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Peng Y, Bathelt F, Gebler R, Gött R, Heidenreich A, Henke E, Kadioglu D, Lorenz S, Vengadeswaran A, Sedlmayr M. Use of Metadata-Driven Approaches for Data Harmonization in the Medical Domain: Scoping Review. JMIR Med Inform 2024; 12:e52967. [PMID: 38354027 PMCID: PMC10902772 DOI: 10.2196/52967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 12/01/2023] [Accepted: 12/03/2023] [Indexed: 03/02/2024] Open
Abstract
BACKGROUND Multisite clinical studies are increasingly using real-world data to gain real-world evidence. However, due to the heterogeneity of source data, it is difficult to analyze such data in a unified way across clinics. Therefore, the implementation of Extract-Transform-Load (ETL) or Extract-Load-Transform (ELT) processes for harmonizing local health data is necessary, in order to guarantee the data quality for research. However, the development of such processes is time-consuming and unsustainable. A promising way to ease this is the generalization of ETL/ELT processes. OBJECTIVE In this work, we investigate existing possibilities for the development of generic ETL/ELT processes. Particularly, we focus on approaches with low development complexity by using descriptive metadata and structural metadata. METHODS We conducted a literature review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We used 4 publication databases (ie, PubMed, IEEE Explore, Web of Science, and Biomed Center) to search for relevant publications from 2012 to 2022. The PRISMA flow was then visualized using an R-based tool (Evidence Synthesis Hackathon). All relevant contents of the publications were extracted into a spreadsheet for further analysis and visualization. RESULTS Regarding the PRISMA guidelines, we included 33 publications in this literature review. All included publications were categorized into 7 different focus groups (ie, medicine, data warehouse, big data, industry, geoinformatics, archaeology, and military). Based on the extracted data, ontology-based and rule-based approaches were the 2 most used approaches in different thematic categories. Different approaches and tools were chosen to achieve different purposes within the use cases. CONCLUSIONS Our literature review shows that using metadata-driven (MDD) approaches to develop an ETL/ELT process can serve different purposes in different thematic categories. The results show that it is promising to implement an ETL/ELT process by applying MDD approach to automate the data transformation from Fast Healthcare Interoperability Resources to Observational Medical Outcomes Partnership Common Data Model. However, the determining of an appropriate MDD approach and tool to implement such an ETL/ELT process remains a challenge. This is due to the lack of comprehensive insight into the characterizations of the MDD approaches presented in this study. Therefore, our next step is to evaluate the MDD approaches presented in this study and to determine the most appropriate MDD approaches and the way to integrate them into the ETL/ELT process. This could verify the ability of using MDD approaches to generalize the ETL process for harmonizing medical data.
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Affiliation(s)
- Yuan Peng
- Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | | | - Richard Gebler
- Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Robert Gött
- Core Unit Datenintegrationszentrum, University Medicine Greifswald, Greifswald, Germany
| | - Andreas Heidenreich
- Department for Information and Communication Technology (DICT), Data Integration Center (DIC), Goethe University Frankfurt, University Hospital, Frankfurt am Main, Germany
| | - Elisa Henke
- Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Dennis Kadioglu
- Department for Information and Communication Technology (DICT), Data Integration Center (DIC), Goethe University Frankfurt, University Hospital, Frankfurt am Main, Germany
- Institute for Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Stephan Lorenz
- Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Abishaa Vengadeswaran
- Institute for Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Martin Sedlmayr
- Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
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2
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Silber AS, Platte S, Kumar A, Arora S, Kadioglu D, Schmidt M, Storf H, Chiocchetti AG, Freitag CM. Admission rates and clinical profiles of children and youth with eating disorders treated as inpatients before and during the COVID-19 pandemic in a German university hospital. Front Public Health 2023; 11:1281363. [PMID: 38098830 PMCID: PMC10720619 DOI: 10.3389/fpubh.2023.1281363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 09/22/2023] [Indexed: 12/17/2023] Open
Abstract
Introduction Children and youth at risk for mental health disorders, such as eating disorders (ED), were particularly affected by the COVID-19 pandemic, yet evidence for the most seriously affected and thus hospitalized youth in Germany is scarce. Methods This crosssectional study investigated anonymized routine hospital data (demographic information, diagnoses, treatment modalities) of patients admitted (n = 2,849) to the Department of Child and Adolescence Psychiatry, Psychosomatics and Psychotherapy (DCAPPP) of a German University Hospital between 01/2016 and 02/2022. Absolute and relative number of inpatients with or without ED prior to (01/2016-02/2020) and during the COVID-19 pandemic (03/2020-02/2022) were compared. The effect of school closures as part of social lockdown measures for COVID-19 mitigation on inpatient admission rate was explored as it has been discussed as a potential risk factor for mental health problems in youth. Results During the COVID-19 pandemic, ED inpatient admission rate increased from 10.5 to 16.7%, primarily driven by Anorexia Nervosa (AN). In contrast to previous reports, we found no change in somatic and mental disorder comorbidity, age or sexratio for hospitalized youth with ED. However, we did observe a shortened length of hospital stay (LOS) for hospitalized youth with and without ED. In addition, non-ED admissions presented with an increased number of mental disorder comorbidities. In contrast to our hypothesis, school closures were not related to the observed increase in ED. Discussion In summary, the COVID-19 pandemic was associated with an increased rate of inpatient treatment for youth suffering from AN, and of youth affected by multiple mental disorders. Accordingly, we assume that inpatient admission was prioritized for individuals with a higher burden of disease during the COVID-19 pandemic. Our findings pinpoint the need for adequate inpatient mental health treatment capacities during environmental crises, and a further strengthening of child and adolescence psychiatry services in Germany.
