SHTI200733},
	pages = {234--235},
	journaltitle = {Integrated Citizen Centered Digital Health and Social Care},
	author = {Rajput, Abdul Mateen and Ballout, Sarah and Drenkhahn, Cora},
	urldate = {2021-09-15},
	year = {2020},
	note = {Publisher: {IOS} Press},
}

@article{drenkhahn_referenzterminologie_2020,
	title = {Referenzterminologie {SNOMED} {CT}},
	pages = {81--84},
	number = {3},
	journaltitle = {medizin://dokumentation/informatik/informationsmanagement/ (mdi), {BVMI} und {DVMD}},
	author = {Drenkhahn, Cora M. and Ingenerf, Josef},
	year = {2020},
}

@inproceedings{banach_metacheck_2020,
	series = {Student {Conference} {Proceedings}},
	title = {{MetaCheck} – a {Web} {Application} for the {Automatic} {Evaluation} of {Metadata} in {Healthcare}},
	isbn = {978-3-945954-62-1},
	publisher = {Infinite Science Publishing},
	author = {Banach, Alexandra and Kock-Schoppenhauer, Ann Kristin and Ulrich, Hannes and Ingenerf, Josef},
	year = {2020},
	pages = {143--146}
}

@article{ablas_konzeption_2020,
	title = {Konzeption und {Implementierung} einer {Geräteschnittstelle} des {TECAN} {EVO} {Aliquotierroboter} im {Biobankkontext}},
	journal = {GMS Medizinische Informatik, Biometrie und Epidemiologie},
	author = {Ablaß, Torge and Ulrich, Hannes and Kock-Schoppenhauer, Ann-Kristin and Simon, Friedrich and Wagenzink, Stefanie and Maushagen, Regina and Habermann, Jens K. and Ingenerf, Josef},
	year = {2020},
}

@article{ulrich_smart_2020,
	title = {A Smart Mapping Editor for Standardised Data Transformation},
	volume = {270},
	issn = {1879-8365},
	doi = {10.3233/SHTI200354},
	abstract = {The integration of heterogeneous healthcare data sources is a necessary process to enable the secondary use valuable information in clinical research. Data integration is time-consuming for data stewards. The transformation using predefined rules for data harmonization can reduce the time-consuming and error-prone work and ease the data integration at various sites. In our study, we examined various script(ing) languages to find the most suitable candidate for definition of transformation rules and implement a smart editor which supports the data stewards in selecting rules reusing them. Thereby, it also provides an automatic and seamless documentation to strengthen the reliability of the defined transformation rules.},
	pages = {1185--1186},
	journaltitle = {Studies in Health Technology and Informatics},
	shortjournal = {Stud Health Technol Inform},
	author = {Ulrich, Hannes and Germer, Sebastian and Kock-Schoppenhauer, Ann-Kristin and Kern, Jori and Lablans, Martin and Ingenerf, Josef},
	date = {2020-06-16},
	pmid = {32570571},
	keywords = {Data Warehousing, Delivery of Health Care, Documentation, Electronic Health Records, {HL}7 {FHIR}, Health Information Interoperability, Health Level Seven, Reproducibility of Results},
}

@inproceedings{kath_connecting_2020,
	series = {Student {Conference} {Proceedings}},
	title = {Connecting {Old} {Devices} {Safely} {To} {The} {Cloud}},
	isbn = {978-3-945954-62-1},
	publisher = {Infinite Science Publishing},
	author = {Kath, Niclas and Seidel, Arne and Ingenerf, Josef},
	year = {2020},
	pages = {277--280}
}

@inproceedings{reimer_deploying_2020,
	title = {Deploying a molecular tumor board on an open platform},
	series = {Student Conference Proceedings},
	pages = {139--142},
	publisher = {Infinite Science Publishing},
	author = {Reimer, Niklas and Busch, Hauke and Ingenerf, Josef},
	year = {2020},
}

@inproceedings{barkow_analysis_2020,
	series = {Student {Conference} {Proceedings}},
	title = {Analysis of {Data} {Loss} when using the {Archiving} and {Exchange} {Interface} for {Practice} {Management} {Systems}},
	isbn = {978-3-945954-62-1},
	publisher = {Infinite Science Publishing},
	author = {Barkow, Linus and Meincke, Oliver and Ulrich, Hannes and Ingenerf, Josef},
	year = {2020},
	pages = {123--126}
}

@article{ulrich_analysis_2020,
	title = {Analysis of {ISO}/{TS} 21526 {Towards} the {Extension} of a {Standardized} {Query} {API}},
	volume = {275},
	issn = {1879-8365},
	doi = {10.3233/SHTI200723},
	abstract = {Metadata is often used for different tasks in the field of medical informatics: semantic description of data, quality validation, data integration, or information retrieval. Metadata definitions are captured and curated in time-consuming tasks and stored in metadata repositories that manage and preserve the metadata. Due to technical and legal restrictions, metadata is rarely as easily accessible and interoperable as it is necessary for modern information systems. In a previous study, a uniform interface based on the widely used ISO/IEC 11179 and the Facebook data retrieval language GraphQL was introduced as a solution to these technical obstacles. In the meantime, the ISO standard 21526 has been published, a recent version designed with a strong focus on health informatics. While it is conceptually oriented on the metamodel in ISO 11179, a number of extensions but also restructurings have been introduced. In this study, the authors investigated the difference between ISO 11179 and ISO 21526 and extended the unified metadata query interface to be future-proof and in particular, to support the semantic extensions of ISO 21526.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Ulrich, Hannes and Kock-Schoppenhauer, Ann-Kristin and Drenkhahn, Cora and Löbe, Matthias and Ingenerf, Josef},
	month = nov,
	year = {2020},
	pmid = {33227769},
	keywords = {GraphQL, ISO 11179, ISO 21526, Metadata, Metadata Repository},
	pages = {202--206},
}