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Affiliation(s)
- Ann-Sophie Silber
- Department of Psychiatry, Psychosomatics and Psychotherapy of Childhood and Adolescence, Goethe University Frankfurt, University Hospital, Frankfurt am Main, Germany
| | - Simeon Platte
- Department of Psychiatry, Psychosomatics and Psychotherapy of Childhood and Adolescence, Goethe University Frankfurt, University Hospital, Frankfurt am Main, Germany
| | - Afsheen Kumar
- Department of Psychiatry, Psychosomatics and Psychotherapy of Childhood and Adolescence, Goethe University Frankfurt, University Hospital, Frankfurt am Main, Germany
| | - Sukhdeep Arora
- Department of Psychiatry, Psychosomatics and Psychotherapy of Childhood and Adolescence, Goethe University Frankfurt, University Hospital, Frankfurt am Main, Germany
| | - Dennis Kadioglu
- Institute of Medical Informatics (IMI), Goethe University Frankfurt, University Hospital, Frankfurt am Main, Germany
| | - Marvin Schmidt
- Institute of Medical Informatics (IMI), Goethe University Frankfurt, University Hospital, Frankfurt am Main, Germany
| | - Holger Storf
- Institute of Medical Informatics (IMI), Goethe University Frankfurt, University Hospital, Frankfurt am Main, Germany
| | - Andreas G. Chiocchetti
- Department of Psychiatry, Psychosomatics and Psychotherapy of Childhood and Adolescence, Goethe University Frankfurt, University Hospital, Frankfurt am Main, Germany
| | - Christine M. Freitag
- Department of Psychiatry, Psychosomatics and Psychotherapy of Childhood and Adolescence, Goethe University Frankfurt, University Hospital, Frankfurt am Main, Germany
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3
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Gierend K, Freiesleben S, Kadioglu D, Siegel F, Ganslandt T, Waltemath D. The Status of Data Management Practices Across German Medical Data Integration Centers: Mixed Methods Study. J Med Internet Res 2023; 25:e48809. [PMID: 37938878 PMCID: PMC10666010 DOI: 10.2196/48809] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 09/09/2023] [Accepted: 09/29/2023] [Indexed: 11/10/2023] Open
Abstract
BACKGROUND In the context of the Medical Informatics Initiative, medical data integration centers (DICs) have implemented complex data flows to transfer routine health care data into research data repositories for secondary use. Data management practices are of importance throughout these processes, and special attention should be given to provenance aspects. Insufficient knowledge can lead to validity risks and reduce the confidence and quality of the processed data. The need to implement maintainable data management practices is undisputed, but there is a great lack of clarity on the status. OBJECTIVE Our study examines the current data management practices throughout the data life cycle within the Medical Informatics in Research and Care in University Medicine (MIRACUM) consortium. We present a framework for the maturity status of data management practices and present recommendations to enable a trustful dissemination and reuse of routine health care data. METHODS In this mixed methods study, we conducted semistructured interviews with stakeholders from 10 DICs between July and September 2021. We used a self-designed questionnaire that we tailored to the MIRACUM DICs, to collect qualitative and quantitative data. Our study method is compliant with the Good Reporting of a Mixed Methods Study (GRAMMS) checklist. RESULTS Our study provides insights into the data management practices at the MIRACUM DICs. We identify several traceability issues that can be partially explained with a lack of contextual information within nonharmonized workflow steps, unclear responsibilities, missing or incomplete data elements, and incomplete information about the computational environment information. Based on the identified shortcomings, we suggest a data management maturity framework to reach more clarity and to help define enhanced data management strategies. CONCLUSIONS The data management maturity framework supports the production and dissemination of accurate and provenance-enriched data for secondary use. Our work serves as a catalyst for the derivation of an overarching data management strategy, abiding data integrity and provenance characteristics as key factors. We envision that this work will lead to the generation of fairer and maintained health research data of high quality.
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Affiliation(s)
- Kerstin Gierend
- Department of Biomedical Informatics at the Center for Preventive Medicine and Digital Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Sherry Freiesleben
- Core Unit Data Integration Center and Medical Informatics Laboratory, University Medicine Greifswald, Greifswald, Germany
| | - Dennis Kadioglu
- Institute for Medical Informatics (IMI), Goethe University Frankfurt, University Hospital, Frankfurt am Main, Germany
- Department for Information and Communication Technology (DICT), Data Integration Center (DIC), Goethe University Frankfurt, University Hospital, Frankfurt am Main, Germany
| | - Fabian Siegel
- Department of Biomedical Informatics at the Center for Preventive Medicine and Digital Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Thomas Ganslandt
- Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Dagmar Waltemath
- Core Unit Data Integration Center and Medical Informatics Laboratory, University Medicine Greifswald, Greifswald, Germany
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Schmidt M, Gebauer S, Bartholmes A, Kadioglu D, Kleesiek J, Hamm B, Vogl TJ, Penzkofer T, Bucher AM, Storf H. CODEX Meets RACOON - A Concept for Collaborative Documentation of Clinical and Radiological COVID-19 Data. Stud Health Technol Inform 2022; 296:58-65. [PMID: 36073489 DOI: 10.3233/shti220804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Within the scope of the two NUM projects CODEX and RACOON we developed a preliminary technical concept for documenting clinical and radiological COVID-19 data in a collaborative approach and its preceding findings of a requirement analysis. At first, we provide an overview of NUM and its two projects CODEX and RACOON including the GECCO data set. Furthermore, we demonstrate the foundation for the increased collaboration of both projects, which was additionally supported by a survey conducted at University Hospital Frankfurt. Based on the survey results mint Lesion™, developed by Mint Medical and used at all project sites within RACOON, was selected as the "Electronic Data Capture" (EDC) system for CODEX. Moreover, to avoid duplicate entry of GECCO data into both EDC systems, an early effort was made to consider a collaborative and efficient technical approach to reduce the workload for the medical documentalists. As a first effort we present a preliminary technical concept representing the current and possible future data workflow of CODEX and RACOON. This concept includes a software component to synchronize GECCO data sets between the two EDC systems using the HL7 FHIR standard. Our first approach of a collaborative use of an EDC system and its medical documentalists could be beneficial in combination with the presented synchronization component for all participating project sites of CODEX and RACOON with regard to an overall reduced documentation workload.
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Affiliation(s)
- Marvin Schmidt
- Institute of Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Sebastian Gebauer
- Institute of Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Annette Bartholmes
- Data Integration Center, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Dennis Kadioglu
- Institute of Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Frankfurt am Main, Germany
- Data Integration Center, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Jens Kleesiek
- Institute for AI in Medicine (IKIM), University Hospital Essen, Essen, Germany
| | - Bernd Hamm
- Department of Radiology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Thomas J Vogl
- Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Tobias Penzkofer
- Department of Radiology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Andreas Michael Bucher
- Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Holger Storf
- Institute of Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Frankfurt am Main, Germany
- Data Integration Center, University Hospital Frankfurt, Frankfurt am Main, Germany
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5
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Vasseur J, Zieschank A, Göbel J, Schaaf J, Dahmer-Heath M, König J, Kadioglu D, Storf H. Development of an Interactive Dashboard for OSSE Rare Disease Registries. Stud Health Technol Inform 2022; 293:187-188. [PMID: 35592980 DOI: 10.3233/shti220367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
BACKGROUND The Open Source Registry System for Rare Diseases (OSSE), a web-based tool to create rare disease patient registries, currently offers no possibility to view aggregated registry data within the system. Here, we present the development and implementation of a dashboard for the registry of the German NEOCYST (Network for early onset cystic kidney diseases) consortium. METHODS Based on user requirements from NEOCYST, we developed a general dashboard for all OSSE registries, which was extended with NEOCYST-specific statistics. RESULTS The dashboard now allows users to gain a quick overview of key data, such as patient counts or the availability of biospecimens. CONCLUSION This work represents a first prototypical approach for an OSSE dashboard, demonstrated in an existing rare disease registry, to be further evaluated and enhanced in the future.
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Affiliation(s)
- Jessica Vasseur
- Institute of Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Germany
| | - Axel Zieschank
- Institute of Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Germany
| | - Jens Göbel
- Institute of Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Germany
| | - Jannik Schaaf
- Institute of Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Germany
| | - Mareike Dahmer-Heath
- Institute of Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Germany
| | - Jens König
- Department of General Pediatrics, University Children's Hospital Münster, Germany
| | - Dennis Kadioglu
- Institute of Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Germany
| | - Holger Storf
- Institute of Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Germany
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6
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Kapsner LA, Mang JM, Mate S, Seuchter SA, Vengadeswaran A, Bathelt F, Deppenwiese N, Kadioglu D, Kraska D, Prokosch HU. Linking a Consortium-Wide Data Quality Assessment Tool with the MIRACUM Metadata Repository. Appl Clin Inform 2021; 12:826-835. [PMID: 34433217 PMCID: PMC8387126 DOI: 10.1055/s-0041-1733847] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Background
Many research initiatives aim at using data from electronic health records (EHRs) in observational studies. Participating sites of the German Medical Informatics Initiative (MII) established data integration centers to integrate EHR data within research data repositories to support local and federated analyses. To address concerns regarding possible data quality (DQ) issues of hospital routine data compared with data specifically collected for scientific purposes, we have previously presented a data quality assessment (DQA) tool providing a standardized approach to assess DQ of the research data repositories at the MIRACUM consortium's partner sites.
Objectives
Major limitations of the former approach included manual interpretation of the results and hard coding of analyses, making their expansion to new data elements and databases time-consuming and error prone. We here present an enhanced version of the DQA tool by linking it to common data element definitions stored in a metadata repository (MDR), adopting the harmonized DQA framework from Kahn et al and its application within the MIRACUM consortium.
Methods
Data quality checks were consequently aligned to a harmonized DQA terminology. Database-specific information were systematically identified and represented in an MDR. Furthermore, a structured representation of logical relations between data elements was developed to model plausibility-statements in the MDR.
Results
The MIRACUM DQA tool was linked to data element definitions stored in a consortium-wide MDR. Additional databases used within MIRACUM were linked to the DQ checks by extending the respective data elements in the MDR with the required information. The evaluation of DQ checks was automated. An adaptable software implementation is provided with the R package
DQAstats
.
Conclusion
The enhancements of the DQA tool facilitate the future integration of new data elements and make the tool scalable to other databases and data models. It has been provided to all ten MIRACUM partners and was successfully deployed and integrated into their respective data integration center infrastructure.
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Affiliation(s)
- Lorenz A Kapsner
- Medical Center for Information and Communication Technology, Universitätsklinikum Erlangen, Erlangen, Germany.,Department of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Jonathan M Mang
- Medical Center for Information and Communication Technology, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Sebastian Mate
- Medical Center for Information and Communication Technology, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Susanne A Seuchter
- Medical Center for Information and Communication Technology, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Abishaa Vengadeswaran
- Medical Informatics Group (MIG), Goethe University Frankfurt, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Franziska Bathelt
- Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technical University Dresden, Dresden, Germany
| | - Noemi Deppenwiese
- Medical Center for Information and Communication Technology, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Dennis Kadioglu
- Medical Informatics Group (MIG), Goethe University Frankfurt, University Hospital Frankfurt, Frankfurt am Main, Germany.,Data Integration Center, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Detlef Kraska
- Medical Center for Information and Communication Technology, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Hans-Ulrich Prokosch
- Medical Center for Information and Communication Technology, Universitätsklinikum Erlangen, Erlangen, Germany.,Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Erlangen, Germany
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7
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Abaza H, Kadioglu D, Martin S, Papadopoulou A, Dos Santos Vieira B, Schaefer F, Storf H. Domain-specific Common Data Elements for Rare Disease Registration: A Conceptual Approach of a European Joint Initiative towards Semantic Interoperability in Rare Disease Research (Preprint). JMIR Med Inform 2021; 10:e32158. [PMID: 35594066 PMCID: PMC9166638 DOI: 10.2196/32158] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 11/28/2021] [Accepted: 01/02/2022] [Indexed: 11/13/2022] Open
Abstract
Background Objective Methods Results Conclusions
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Affiliation(s)
- Haitham Abaza
- Institute of Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Dennis Kadioglu
- Institute of Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Simona Martin
- European Commission, Joint Research Centre, Ispra, Italy
| | | | - Bruna Dos Santos Vieira
- Department of Medical Imaging, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, Netherlands
- Center for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, Netherlands
| | - Franz Schaefer
- Division of Pediatric Nephrology, Center for Pediatrics and Adolescent Medicine, Heidelberg, Germany
| | - Holger Storf
- Institute of Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Frankfurt am Main, Germany
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8
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Schaaf J, Sedlmayr M, Prokosch HU, Tegtbauer N, Kadioglu D, Schaefer J, Boeker M, Storf H. Visualization of Similar Patients in a Clinical Decision Support System for Rare Diseases - A Focus Group Study. Stud Health Technol Inform 2021; 278:49-57. [PMID: 34042875 DOI: 10.3233/shti210050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The diagnosis of patients with rare diseases is often delayed. A Clinical Decision Support System using similarity analysis of patient-based data may have the potential to support the diagnosis of patients with rare diseases. This qualitative study has the objective to investigate how the result of a patient similarity analysis should be presented to a physician to enable diagnosis support. We conducted a focus group with physicians practicing in rare diseases as well as medical informatics researchers. To prepare the focus group, a literature search was performed to check the current state of research regarding visualization of similar patients. We then created software-mockups for the presentation of these visualization methods for the discussion within the focus group. Two persons took independently field notes for data collection of the focus group. A questionnaire was distributed to the participants to rate the visualization methods. The results show that four visualization methods are promising for the visualization of similar patients: "Patient on demand table", "Criteria selection", "Time-Series chart" and "Patient timeline. "Patient on demand table" shows a direct comparison of patient characteristics, whereas "Criteria selection" allows the selection of different patient criteria to get deeper insights into the data. The "Time-Series chart" shows the time course of clinical parameters (e.g. blood pressure) whereas a "Patient timeline" indicates which time events exist for a patient (e.g. several symptoms on different dates). In the future, we will develop a software-prototype of the Clinical Decision Support System to include the visualization methods and evaluate the clinical usage.