@article {ulrich_ql4mdr,
	title = {QL4MDR: a GraphQL query language for ISO 11179-based metadata repositories},
        url = {https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-019-0794-z},
	journal = {BMC Medical Informatics and Decision Making},
	volume = {19},
	year = {2019},
	month = {03/2019},
	pages = {45},
	abstract = {Heterogeneous healthcare instance data can hardly be integrated without harmonizing its schema-level metadata. Many medical research projects and organizations use metadata repositories to edit, store and reuse data elements. However, existing metadata repositories differ regarding software implementation and have shortcomings when it comes to exchanging metadata. This work aims to define a uniform interface with a technical interlingua between the different MDR implementations in order to enable and facilitate the exchange of metadata, to query over distributed systems and to promote cooperation. To design a unified interface for multiple existing MDRs, a standardized data model must be agreed on. The ISO 11179 is an international standard for the representation of metadata, and since most MDR systems claim to be at least partially compliant, it is suitable for defining an interface thereupon. Therefore, each repository must be able to define which parts can be served and the interface must be able to handle highly linked data. GraphQL is a data access layer and defines query techniques designed to navigate easily through complex data structures.},
	issn = {1472-6947},
	doi = {10.1186/s12911-019-0794-z},
		author = {Ulrich, Hannes and Kern, Jori and Tas, Deniz and Kock-Schoppenhauer, Ann-Kristen and Ückert, Frank and Ingenerf, Josef and Lablans, Martin},

}

@misc{klaucke_b._medical_2019,
	address = {Luebeck},
	type = {Poster},
	title = {Medical {Informatics} in {Biobanks}: {Experiences} from an {Interdisciplinary} {Internship} from the {Student}'s {Side}},
	shorttitle = {Medical {Informatics} in {Biobanks}: {Experiences} from an {Interdisciplinary} {Internship} from the {Student}'s {Side}},
	url = {http://europebiobankweek.eu/wp-content/uploads/2019/10/EBW-2019-Abstract-Book-Poster-Presentations-20191007.pdf},
	abstract = {Background
Students choose to study Medical Informatics because it is scientifically oriented and at the same time practicerelated. The tasks in the research field between medicine and computer science serve to further improve medical care and patient treatment in the future.
Methods
The practical course in the master's program can be done in research institutions or companies in Germany
or abroad. This internship lasts six months and is carried out at the IT Center for Clinical Research, Lübeck in close cooperation with the Interdisciplinary Center for Biobanking-Lübeck at the campus.
Results
During the internship two main areas of the clinical infrastructure, biobanking and study administration can
be explored. In the laboratory of ICB-L collecting, processing and storage of samples are demonstrated,
especially the different automated storage systems. Regarding the samples, the cut of tissue samples is
examined in the pathology. Getting to know these biobank relevant processes is particularly instructive to
transfer them to mobile sample documentation. In the field of study management different approaches for
automated study recruitment on the basis of inclusion and exclusion criteria were evaluated.
Discussion
The practical course had a positive influence on my professional and personal development. In particular, the interaction with other international interns of other disciplines was very educational. I think the internship is a good preparation for my future professional life. The wideranging ethical and data protection requirements were both a challenge and an opportunity.},
	language = {English},
	author = {{Klaucke, B.}},
	collaborator = {{Kock-Schoppenhauer, A.K.} and {Simon, F.} and {Wagenzink, S.} and {Fkiri, H.} and {Maushagen, R.} and {Figge, L.} and {Flügge,F.} and {Habermann, J.K.} and {Ingenerf, J.} and {DuhmHarbeck, P.}},
	month = oct,
	year = {2019},
	keywords = {EBW}
}

@article{ulrich_towards_2019,
	title = {Towards a {Federation} of {Metadata} {Repositories}: {Addressing} {Technical} {Interoperability}},
	volume = {253},
	issn = {0926-9630},
	abstract = {Secondary use of routinely collected data is more and more promoted by the utilization of metadata repositories. However, this has not yet solved the problem of data exchange across organizational boundaries. The local description of a metadata set must also be exchangeable for flawless data exchange. In previous work a metadata exchange language QL4MDR was developed. The aim of this work was to examine the applicability of this exchange language. For this purpose, existing MDR implementations were identified and systematically inspected. Roughly divided into two categories to distinguish between data integration and query integration. It has been shown that all the implementations can be adapted to QL4MDR. The integration of metadata is an important first step; it enables the exchange of information, which is so urgently needed for the further processing of instance data, from the metadata mappings to the transformation regulations.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Ulrich, Hannes and Kern, Jori and Kock-Schoppenhauer, Ann-Kristin and Lablans, Martin and Ingenerf, Josef},
	year = {2019},
	pmid = {30147040},
	keywords = {Algorithms, Databases, Factual, Federation, GraphQL, Metadata, Metadata repository, Neo4j, QL4MDR, Statistics as Topic, graph database},
	pages = {55--59}
}

@article{andersen_service-oriented_2019,
	title = {Service-{Oriented} {Device} {Connectivity}: {Device} {Specialisations} for {Interoperability}},
	volume = {264},
	issn = {1879-8365},
	shorttitle = {Service-{Oriented} {Device} {Connectivity}},
	doi = {10.3233/SHTI190274},
	abstract = {There are IEEE 11073 standards for foundational, structural, and semantic point-of-care medical device interoperability, but the first devices with this interface have yet to enter the market. One of the missing pieces for implementation and approval are Device Specialisations that specify how to use information and service models to represent a specific type of device on the network. Required and optional metrics need to be standardised as well as nomenclature terms, units of measure, and extension points. Finally, device-to-device interaction at runtime has to be defined for automatic verification during testing and approval. Applications include C-arm fluoroscopes used in different clinical settings.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Andersen, Björn and Baumhof, Simon and Ingenerf, Josef},
	year = {2019},
	pmid = {31437975},
	keywords = {Computer Communication Networks, Health Information Interoperability, Reference Standards},
	pages = {509--511}
}