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Affiliation(s)
- Jannik Schaaf
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt, Germany
| | - Martin Sedlmayr
- Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine Technical University of Dresden, Dresden, Germany
| | - Hans-Ulrich Prokosch
- Chair of Medical Informatics, Department of Medical Informatics, Biometrics and Epidemiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Niels Tegtbauer
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt, Germany
| | - Dennis Kadioglu
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt, Germany
| | - Johanna Schaefer
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt, Germany
| | - Martin Boeker
- Institute of Medical Biometry and Statistics, Medical Faculty and Medical Centre - University of Freiburg, Freiburg, Germany
| | - Holger Storf
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt, Germany
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9
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Berger A, Rustemeier AK, Göbel J, Kadioglu D, Britz V, Schubert K, Mohnike K, Storf H, Wagner TOF. How to design a registry for undiagnosed patients in the framework of rare disease diagnosis: suggestions on software, data set and coding system. Orphanet J Rare Dis 2021; 16:198. [PMID: 33933089 PMCID: PMC8088651 DOI: 10.1186/s13023-021-01831-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 04/20/2021] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND About 30 million people in the EU and USA, respectively, suffer from a rare disease. Driven by European legislative requirements, national strategies for the improvement of care in rare diseases are being developed. To improve timely and correct diagnosis for patients with rare diseases, the development of a registry for undiagnosed patients was recommended by the German National Action Plan. In this paper we focus on the question on how such a registry for undiagnosed patients can be built and which information it should contain. RESULTS To develop a registry for undiagnosed patients, a software for data acquisition and storage, an appropriate data set and an applicable terminology/classification system for the data collected are needed. We have used the open-source software Open-Source Registry System for Rare Diseases (OSSE) to build the registry for undiagnosed patients. Our data set is based on the minimal data set for rare disease patient registries recommended by the European Rare Disease Registries Platform. We extended this Common Data Set to also include symptoms, clinical findings and other diagnoses. In order to ensure findability, comparability and statistical analysis, symptoms, clinical findings and diagnoses have to be encoded. We evaluated three medical ontologies (SNOMED CT, HPO and LOINC) for their usefulness. With exact matches of 98% of tested medical terms, a mean number of five deposited synonyms, SNOMED CT seemed to fit our needs best. HPO and LOINC provided 73% and 31% of exacts matches of clinical terms respectively. Allowing more generic codes for a defined symptom, with SNOMED CT 99%, with HPO 89% and with LOINC 39% of terms could be encoded. CONCLUSIONS With the use of the OSSE software and a data set, which, in addition to the Common Data Set, focuses on symptoms and clinical findings, a functioning and meaningful registry for undiagnosed patients can be implemented. The next step is the implementation of the registry in centres for rare diseases. With the help of medical informatics and big data analysis, case similarity analyses could be realized and aid as a decision-support tool enabling diagnosis of some undiagnosed patients.
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Affiliation(s)
- Alexandra Berger
- Frankfurt Reference Centre for Rare Diseases, University Hospital Frankfurt, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany.
| | - Anne-Kathrin Rustemeier
- Medical Clinic II, University Hospital Gießen and Marburg, Klinikstraße 33, 35392, Gießen, Germany
| | - Jens Göbel
- Medical Informatics Group Frankfurt, University Hospital Frankfurt, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Dennis Kadioglu
- Medical Informatics Group Frankfurt, University Hospital Frankfurt, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Vanessa Britz
- Frankfurt Reference Centre for Rare Diseases, University Hospital Frankfurt, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Katharina Schubert
- Central-German Network for rare diseases, University Hospital Magdeburg A.Ö.R, Leipziger Straße 44, 39120, Magdeburg, Germany
| | - Klaus Mohnike
- Central-German Network for rare diseases, University Hospital Magdeburg A.Ö.R, Leipziger Straße 44, 39120, Magdeburg, Germany
| | - Holger Storf
- Medical Informatics Group Frankfurt, University Hospital Frankfurt, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Thomas O F Wagner
- Frankfurt Reference Centre for Rare Diseases, University Hospital Frankfurt, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
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Scheible R, Kadioglu D, Ehl S, Blum M, Boeker M, Folz M, Grimbacher B, Göbel J, Klein C, Nieters A, Rusch S, Kindle G, Storf H. Enabling External Inquiries to an Existing Patient Registry by Using the Open Source Registry System for Rare Diseases: Demonstration of the System Using the European Society for Immunodeficiencies Registry. JMIR Med Inform 2020; 8:e17420. [PMID: 33026355 PMCID: PMC7578818 DOI: 10.2196/17420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 03/13/2020] [Accepted: 03/22/2020] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND The German Network on Primary Immunodeficiency Diseases (PID-NET) utilizes the European Society for Immunodeficiencies (ESID) registry as a platform for collecting data. In the context of PID-NET data, we show how registries based on custom software can be made interoperable for better collaborative access to precollected data. The Open Source Registry System for Rare Diseases (Open-Source-Registersystem für Seltene Erkrankungen [OSSE], in German) provides patient organizations, physicians, scientists, and other parties with open source software for the creation of patient registries. In addition, the necessary interoperability between different registries based on the OSSE, as well as existing registries, is supported, which allows those registries to be confederated at both the national and international levels. OBJECTIVE Data from the PID-NET registry should be made available in an interoperable manner without losing data sovereignty by extending the existing custom software of the registry using the OSSE registry framework. METHODS This paper describes the following: (1) the installation and configuration of the OSSE bridgehead, (2) an approach using a free toolchain to set up the required interfaces to connect a registry with the OSSE bridgehead, and (3) the decentralized search, which allows the formulation of inquiries that are sent to a selected set of registries of interest. RESULTS PID-NET uses the established and highly customized ESID registry software. By setting up a so-called OSSE bridgehead, PID-NET data are made interoperable according to a federated approach, and centrally formulated inquiries for data can be received. As the first registry to use the OSSE bridgehead, the authors introduce an approach using a free toolchain to efficiently implement and maintain the required interfaces. Finally, to test and demonstrate the system, two inquiries are realized using the graphical query builder. By establishing and interconnecting an OSSE bridgehead with the underlying ESID registry, confederated queries for data can be received and, if desired, the inquirer can be contacted to further discuss any requirements for cooperation. CONCLUSIONS The OSSE offers an infrastructure that provides the possibility of more collaborative and transparent research. The decentralized search functionality includes registries into one search application while still maintaining data sovereignty. The OSSE bridgehead enables any registry software to be integrated into the OSSE network. The proposed toolchain to set up the required interfaces consists of freely available software components that are well documented. The use of the decentralized search is uncomplicated to use and offers a well-structured, yet still improvable, graphical user interface to formulate queries.