@article{kock-schoppenhauer_scientific_2019,
	title = {Scientific {Challenge} in {eHealth}: {MAPPATHON}, a {Metadata} {Mapping} {Challenge}},
	volume = {264},
	issn = {1879-8365},
	shorttitle = {Scientific {Challenge} in {eHealth}},
	doi = {10.3233/SHTI190512},
	abstract = {Scientific challenges based on benchmark data enable the comparison and evaluation of different algorithms and take place regularly in scientific disciplines like medical image processing, text mining or genetics. The idea of a challenge is rarely applied within the eHealth community. Mappathon is a metadata mapping challenge that asks for methods to find corresponding data elements within similar datasets and to correlate data elements among each other.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Kock-Schoppenhauer, Ann-Kristin and Bruland, Philipp and Kadioglu, Dennis and Brammen, Dominik and Ulrich, Hannes and Kulbe, Kerstin and Duhm-Harbeck, Petra and Ingenerf, Josef},
	year = {2019},
	pmid = {31438209},
	keywords = {Algorithms, Benchmarking, Data Mining, Image Processing, Computer-Assisted, Metadata, Telemedicine},
	pages = {1516--1517}
}

@article{deppenwiese_mdrcupid:_2019,
	title = {{MDRCupid}: {A} {Configurable} {Metadata} {Matching} {Toolbox}.},
	volume = {264},
	journal = {Studies in health technology and informatics},
	author = {Deppenwiese, Noemi and Duhm-Harbeck, Petra and Ingenerf, Josef and Ulrich, Hannes},
	year = {2019},
	keywords = {Algorithms, Data Curation, Delivery of Health Care, Health Information Interoperability, Metadata},
	pages = {88--92}
}

@misc{simon_f._illustrating_2019,
	address = {Luebeck},
	type = {Poster},
	title = {Illustrating the {Sample} {Life} {Cycle} at an {Hospital} {Integrated} {Biobank}},
	shorttitle = {Illustrating the {Sample} {Life} {Cycle} at an {Hospital} {Integrated} {Biobank}},
	url = {http://europebiobankweek.eu/wp-content/uploads/2019/10/EBW-2019-Abstract-Book-Poster-Presentations-20191007.pdf},
	abstract = {Background
Biobanks collect high-quality biological material, donorspecific data, and sociodemographic information about the donor. Sample-specific data such as sampling time, processing conditions or sample location should all be documented in a Biobank Management System. The hospital-integrated biobank ICB-L uses the software CentraXX from KAIROS ® to enable sample and data management.
Methods
To proof the quality of processing and storage, we developed a sample-life-cycle BIRT-report (Business
Intelligence and Reporting Tools) and made it available in CentraXX. This analysis contains information about donors, medical-conditions, acquisition and storage. With the distribution of the sample the monitoring process ends. results All information is processed at the individual sample level from sampling to storage. Temperature has a major influence on sample quality, which is why the analysis of sample storage has a special focus. Taking into account the temperature logs supplied by the trackers, a temperature curve is drawn on the box/rack level. Special events such as the opening of the box, e.g. for the storage of new samples or removal of samples, are projected. Repositioning of the box within the nitrogen tank is timed as well as the position inside the box. discussion The quality can only
be guaranteed over a long period if the samples are stored properly. Freezing and thawing cycles,
unintentional temperature changes and exposure to air and other substances can have unintentional
consequences. The report is a tool to visualize and summarize all available data. The data was queried and
analyzed from two databases and more than 50 tables.},
	language = {English},
	author = {{Simon, F.}},
	collaborator = {{Kock-Schoppenhauer, A.K.} and {Wagenzink, S.} and {Maushagen, R.} and {Figge, L.} and {Flügge, F.} and {Habermann, J.K.} and {Duhm-Harbeck, P.}},
	month = oct,
	year = {2019},
	keywords = {EBW}
}

@inproceedings{wiedekopf_human_2019,
	address = {Lübeck},
	title = {Human {Readable} {Data} {Export} of {Medical} {Documentation}},
	isbn = {978-3-945954-57-7},
	booktitle = {Student {Conference} 2019, {Medical} {Engineering} {Science}, {Medical} {Informatics}, {Biomedical} {Engineering} and {Auditory} {Technology}},
	publisher = {Infinite Science Publishing},
	author = {Wiedekopf, Joshua and Becker, Tim and Ingenerf, Josef},
	editor = {Buzug, Thorsten M. and Handels, Heinz and Klein, Stephan and Mertins, Alfred},
	year = {2019},
	note = {Backup Publisher: Infinite Science Publishing},
	pages = {277--280},
}

@misc{kock-schoppenhauer_generic_2019,
	address = {Lübeck},
	type = {Vortrag},
	title = {Generic {Test} {Protocol} for the {Integration} {Test} of {Automated} {Storage} {Systems} on {Rack} or {Tube} {Level}},
	author = {Kock-Schoppenhauer, Ann-Kristin},
	collaborator = {Wagenzink, Stefanie and Stüdemann, Maj Kristin and Figge, Lena and Flügge, Friedemann and Simon, Friedrich and Maushagen, Regina and Habermann, Jens K. and Duhm-Harbeck, Petra},
	year = {2019}
}

@article{kasparick_enabling_2019,
	title = {Enabling artificial intelligence in high acuity medical environments},
	volume = {28},
	issn = {1365-2931},
	doi = {10.1080/13645706.2019.1599957},
	abstract = {Acute patient treatment can heavily profit from AI-based assistive and decision support systems, in terms of improved patient outcome as well as increased efficiency. Yet, only very few applications have been reported because of the limited accessibility of device data due to the lack of adoption of open standards, and the complexity of regulatory/approval requirements for AI-based systems. The fragmentation of data, still being stored in isolated silos, results in limited accessibility for AI in healthcare and machine learning is complicated by the loss of semantics in data conversions. We outline a reference model that addresses the requirements of innovative AI-based research systems as well as the clinical reality. The integration of networked medical devices and Clinical Repositories based on open standards, such as IEEE 11073 SDC and HL7 FHIR, will foster novel assistance and decision support. The reference model will make point-of-care device data available for AI-based approaches. Semantic interoperability between Clinical and Research Repositories will allow correlating patient data, device data, and the patient outcome. Thus, complete workflows in high acuity environments can be analysed. Open semantic interoperability will enable the improvement of patient outcome and the increase of efficiency on a large scale and across clinical applications.},
	language = {eng},
	number = {2},
	journal = {Minimally invasive therapy \& allied technologies: MITAT: official journal of the Society for Minimally Invasive Therapy},
	author = {Kasparick, Martin and Andersen, Björn and Franke, Stefan and Rockstroh, Max and Golatowski, Frank and Timmermann, Dirk and Ingenerf, Josef and Neumuth, Thomas},
	year = {2019},
	pmid = {30950665},
	keywords = {Artificial Intelligence, Context-aware medical technology, Critical Care, Decision Support Systems, Clinical, Efficiency, Organizational, HL7 FHIR, Humans, IEEE 11073 SDC, Surgical Procedures, Operative, Workflow, big data, surgery},
	pages = {120--126}
}

@misc{wagenzink_s._central_2019,
	address = {Luebeck},
	type = {Poster},
	title = {Central {Acquisition} and {Visualization} of {Temperature} {Logs} of {Various} {Biobank} {Storage} {Systems}},
	shorttitle = {Central {Acquisition} and {Visualization} of {Temperature} {Logs} of {Various} {Biobank} {Storage} {Systems}},
	url = {http://europebiobankweek.eu/wp-content/uploads/2019/10/EBW-2019-Abstract-Book-Poster-Presentations-20191007.pdf},
	abstract = {Background
Quality-assured biobanks are obliged to keep a complete sample documentation. The appropriate storage temperature is particularly responsible for the sample quality. Storage systems either have internal temperature recording or are equipped with such systems. Having this information available in a uniform format and in one place facilitates overview and access.
Methods
In this project, the -80°C Thermo Fisher freezers, the automated storage systems HS200 from Askion and BIO Store III from Brooks and the conventional tanks using TTracker are taken into account by ICB-L. This selection results in four different temperature measurement systems and different formats, which need to be harmonized.
Results
Not all storage systems have a direct connection to the network of the biobank software, they have to be read and transferred manually. We have developed an interface that reads the formats and transfers the specific xml format. All temperature logs of these devices are then stored as measurement series in the BIMS and can be used for further analysis. Errors and other logging system specific events are stored and considered separately. An automated analysis of the temperature data, over the different systems becomes now even possible.
Discussion
We can continuously retrieve and use the logs of the automated systems to identify deviations and promote an early reaction. But also the non-automated storage systems can be better controlled by automatic instead of manual verification. This specific information can then be used to calculate curves on single tube level.},
	language = {English},
	author = {{Wagenzink, S.}},
	collaborator = {{Kock-Schoppenhauer, A.K.} and {Simon, F.} and {Maushagen, R.} and {Figge, L.} and {Flügge, F.} and {Habermann, J.K.} and {Duhm-Harbeck, P.}},
	month = oct,
	year = {2019},
	keywords = {EBW}
}

@article{drenkhahn_aggregation_2019,
	title = {Aggregation and {Visualization} of {Laboratory} {Data} by {Using} {Ontological} {Tools} {Based} on {LOINC} and {SNOMED} {CT}},
	volume = {264},
	issn = {1879-8365},
	doi = {10.3233/SHTI190193},
	abstract = {With the proliferation of digital communication in healthcare, the reuse of laboratory test data entails valuable insights into clinical and scientific issues, basically enabled by semantic standardization using the LOINC coding system. In order to extend the currently limited potential for analysis, which is mainly caused by structural peculiarities of LOINC, an algorithmic transformation of relevant content into an OWL ontology was performed, which includes LOINC Terms, Parts and Hierarchies. For extending analysis capabilities, the comprehensive SNOMED CT ontology is added by transferring its contents and the recently published LOINC-related mapping data into OWL ontologies. These formalizations offer rich, computer-processable content and allow to infer additional structures and relationships, especially when used together. Consequently, various reutilizations are facilitated; an application demonstrating the dynamic visualization of fractional hierarchy structures for user-supplied laboratory data was already implemented. By providing element-wise aggregation via superclasses, an adaptable, graph representation is obtained for studying categorizations.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Drenkhahn, Cora and Duhm-Harbeck, Petra and Ingenerf, Josef},
	year = {2019},
	pmid = {31437895},
	keywords = {Biomedical Ontologies, Computers, LOINC, Logical Observation Identifiers Names and Codes, SNOMED CT, Semantics, Systematized Nomenclature of Medicine},
	pages = {108--112}
}

@article{ververs_konvertierung_2018,
	title = {Konvertierung von {MIMIC}-{III}-{Daten} zu {FHIR}},
	url = {http://www.egms.de/en/meetings/gmds2018/18gmds018.shtml},
	doi = {10.3205/18gmds018},
	abstract = {Einleitung: Die Medical Information Mart for Intensive Care (MIMIC-III) [ref:1] ist eine für akademische Zwecke frei verfügbare Datenbank mit klinischen Patientendaten aus vorwiegend intensivmedizinischen Fällen und umfasst ca. 59000 Aufenthalte von ca. 46000 Patienten. Zu diesen[zum vollständigen Text gelangen Sie über die oben angegebene URL]},
	language = {de},
	urldate = {2018-11-20},
	journal = {63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)},
	author = {Ververs, Stefanie and Ulrich, Hannes and Kock, Ann-Kristin and Ingenerf, Josef},
	editor = {Deutsche Gesellschaft Für Medizinische Informatik, Biometrie Und Epidemiologie},
	month = aug,
	year = {2018}
}