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Affiliation(s)
- Raphael Scheible
- Institute of Medical Biometry and Statistics, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Institute for Immunodeficiency, Center for Chronic Immunodeficiency, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Dennis Kadioglu
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Stephan Ehl
- Institute for Immunodeficiency, Center for Chronic Immunodeficiency, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Marco Blum
- Institute of Medical Biometry and Statistics, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Martin Boeker
- Institute of Medical Biometry and Statistics, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Michael Folz
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Bodo Grimbacher
- Institute for Immunodeficiency, Center for Chronic Immunodeficiency, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Center for Infection Research, Satellite Center Freiburg, Freiburg, Germany
- Centre for Integrative Biological Signalling Studies, University of Freiburg, Freiburg, Germany
- RESIST, Cluster of Excellence 2155 to Hanover Medical School, Satellite Center Freiburg, Freiburg, Germany
| | - Jens Göbel
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Christoph Klein
- Department of Pediatrics, Dr von Hauner Children's Hospital, University Hospital, Ludwig Maximilians Universität München, München, Germany
| | - Alexandra Nieters
- Institute for Immunodeficiency, Center for Chronic Immunodeficiency, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- FREEZE Biobank, Center for Biobanking, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Stephan Rusch
- Institute for Immunodeficiency, Center for Chronic Immunodeficiency, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- FREEZE Biobank, Center for Biobanking, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Gerhard Kindle
- Institute for Immunodeficiency, Center for Chronic Immunodeficiency, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- FREEZE Biobank, Center for Biobanking, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Holger Storf
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt am Main, Germany
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Schaaf J, Sedlmayr M, Prokosch HU, Ganslandt T, Schade-Brittinger C, von Wagner M, Kadioglu D, Schubert K, Lee-Kirsch MA, Kraemer BK, Winner B, Mueller T, Schaefer JR, Wagner TOF, Bruckner-Tuderman L, Tuescher O, Boeker M, Storf H. The Status Quo of Rare Diseases Centres for the Development of a Clinical Decision Support System - A Cross-Sectional Study. Stud Health Technol Inform 2020; 271:176-183. [PMID: 32578561 DOI: 10.3233/shti200094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Clinical decision support systems (CDSS) help to improve the diagnostics and treatment of rare diseases (RD). As one of four funded consortia of the Medical Informatics Initiative supported by the Federal Ministry of Education and Research (BMBF, Germany), MIRACUM develops a clinical decision support system (CDSS) for RD based on distributed data of ten university hospitals. The CDSS will be developed at the Rare Diseases Centres (RDC) of the MIRACUM consortium. Since it is essential to deliver decision support at the right time and place in the clinician's workflow, this study aimed to capture relevant information of the RDCs regarding patient admission and diagnostic process. Additionally, we investigated how patient documentation and digitalisation is performed at the centres. Therefore, we conducted a cross-sectional survey involving experts in the RDs domain to capture relevant information for the further development of a CDSS in RD. For each centre, one expert on RDs participated in the study (n=8). The survey identified several challenges regarding the reuse of patient data, e.g. the paper-based documentation of a patientâĂŹs medical history and coding of diagnoses using ICD-10. However, we noticed a relevant use of current software diagnosis support and a similarly performed diagnostic process in all RDC. Further studies are needed to get more detailed insights and to define specific requirements.
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Affiliation(s)
- Jannik Schaaf
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt, Germany
| | - Martin Sedlmayr
- Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technical University of Dresden, Dresden, Germany
| | - Hans-Ulrich Prokosch
- Chair of Medical Informatics, Department of Medical Informatics, Biometrics and Epidemiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Thomas Ganslandt
- Heinrich-Lanz-Centre for Digital Health, Department of Biomedical Informatics, University Medicine Mannheim, Mannheim, Germany
| | - Carmen Schade-Brittinger
- Chair of the Coordinating Centre for Clinical Trials, Philipps University Marburg, Marburg, Germany
| | - Michael von Wagner
- Executive Department for Medical IT-Systems and Digitalisation, University Hospital Frankfurt, Frankfurt, Germany
| | - Dennis Kadioglu
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt, Germany
| | - Katharina Schubert
- Central German Competence Network for Rare Diseases, University Hospitals Magdeburg & Halle, Germany
| | - Min Ae Lee-Kirsch
- University Centre for Rare Diseases, University Hospital Carl Gustav Carus Dresden, Dresden, Germany
| | - Bernhard K Kraemer
- Mannheim Centre for Rare Diseases, University Medicine Mannheim, Medical Faculty Mannheim of the University of Heidelberg, Mannheim, Germany
| | - Beate Winner
- Centre for Rare Diseases Erlangen, University Hospital Erlangen, Erlangen, Germany
| | - Tobias Mueller
- Centre for undiagnosed and rare diseases, University Hospital Gießen and Marburg, Marburg, Germany
| | - Juergen R Schaefer
- Centre for undiagnosed and rare diseases, University Hospital Gießen and Marburg, Marburg, Germany
| | - Thomas O F Wagner
- Frankfurt Reference Centre for Rare Diseases, University Hospital Frankfurt, Frankfurt, Germany
| | - Leena Bruckner-Tuderman
- Freiburg Centre for Rare Diseases, Medical Faculty and Medical Centre - University of Freiburg, Freiburg, Germany
| | - Oliver Tuescher
- Centre for Rare Diseases of the Nervous System, University Medicine Mainz, Mainz, Germany
| | - Martin Boeker
- Institute of Medical Biometry and Statistics, Medical Faculty and Medical Centre - University of Freiburg, Freiburg, Germany
| | - Holger Storf
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt, Germany
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12
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Vengadeswaran A, Neuhaus P, Hegselmann S, Storf H, Kadioglu D. Semantically Annotated Metadata: Interconnecting Samply.MDR and MDM-Portal. Stud Health Technol Inform 2019; 267:86-92. [PMID: 31483259 DOI: 10.3233/shti190810] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Interoperability is a growing demand in healthcare, caused by heterogeneous sources, which aggravate information transfer. The interoperability issues can be addressed by metadata repositories. These support to ensure syntactical interoperability, like compatible data formats or value ranges, however especially semantic interoperability is still challenging. Semantic annotation through standardized terminologies and classifications enables to foster semantic interoperability. This work aims to interconnect Samply.MDR and Portal of Medical Data Model (MDM-Portal) to allow facilitated semantic annotation with UMLS. Therefore, Samply.MDR was extended to store semantic information. While creating a data element, a request to MDM is send, which results in possible UMLS codes. The user can now adopt the most suitable code and select a link type between the code and the element itself. A successful enrichment of data elements with UMLS codes was shown by interconnecting Samply.MDR and MDM-Portal.