@article{ulrich_using_2018,
	title = {Using {Graph} {Tools} on {Metadata} {Repositories}},
	volume = {253},
	issn = {1879-8365},
	abstract = {To exchange data across several sites or to interpret it at a later point in time, it is necessary to create a general understanding of the data. As a standard practice, this understanding is achieved through metadata. These metadata are usually stored in relational databases, so-called metadata repositories (MDR). Typical functions of such an MDR include pure storage, administration and other specific metadata functionalities such as finding relations among data elements. This results in a multitude of connections between the data elements, which can be described as highly interconnected graphs. To use alternative databases such as graph databases for modelling and visualisation it has already been proven to be beneficial in previous studies. The objective of this work is to evaluate how on-board techniques rely on matching and mapping using a graph database. Different datasets relating to cancer were entered, and algorithms for metadata management were applied.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Ulrich, Hannes and Kock-Schoppenhauer, Ann-Kristin and Duhm-Harbeck, Petra and Ingenerf, Josef},
	year = {2018},
	pmid = {30147040},
	keywords = {Algorithms, Databases, Factual, graph database, Metadata, Metadata repository, Neo4j, Statistics as Topic},
	pages = {55--59}
}

@techreport{bruland_secondary_nodate,
	address = {MIE 2018, Gothenburg},
	type = {accepted as {Workshop}},
	title = {Secondary use of {Routinely} {Collected} {Healthcare} {Data} for {Multiple} {Purposes} – {Experiences} and {Obstacles}},
	author = {Bruland, Philipp and Kock-Schoppenhauer, Ann-Kristin and Kadioglu, Dennis}
}

@article{kock-schoppenhauer_practical_2018,
	title = {Practical {Extension} of {Provenance} to {Healthcare} {Data} {Based} on the {W}3C {PROV} {Standard}},
	volume = {253},
	issn = {0926-9630},
	abstract = {Secondary use of healthcare data is dependent on the availability of provenance data for assessing its quality, reliability or trustworthiness. Usually, instance-level data that might be communicated by HL7 interfaces entail limited metadata about involved software systems, persons or organizations bearing responsibility for those systems. This paper proposes a strategy for capturing interoperable provenance data needed by data stewards for assessing healthcare data that are reused in a research context. Aimed at a realistic level of granularity even system-level metadata will support a data steward trying to trace the origins or provenance of healthcare data that have been transferred to the research context. Those metadata are extracted from the 3LGM2-system, used for modelling hospital information systems. Based on the W3C provenance specification interrelated activities, entities and agents can be integrated and stored in RDF triple stores and therefore queried and visualized.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Kock-Schoppenhauer, Ann-Kristin and Hartung, Lina and Ulrich, Hannes and Duhm-Harbeck, Petra and Ingenerf, Josef},
	year = {2018},
	pmid = {30147034},
	keywords = {Metadata, Software, Delivery of Health Care, Reproducibility of Results, interoperable provenance data, Secondary use of EHR data, Statistics as Topic},
	pages = {28--32}
}

@techreport{ulrich_modelling_nodate,
	address = {MIE 2018, Gothenburg},
	type = {accepted as {Short} {Communication}},
	title = {Modelling a {Metadata} {Repository} in a {Graph} {Database} using {Neo}4j},
	author = {Ulrich, Hannes and Kock-Schoppenhauer, Ann-Kristin and Duhm-Harbeck, Petra and Ingenerf, Josef}
}

@inproceedings{drenkhahn_mapping_2018,
	series = {Student {Conference} {Proceedings}},
	title = {Mapping of {Laboratory} {Services} included in an {Internal} {Catalog} to {SNOMED} {CT} using the {UMLS}},
	isbn = {978-3-945954-47-8},
	abstract = {The contributions to this proceedings book show how new approaches and methods in medical engineering and medical informatics can advance medicine, health and health care. The papers focus on the following topics: Medical Image Processing, Medical Imaging, Signal Processing, Biomedical Optics, Biochemical Physics, Safety and Quality, E-Health.},
	language = {English},
	booktitle = {Student {Conference} {Proceedings} 2018: 7th {Conference} on {Medical} {Engineering} {Science} and 3rd {Conference} on {Medical} {Informatics} and 1st {Conference} on {Biomediacal} {Engineering}},
	publisher = {Infinite Science Publishing},
	author = {Drenkhahn, Cora and Ulrich, Hannes and Ingenerf, Josef and Duhm-Harbeck, Petra},
	editor = {Buzug, Thorsten and Handels, Heinz and Klein, Stephan},
	year = {2018},
	pages = {337--340}
}

@techreport{kock-schoppenhauer_mappathon_2018,
	address = {63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)},
	title = {Mappathon – {A} {Metadata} {Mapping} {Challenge} for {Secondary} {Use}},
	url = {https://www.mappathon.de},
	author = {Kock-Schoppenhauer, Ann-Kristin and Bruland, Philipp and Kadioglu, Dennis},
	month = sep,
	year = {2018}
}

@article{neumann_entwicklung_2018,
	title = {Entwicklung eines generischen {Modells} zur {Abbildung} von {Studienzentralen} in {CentraXX}},
	url = {http://www.egms.de/en/meetings/gmds2018/18gmds003.shtml},
	doi = {10.3205/18gmds003},
	abstract = {Einleitung: Klinische Studien sind für den Fortschritt in der Medizin unabdingbar. Studien können beispielsweise Teil des Entwicklungsplans eines Arzneimittels (AMG-Studie) oder Medizinproduktes (MPG-Studie) sein oder untersuchen andere Therapien [ref:1]. Die Verwaltung und Durchführung[zum vollständigen Text gelangen Sie über die oben angegebene URL]},
	language = {de},
	urldate = {2018-11-20},
	journal = {63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)},
	author = {Neumann, Anke and Kock, Ann-Kristin and Simon, Friedrich and Wagenzink, Stefanie and Nohr, Manuela and Jürgens, Martin and Milinski, Rita and Holler, Ursula and Habermann, Jens K. and Duhm-Harbeck, Petra and Ingenerf, Josef},
	editor = {Deutsche Gesellschaft Für Medizinische Informatik, Biometrie Und Epidemiologie},
	month = aug,
	year = {2018},
	keywords = {Medizinische Informatik},
	file = {Snapshot:C\:\\Users\\Ann-Kristin Kock\\Zotero\\storage\\B34VPNQ5\\18gmds003.html:text/html}
}

@techreport{kock-schoppenhauer_integrating_nodate,
	address = {MIE 2018, Gothenburg},
	type = {accepted as {Poster}},
	title = {Integrating {Instance}- and {Systemlevel} {Provenance} {Data} for {Supporting} {Secondary} {Use} of {Healthcare} {Data}},
	author = {Kock-Schoppenhauer, Ann-Kristin and Hartung, Lisa and Ulrich, Hannes and Duhm-Harbeck, Petra and Ingenerf, Josef}
}

@article{simon_aufbau_2018,
	title = {Aufbau eines campusweiten {Studienregisters} harmonisiert aus {DRKS}, {ClinicalTrails}.gov und {EU} {Clinical} {Trials} {Register}},
	url = {http://www.egms.de/en/meetings/gmds2018/18gmds001.shtml},
	doi = {10.3205/18gmds001},
	abstract = {Einleitung: Ein Studienregister ermöglicht einen aktuellen und nutzerorientierten Überblick über laufende und abgeschlossene Studien. Die frei verfügbaren Informationen in den nationalen und internationalen Studienregistern unterstützen die Transparenz in der medizinischen Forschung.[zum vollständigen Text gelangen Sie über die oben angegebene URL]},
	language = {de},
	urldate = {2018-11-20},
	journal = {63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)},
	author = {Simon, Friedrich and Kock, Ann-Kristin and Neumann, Anke and Wagenzink, Stefanie and Nohr, Manuela and Jürgens, Martin and Milinski, Rita and Holler, Ursula and Habermann, Jens K. and Ingenerf, Josef and Duhm-Harbeck, Petra},
	editor = {Deutsche Gesellschaft Für Medizinische Informatik, Biometrie Und Epidemiologie},
	month = aug,
	year = {2018}
}

@techreport{kock-schoppenhauer_data_2018,
	address = {Nationales Biobanken-Symposium Moderne Biobanken – fit for purpose!},
	title = {Data {Quality} {Analysis} for {Biobanks}},
	author = {Kock-Schoppenhauer, Ann-Kristin and Simon, Friedrich and Maushagen, Regina and Oberländer, Martina and Figge, Lena and Habermann, Jens K. and Duhm-Harbeck, Petra},
	year = {2018}
}

@article{kern_method_2018,
	title = {A {Method} to use {Metadata} in legacy {Web} {Applications}: {The} {Samply}.{MDR}.{Injector}},
	abstract = {Whenever medical data is integrated from multiple sources, it is regarded good practice to separate data from information about its meaning, such as designations, definitions or permissible values (in short: metadata). However, the ways in which applications work with metadata are imperfect: Many applications do not support fetching metadata from externalized sources such as metadata repositories. In order to display human-readable metadata in any application, we propose not to change the application, but to provide a library that makes a change to the user interface. The goal of this work is to provide a way to “inject” the meaning of metadata keys into the web-based frontend of an application to make it “metadata aware”.},
	journal = {Stud Health Technol Inform},
	author = {Kern, Jori and Tas, Deniz and Ulrich, Hannes and Schmidt, Esther Erika and Ingenerf, Josef and Ückert, Frank and Lablans, Martin},
	year = {2018}
}

@techreport{kock-schoppenhauer_new_2018,
	address = {Global Biobank Week 2018, Antwerpen},
	title = {New {Data} {Quality} {BIRT}-{Reports} for {Biobanks}},
	author = {Kock-Schoppenhauer, Ann-Kristin and Simon, Friedrich and Wagenzink, Stefanie and Maushagen, Regina and Oberländer, Martina and Figge, Lena and Duhm-Harbeck, Petra and Habermann, Jens K.},
	year = {2018}
}

@techreport{kock-schoppenhauer_ccdc_2018,
	address = {Global Biobank Week 2018, Antwerpen},
	title = {{CCDC} {Data} {Provision} in the {Context} of {BBMRI}-{ERIC} {ADOPT} {CRC}-{Cohort}},
	author = {Kock-Schoppenhauer, Ann-Kristin and Wagenzink, Stefanie and Böckmann, Lars and Krampitz, Anna and Simon, Friedrich and Duhm-Harbeck, Petra and Habermann, Jens K.},
	year = {2018}
}

@article{kock-schoppenhauer_compatibility_2018,
	title = {Compatibility {Between} {Metadata} {Standards}: {Import} {Pipeline} of {CDISC} {ODM} to the {Samply}.{MDR}},
	volume = {247},
	issn = {0926-9630},
	abstract = {The establishment of a digital healthcare system is a national and community task. The Federal Ministry of Education and Research in Germany is providing funding for consortia consisting of university hospitals among others participating in the "Medical Informatics Initiative". Exchange of medical data between research institutions necessitates a place where meta information for this data is made accessible. Within these consortia different metadata registry solutions were chosen. To promote interoperability between these solutions, we have examined whether the portal of Medical Data Models is eligible for managing and communicating metadata and relevant information across different data integration centres of the Medical Informatics Initiative and beyond. Apart from the MDM-portal, some ISO 11179-based systems such as Samply.MDR as well as openEHR-based solutions are going to be applyed. In this paper, we have focused on the creation of a mapping model between the CDISC ODM standard and the Samply.MDR import format. In summary, it can be stated that the mapping model is feasible and promote the exchangeability between different metadata registry approaches.},
	language = {eng},
	journal = {Studies in health technology and informatics},
	author = {Kock-Schoppenhauer, Ann-Kristin and Ulrich, Hannes and Wagenzink, Stefanie and Duhm-Harbeck, Petra and Ingenerf, Josef and Neuhaus, Philipp and Dugas, Martin and Bruland, Philipp},
	year = {2018},
	keywords = {Metadata, Humans, Biomedical Research, Germany, Metadata/standards, Reference Standards, Registries, CDISC ODM, data elements, mapping, MDR, metadata registry},
	pages = {221--225}
}