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Affiliation(s)
- Abishaa Vengadeswaran
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Philipp Neuhaus
- Institute of Medical Informatics, University of Münster, Münster, Germany
| | - Stefan Hegselmann
- Institute of Medical Informatics, University of Münster, Münster, Germany
| | - Holger Storf
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Dennis Kadioglu
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt am Main, Germany
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13
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Schaaf J, Boeker M, Ganslandt T, Haverkamp C, Hermann T, Kadioglu D, Prokosch HU, Wagner TOF, von Wagner M, Schaefer J, Sedlmayr M, Storf H. Finding the Needle in the Hay Stack: An Open Architecture to Support Diagnosis of Undiagnosed Patients. Stud Health Technol Inform 2019; 264:1580-1581. [PMID: 31438241 DOI: 10.3233/shti190544] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Clinical Decision Support Systems (CDSS) are promising to support physicians in finding the right diagnosis of patients with rare diseases (RD). The MIRACUM consortium, which includes ten university hospitals in Germany, will establish a diagnosis support system for RD. This system conducts a similarity analysis on distributed clinical data with the aim to identify similar patient cases at each MIRACUM site to offer the physician a hint to a possible diagnosis.
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Affiliation(s)
- Jannik Schaaf
- Medical Informatics Group (MIG), University Hospital Frankfurt, Frankfurt, Germany
| | - Martin Boeker
- Institute of Medical Biometry and Statistics, Medical Faculty and Medical Center - University of Freiburg, Freiburg, Germany
| | - Thomas Ganslandt
- Department of Biomedical Informatics, University Medicine Mannheim, Ruprecht-Karls-University Heidelberg, Mannheim, Germany
| | | | - Tim Hermann
- Institute for Biometry and Medical Informatics, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
| | - Dennis Kadioglu
- Medical Informatics Group (MIG), University Hospital Frankfurt, Frankfurt, Germany
| | - Hans-Ulrich Prokosch
- Chair of Medical Informatics, Department of Medical Informatics, Biometrics and Epidemiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Thomas O F Wagner
- Frankfurt Reference Center for Rare Diseases, University Hospital Frankfurt, Frankfurt, Germany
| | - Michael von Wagner
- Executive Department of Medical IT-Systems and Digitalization, University Hospital Frankfurt, Frankfurt, Germany
| | - Johanna Schaefer
- Medical Informatics Group (MIG), University Hospital Frankfurt, Frankfurt, Germany
| | - Martin Sedlmayr
- Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine Technische Universität Dresden, Dresden, Germany
| | - Holger Storf
- Medical Informatics Group (MIG), University Hospital Frankfurt, Frankfurt, Germany
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14
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Kock-Schoppenhauer AK, Bruland P, Kadioglu D, Brammen D, Ulrich H, Kulbe K, Duhm-Harbeck P, Ingenerf J. Scientific Challenge in eHealth: MAPPATHON, a Metadata Mapping Challenge. Stud Health Technol Inform 2019; 264:1516-1517. [PMID: 31438209 DOI: 10.3233/shti190512] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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.
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Affiliation(s)
| | - Philipp Bruland
- Institute of Medical Informatics, University of Münster, Germany
| | - Dennis Kadioglu
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Dominik Brammen
- Department of Anesthesiology, University of Magdeburg, Germany
| | - Hannes Ulrich
- IT Center for Clinical Research, Lübeck, University of Lübeck, Germany
| | - Kerstin Kulbe
- Institute of Medical Informatics, University of Lübeck, Germany
| | | | - Josef Ingenerf
- IT Center for Clinical Research, Lübeck, University of Lübeck, Germany.,Institute of Medical Informatics, University of Lübeck, Germany
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15
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Storf H, Schaaf J, Kadioglu D, Göbel J, Wagner TOF, Ückert F. [Registries for rare diseases : OSSE - An open-source framework for technical implementation]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2018; 60:523-531. [PMID: 28289778 DOI: 10.1007/s00103-017-2536-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Meager amounts of data stored locally, a small number of experts, and a broad spectrum of technological solutions incompatible with each other characterize the landscape of registries for rare diseases in Germany. Hence, the free software Open Source Registry for Rare Diseases (OSSE) was created to unify and streamline the process of establishing specific rare disease patient registries. The data to be collected is specified based on metadata descriptions within the registry framework's so-called metadata repository (MDR), which was developed according to the ISO/IEC 11179 standard. The use of a central MDR allows for sharing the same data elements across any number of registries, thus providing a technical prerequisite for making data comparable and mergeable between registries and promoting interoperability.With OSSE, the foundation is laid to operate linked patient registries while respecting strong data protection regulations. Using the federated search feature, data for clinical studies can be identified across registries. Data integrity, however, remains intact since no actual data leaves the premises without the owner's consent. Additionally, registry solutions other than OSSE can participate via the OSSE bridgehead, which acts as a translator between OSSE registry networks and non-OSSE registries. The pseudonymization service Mainzelliste adds further data protection.Currently, more than 10 installations are under construction in clinical environments (including university hospitals in Frankfurt, Hamburg, Freiburg and Münster). The feedback given by the users will influence further development of OSSE. As an example, the installation process of the registry for undiagnosed patients at University Hospital Frankfurt is described in more detail.
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Affiliation(s)
- Holger Storf
- Medical Informatics Group (MIG), Universitätsklinikum Frankfurt, Haus 33C, Theodor-Stern-Kai 7, 60590, Frankfurt, Deutschland.
| | - Jannik Schaaf
- Medical Informatics Group (MIG), Universitätsklinikum Frankfurt, Haus 33C, Theodor-Stern-Kai 7, 60590, Frankfurt, Deutschland
| | - Dennis Kadioglu
- Institut für Medizinische Biometrie, Epidemiologie und Informatik (IMBEI), Universitätsmedizin Mainz, Obere Zahlbacher Str. 69, 55131, Mainz, Deutschland
| | - Jens Göbel
- Medical Informatics Group (MIG), Universitätsklinikum Frankfurt, Haus 33C, Theodor-Stern-Kai 7, 60590, Frankfurt, Deutschland
| | - Thomas O F Wagner
- Frankfurter Referenzzentrum für Seltene Erkrankungen (FRZSE), Universitätsklinikum Frankfurt, Haus 18, Theodor-Stern-Kai 7, 60590, Frankfurt, Deutschland
| | - Frank Ückert
- Medizinische Informatik in der Translationalen Onkologie, Deutsches Krebsforschungszentrum Heidelberg, Im Neuenheimer Feld 280, 69120, Heidelberg, Deutschland
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16
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Lablans M, Kadioglu D, Muscholl M, Ückert F. Exploiting Distributed, Heterogeneous and Sensitive Data Stocks while Maintaining the Owner’s Data Sovereignty. Methods Inf Med 2018. [PMID: 26196653 DOI: 10.3414/me14-01-0137] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
SummaryBackground: To achieve statistical significance in medical research, biological or data samples from several bio- or databanks often need to be complemented by those of other institutions. For that purpose, IT-based search services have been established to locate datasets matching a given set of criteria in databases distributed across several institutions. However, previous approaches require data owners to disclose information about their samples, raising a barrier for their participation in the network.Objective: To devise a method to search distributed databases for datasets matching a given set of criteria while fully maintaining their owner’s data sovereignty.Methods: As a modification to traditional federated search services, we propose the decentral search, which allows the data owner a high degree of control. Relevant data are loaded into local bridgeheads, each under their owner’s sovereignty. Researchers can formulate criteria sets along with a project proposal using a central search broker, which then notifies the bridgeheads. The criteria are, however, treated as an inquiry rather than a query: Instead of responding with results, bridgeheads notify their owner and wait for his/her decision regarding whether and what to answer based on the criteria set, the matching datasets and the specific project proposal. Without the owner’s explicit consent, no data leaves his/ her institution.Results: The decentral search has been deployed in one of the six German Centers for Health Research, comprised of eleven university hospitals. In the process, compliance with German data protection regulations has been confirmed. The decentral search also marks the centerpiece of an open source registry software toolbox aiming to build a national registry of rare diseases in Germany.Conclusions: While the sacrifice of real-time answers impairs some use-cases, it leads to several beneficial side effects: improved data protection due to data parsimony, tolerance for incomplete data schema mappings and flexibility with regard to patient consent. Most importantly, as no datasets ever leave their institution, owners can reject projects without facing potential peer pressure. By its lower barrier for participation, a decentral search service is likely to attract a larger number of partners and to bring a researcher into contact with the right potential partners.