@article{andersen_connecting_2018,
	title = {Connecting the clinical {IT} infrastructure to a service-oriented architecture of medical devices},
	volume = {63},
	issn = {0013-5585},
	doi = {10.1515/bmt-2017-0021},
	abstract = {The new medical device communication protocol known as IEEE 11073 SDC is well-suited for the integration of (surgical) point-of-care devices, so are the established Health Level Seven (HL7) V2 and Digital Imaging and Communications in Medicine (DICOM) standards for the communication of systems in the clinical IT infrastructure (CITI). An integrated operating room (OR) and other integrated clinical environments, however, need interoperability between both domains to fully unfold their potential for improving the quality of care as well as clinical workflows. This work thus presents concepts for the propagation of clinical and administrative data to medical devices, physiologic measurements and device parameters to clinical IT systems, as well as image and multimedia content in both directions. Prototypical implementations of the derived components have proven to integrate well with systems of networked medical devices and with the CITI, effectively connecting these heterogeneous domains. Our qualitative evaluation indicates that the interoperability concepts are suitable to be integrated into clinical workflows and are expected to benefit patients and clinicians alike. The upcoming HL7 Fast Healthcare Interoperability Resources (FHIR) communication standard will likely change the domain of clinical IT significantly. A straightforward mapping to its resource model thus ensures the tenability of these concepts despite a foreseeable change in demand and requirements.},
	language = {English},
	number = {1},
	journal = {Biomedizinische Technik},
	author = {Andersen, Björn and Kasparick, Martin and Ulrich, Hannes and Franke, Stefan and Schlamelcher, Jan and Rockstroh, Max and Ingenerf, Josef},
	year = {2018},
	pages = {57--68}
}

@techreport{lablans_it_nodate,
	address = {Stockholm},
	type = {Poster},
	title = {An {IT} {Architecture} for {Federated} {Biobanking} in {Germany}},
	author = {Lablans, Martin and Döllinger, Christoph and Duhm-Harbeck, Petra and Ebert, Lars and Habermann, Jens K. and Illig, Thomas and Ingenerf, Josef and Kadioglu, Dennis and Kern, Jori and Kiel, Alexander}
}

@article{ulrich_analysis_2017,
	title = {Analysis of {Annotated} {Data} {Models} for {Improving} {Data} {Quality}},
	volume = {243},
	issn = {0926-9630},
	abstract = {The public Medical Data Models (MDM) portal with more than 9.000 annotated forms from clinical trials and other sources provides many research opportunities for the medical informatics community. It is mainly used to address the problem of heterogeneity by searching, mediating, reusing, and assessing data models, e. g. the semi-interactive curation of core data records in a special domain. Furthermore, it can be used as a benchmark for evaluating algorithms that create, transform, annotate, and analyse structured patient data. Using CDISC ODM for syntactically representing all data models in the MDM portal, there are semi-automatically added UMLS CUIs at several ODM levels like ItemGroupDef, ItemDef, or CodeList item. This can improve the interpretability and processability of the received information, but only if the coded information is correct and reliable. This raises the question how to assure that semantically similar datasets are also processed and classified similarly. In this work, a (semi-)automatic approach to analyse and assess items, questions, and data elements in clinical studies is described. The approach uses a hybrid evaluation process to rate and propose semantic annotations for under-specified trial items. The evaluation algorithm operates with the commonly used NLM MetaMap to provide UMLS support and corpus-based proposal algorithms to link datasets from the provided CDISC ODM item pool.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Ulrich, Hannes and Kock-Schoppenhauer, Ann-Kristin and Andersen, Björn and Ingenerf, Josef},
	year = {2017},
	pmid = {28883198},
	keywords = {Humans, Electronic Health Records, Semantics, Algorithms, CDISC ODM, Data Accuracy, Medical Informatics, Natural Language Processing, Semantic Interoperability, UMLS},
	pages = {190--194}
}

@article{maushagen_cross-border_2017,
	title = {Cross-border biobanking: {The} {German}-{Danish} {Interreg} project {BONEBANK}},
	shorttitle = {Cross-border biobanking},
	url = {https://portal.findresearcher.sdu.dk/en/publications/cross-border-biobanking-the-german-danish-interreg-project-boneba},
	language = {English},
	urldate = {2019-02-13},
	author = {Maushagen, Regina and Gemoll, Timo and Oberlaender, Martina and Faccinetti, Giulia and Figge, Lena and Kock-Schoppenhauer, Ann-Kristin and Duhm-Harbeck, Petra and Niessen, Lina and Unger, Andreas and Waizner, Klaus and Wendlandt, Robert and Zweig, Wiebke and Kowal, Justyna M. and Haakonsson, Anders and Bober, Christina and Diercks, Kai and Nassutt, Roman and Buescher, Robin and Reimers, Nils and Schmal, Hagen and Duckert, Ralf and Kroeger, Ines and Stueck, Gesine and Kessel, Stefanie and Hecht, Mirjam and Frahm, Thomas and Eckers, Anna and Brilling, Julia and Barington, Torben and Kassem, Moustapha and Schulz, Arndt-Peter and Habermann, Jens K.},
	year = {2017},
	file = {Snapshot:C\:\\Users\\Ann-Kristin Kock\\Zotero\\storage\\D95Z922L\\cross-border-biobanking-the-german-danish-interreg-project-boneba.html:text/html}
}

@inproceedings{deppenwiese_entwicklung_2017,
	address = {Oldenburg},
	title = {Entwicklung eines {Tools} zum {Konvertieren} von {HL}7 {FHIR} {Questionnaires} in das {MOLGENIS} {EMX} {Format}},
	url = {https://www.egms.de/static/en/meetings/gmds2017/17gmds148.shtml},
	doi = {10.3205/17gmds148},
	booktitle = {62. {Jahrestagung} der {Deutschen} {Gesellschaft} für {Medizinische} {Informatik}, {Biometrie} und {Epidemiologie} e.{V}. ({GMDS})},
	publisher = {German Medical Science GMS Publishing House},
	author = {Deppenwiese, Noemi and Hannes, Ulrich and Wrage, Jan-Hinrich and Kock, Ann-Kristin and Ingenerf, Josef},
	year = {2017}
}

@techreport{kock-schoppenhauer_increasing_2017,
	address = {Stockholm},
	type = {poster},
	title = {Increasing {Standardization} of {Biobank} {Data} through {HL}7 {FHIR} {Mapping}},
	author = {Kock-Schoppenhauer, Ann-Kristen and Ulrich, Hannes and Duhm-Harbeck, Petra and Habermann, Jens K. and Ingenerf, Josef},
	year = {2017}
}

@techreport{neumann_konzept_nodate,
	address = {Berlin},
	type = {Poster},
	title = {Konzept eines lokalen regelbasierten {Antwortsystems} zur automatischen {Anfrage}-{Prüfung} in {Biobanken}},
	author = {Neumann and Ulrich, Hannes and Linde, John and Lablans, Martin and Döllinger, Christoph and Duhm-Harbeck, Petra and Ebert, Lars and Habermann, Jens K. and Illig, Thomas and Ingenerf, Josef and Kern, Jori and Kiel, Alexander and Knell, Christian and Kock, Ann-Kristin and Maier and Mate, Sebastian and Popp and Proynova and Rambow, Matt and Rufenach and Sahr and Schmidt and Schüttler, Christina and Seelke and Prokosch, Ulrich and Ückert and Hummel, Michael}
}

@article{kock-schoppenhauer_linked_2017,
	title = {Linked {Data} {Applications} {Through} {Ontology} {Based} {Data} {Access} in {Clinical} {Research}},
	volume = {235},
	issn = {0926-9630},
	abstract = {Clinical care and research data are widely dispersed in isolated systems based on heterogeneous data models. Biomedicine predominantly makes use of connected datasets based on the Semantic Web paradigm. Initiatives like Bio2RDF created Resource Description Framework (RDF) versions of Omics resources, enabling sophisticated Linked Data applications. In contrast, electronic healthcare records (EHR) data are generated and processed in diverse clinical subsystems within hospital information systems (HIS). Usually, each of them utilizes a relational database system with a different proprietary schema. Semantic integration and access to the data is hardly possible. This paper describes ways of using Ontology Based Data Access (OBDA) for bridging the semantic gap between existing raw data and user-oriented views supported by ontology-based queries. Based on mappings between entities of data schemas and ontologies data can be made available as materialized or virtualized RDF triples ready for querying and processing. Our experiments based on CentraXX for biobank and study management demonstrate the advantages of abstracting away from low level details and semantic mediation. Furthermore, it becomes clear that using a professional platform for Linked Data applications is recommended due to the inherent complexity, the inconvenience to confront end users with SPARQL, and scalability and performance issues.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Kock-Schoppenhauer, Ann-Kristin and Kamann, Christian and Ulrich, Hannes and Duhm-Harbeck, Petra and Ingenerf, Josef},
	year = {2017},
	pmid = {28423769},
	keywords = {Electronic Health Records, Internet, Semantics, Biomedical Research, Biological Ontologies, Information Storage and Retrieval, Linked Data, Semantic Querying and Data Integration, Semantic Web},
	pages = {131--135}
}

@techreport{neumann_it_nodate,
	title = {The {IT} {Architecture} of the {German} {Biobank} {Alliance} ({GBA})},
	author = {Neumann and Lablans and Döllinger and Duhm-Harbeck and Ebert and Habermann and Hummel and Illig and Ingenerf and Kadioglu and Kern and Kiel and Knell and Kock and Linde and Maier and Mate and Popp and Proynova and Rambow and Rufenach and Sahr and Schmidt and Schüttler and Ulrich and Prokosch and Ückert}
}

@misc{baake_creating_2017,
	title = {Creating {Reports} with {BIRT} to support the {Development} {Process} of {Medical} {Software}},
	author = {Baake, Merle},
	year = {2017},
	file = {Publikationen | Institute of Medical Informatics:C\:\\Users\\Ann-Kristin Kock\\Zotero\\storage\\GNQU4WSC\\biblio.html:text/html}
}

@article{ulrich_metadata_2016,
	title = {Metadata {Repository} for {Improved} {Data} {Sharing} and {Reuse} {Based} on {HL}7 {FHIR}},
	volume = {228},
	issn = {0926-9630},
	abstract = {Unreconciled data structures and formats are a common obstacle to the urgently required sharing and reuse of data within healthcare and medical research. Within the North German Tumor Bank of Colorectal Cancer, clinical and sample data, based on a harmonized data set, is collected and can be pooled by using a hospital-integrated Research Data Management System supporting biobank and study management. Adding further partners who are not using the core data set requires manual adaptations and mapping of data elements. Facing this manual intervention and focusing the reuse of heterogeneous healthcare instance data (value level) and data elements (metadata level), a metadata repository has been developed. The metadata repository is an ISO 11179-3 conformant server application built for annotating and mediating data elements. The implemented architecture includes the translation of metadata information about data elements into the FHIR standard using the FHIR Data Element resource with the ISO 11179 Data Element Extensions. The FHIR-based processing allows exchange of data elements with clinical and research IT systems as well as with other metadata systems. With increasingly annotated and harmonized data elements, data quality and integration can be improved for successfully enabling data analytics and decision support.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Ulrich, Hannes and Kock, Ann-Kristin and Duhm-Harbeck, Petra and Habermann, Jens K. and Ingenerf, Josef},
	year = {2016},
	pmid = {27577363},
	keywords = {},
	pages = {162--166}
}