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Affiliation(s)
- M Lablans
- Martin Lablans, University Medical Center Mainz, Obere Zahlbacher Straße 69, 55131 Mainz, Germany, E-mail:
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17
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Kadioglu D, Breil B, Knell C, Lablans M, Mate S, Schlue D, Serve H, Storf H, Ückert F, Wagner T, Weingardt P, Prokosch HU. Samply.MDR - A Metadata Repository and Its Application in Various Research Networks. Stud Health Technol Inform 2018; 253:50-54. [PMID: 30147039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Collaboration in medical research is becoming common, especially for collecting relevant cases across institutional boundaries. If the data, which is usually very heterogeneously formalized and structured, can be integrated, such a collaboration can facilitate research. An absolute prerequisite for this is an extensive description about the formalization and exact meaning of every data element contained in a dataset. This information is commonly known as metadata. Various research networking projects tackle this challenge with the development of concepts and IT tools. The Samply Metadata Repository (Samply.MDR) is a solution for managing and publishing such metadata in a standardized and reusable way. In this article we present the structure and features of the Samply.MDR as well as its flexible usability by giving an overview about its application in various projects.
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Affiliation(s)
- Dennis Kadioglu
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Bernhard Breil
- Niederrhein University of Applied Sciences, Krefeld, Germany
| | - Christian Knell
- Chair of Medical Informatics, Friedrich-Alexander-University Erlangen-Nuernberg, Erlangen, Germany
| | - Martin Lablans
- Medical Informatics in Translational Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Sebastian Mate
- Chair of Medical Informatics, Friedrich-Alexander-University Erlangen-Nuernberg, Erlangen, Germany
| | - Danijela Schlue
- Center of Clinical Epidemiology, University Hospital Essen, Essen, Germany
| | - Hubert Serve
- Department of Hematology and Oncology, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Holger Storf
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Frank Ückert
- Medical Informatics in Translational Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Thomas Wagner
- Frankfurt Reference Center for Rare Diseases, University Hospital Frankfurt, Frankfurt am Main, Germany
| | | | - Hans-Ulrich Prokosch
- Chair of Medical Informatics, Friedrich-Alexander-University Erlangen-Nuernberg, Erlangen, Germany
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18
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Schaaf J, Kadioglu D, Goebel J, Behrendt CA, Roos M, van Enckevort D, Ückert F, Sadiku F, Wagner TOF, Storf H. OSSE Goes FAIR - Implementation of the FAIR Data Principles for an Open-Source Registry for Rare Diseases. Stud Health Technol Inform 2018; 253:209-213. [PMID: 30147075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
The Open Source Registry for Rare Diseases (OSSE) provides a concept and a software for the management of registries for patients with rare diseases. A disease is defined as rare if less than 5 out of 10,000 people are affected. Up to date, approximately 6,000 rare diseases are catalogued. Networking and data exchange for research purposes remains challenging due to the paucity of interoperability and due to the fact that small data stocks are stored locally. The so called "Findable, Accessible, Interoperable, Reusable" (FAIR) Data Principles have been developed to improve research in the field of rare diseases. Subsequently, the OSSE architecture was adapted to implement the FAIR Data Principles. Therefore, the so-called FAIR Data Point was integrated into OSSE to provide a description of metadata in a FAIR manner. OSSE relies on the existing metadata repository (MDR), which is used in to define data elements in the system. This is an important step towards unified documentation across multiple registries. The integration and use of new procedures to improve interoperability plays an important role in the context of registries for rare diseases.
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Affiliation(s)
- Jannik Schaaf
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt, Germany
| | - Dennis Kadioglu
- University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jens Goebel
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt, Germany
| | | | - Marco Roos
- Dutch Tech Centre for Life Sciences, Leiden, Netherlands
| | - David van Enckevort
- University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Frank Ückert
- Division of Medical Informatics for Translational Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Fatlume Sadiku
- Division of Medical Informatics for Translational Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Thomas O F Wagner
- Frankfurt Reference Center for Rare Diseases, University Hospital Frankfurt, Frankfurt, Germany
| | - Holger Storf
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt, Germany
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Mate S, Vormstein P, Kadioglu D, Majeed RW, Lablans M, Prokosch HU, Storf H. On-The-Fly Query Translation Between i2b2 and Samply in the German Biobank Node (GBN) Prototypes. Stud Health Technol Inform 2017; 243:42-46. [PMID: 28883167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Information retrieval is a major challenge in medical informatics. Various research projects have worked on this task in recent years on an institutional level by developing tools to integrate and retrieve information. However, when it comes down to querying such data across institutions, the challenge persists due to the high heterogeneity of data and differences in software systems. The German Biobank Node (GBN) project faced this challenge when trying to interconnect four biobanks to enable distributed queries for biospecimens. All biobanks had already established integrated data repositories, and some of them were already part of research networks. Instead of developing another software platform, GBN decided to form a bridge between these. This paper describes and discusses a core component from the GBN project, the OmniQuery library, which was implemented to enable on-the-fly query translation between heterogeneous research infrastructures.
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Affiliation(s)
- Sebastian Mate
- Medical Informatics, Univ. of Erlangen-Nürnberg, Erlangen, Germany
| | - Patric Vormstein
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt, Germany; German Cancer Consortium (DKTK), partner site Frankfurt; and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Dennis Kadioglu
- Medical Informatics, Univ. of Erlangen-Nürnberg, Erlangen, Germany
| | - Raphael W Majeed
- German Center for Lung Research, Justus-Liebig-University, Giessen, Germany
| | - Martin Lablans
- Medical Informatics in Translational Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Holger Storf
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt, Germany; German Cancer Consortium (DKTK), partner site Frankfurt; and German Cancer Research Center (DKFZ), Heidelberg, Germany
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20
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Mate S, Kadioglu D, Majeed RW, Stöhr MR, Folz M, Vormstein P, Storf H, Brucker DP, Keune D, Zerbe N, Hummel M, Senghas K, Prokosch HU, Lablans M. Proof-of-Concept Integration of Heterogeneous Biobank IT Infrastructures into a Hybrid Biobanking Network. Stud Health Technol Inform 2017; 243:100-104. [PMID: 28883179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Cross-institutional biobank networks hold the promise of supporting medicine by enabling the exchange of associated samples for research purposes. Various initiatives, such as BBMRI-ERIC and German Biobank Node (GBN), aim to interconnect biobanks for enabling the compilation of joint biomaterial collections. However, building software platforms to facilitate such collaboration is challenging due to the heterogeneity of existing biobank IT infrastructures and the necessary efforts for installing and maintaining additional software components. As a remedy, this paper presents the concept of a hybrid network for interconnecting already existing software components commonly found in biobanks and a proof-of-concept implementation of two prototypes involving four biobanks of the German Biobank Node. Here we demonstrate the successful bridging of two IT systems found in many German biobanks - Samply and i2b2.
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Affiliation(s)
- Sebastian Mate
- Medical Informatics, Univ. of Erlangen-Nürnberg, Erlangen, Germany
| | - Dennis Kadioglu
- Medical Informatics, Univ. of Erlangen-Nürnberg, Erlangen, Germany
| | - Raphael W Majeed
- UGMLC, German Center for Lung Research (DZL), Justus-Liebig-University, Giessen, Germany
| | - Mark R Stöhr
- UGMLC, German Center for Lung Research (DZL), Justus-Liebig-University, Giessen, Germany
| | - Michael Folz
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt, Germany
| | - Patric Vormstein
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt, Germany
| | - Holger Storf
- Medical Informatics Group, University Hospital Frankfurt, Frankfurt, Germany
| | - Daniel P Brucker
- German Cancer Consortium (DKTK), partner site Frankfurt; and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Dietmar Keune
- Clinical Cancer Registry, Charité Comprehensive Cancer Center, Berlin, Germany
| | - Norman Zerbe
- Institute of Pathology, Charité - Universitätsmedizin Berlin, Berlin, Germany; and Central Biobank Charité (ZeBanC), Berlin, Germany
| | - Michael Hummel
- Institute of Pathology, Charité - Universitätsmedizin Berlin, Berlin, Germany; and Central Biobank Charité (ZeBanC), Berlin, Germany
| | - Karsten Senghas
- Medical Informatics in Translational Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Martin Lablans
- Medical Informatics in Translational Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
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Schlue D, Mate S, Haier J, Kadioglu D, Prokosch HU, Breil B. From a Content Delivery Portal to a Knowledge Management System for Standardized Cancer Documentation. Stud Health Technol Inform 2017; 243:180-184. [PMID: 28883196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Heterogeneous tumor documentation and its challenges of interpretation of medical terms lead to problems in analyses of data from clinical and epidemiological cancer registries. The objective of this project was to design, implement and improve a national content delivery portal for oncological terms. Data elements of existing handbooks and documentation sources were analyzed, combined and summarized by medical experts of different comprehensive cancer centers. Informatics experts created a generic data model based on an existing metadata repository. In order to establish a national knowledge management system for standardized cancer documentation, a prototypical tumor wiki was designed and implemented. Requirements engineering techniques were applied to optimize this platform. It is targeted to user groups such as documentation officers, physicians and patients. The linkage to other information sources like PubMed and MeSH was realized.
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Affiliation(s)
- Danijela Schlue
- Niederrhein University of Applied Sciences, Krefeld, Germany
| | - Sebastian Mate
- Medical Informatics, Univ. of Erlangen-Nürnberg, Erlangen, Germany
| | | | | | | | - Bernhard Breil
- Niederrhein University of Applied Sciences, Krefeld, Germany
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Lablans M, Kadioglu D, Mate S, Leb I, Prokosch HU, Ückert F. Strategien zur Vernetzung von Biobanken. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2016; 59:373-8. [DOI: 10.1007/s00103-015-2299-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Zusammenfassung
Hintergrund
Nicht selten benötigt ein medizinisches Forschungsvorhaben mehr biologisches Material, als in einer einzigen Biobank verfügbar ist. Daher unterstützt eine Vielzahl von Strategien das Auffinden potentieller Forschungspartner mit passenden Proben, auch ohne dass diese zuvor in einer zentralisierten Sammlung zusammengeführt werden müssen.
Ziel
Der vorliegende Beitrag beschreibt die Klassifizierung verschiedener Strategien zur Vernetzung von Biomaterialbanken, speziell zur Probensuche, sowie eine IT-Infrastruktur, die diese Ansätze kombiniert.
Material und Methoden
Bestehende Strategien lassen sich nach drei Kriterien klassifizieren: a) Granularität der Probendaten: grobe Daten auf Bankebene (Katalog) vs. feingranulare Daten auf Probenebene, b) Speicherort der Probendaten: zentrale (zentraler Suchdienst) vs. dezentrale Datenhaltung (föderierte Suchdienste) und c) Automatisierungsgrad: automatisch (abfragebasiert, föderierter Suchdienst) vs. halbautomatisch (anfragebasiert, dezentrale Suche). Alle genannten Suchdienste setzen eine Datenintegration voraus; dabei helfen Metadaten bei der Überwindung semantischer Heterogenität.
Ergebnisse
Der „Common Service IT“ in BBMRI-ERIC („Biobanking and Biomolecular Resources Research Infrastructure-European Research Infrastructure Consortium“) vereint einen Katalog, die dezentrale Suche und Metadaten in einer integrierten Plattform, um Forschern vielseitige Werkzeuge zur Suche nach passendem Probenmaterial zu geben und bei den Biobankern gleichzeitig ein hohes Maß an Datenhoheit zu bewahren.
Diskussion
Trotz ihrer Unterschiede schließen sich die vorgestellten Strategien zur Vernetzung von Biomaterialbanken gegenseitig nicht aus. Vielmehr lassen sie sich in gemeinsamen Forschungsinfrastrukturen sinnvoll ergänzen und sie können sogar voneinander profitieren.
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Affiliation(s)
- Martin Lablans
- Medizinische Informatik in der Translationalen Onkologie, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120, Heidelberg, Deutschland.
| | - Dennis Kadioglu
- Institut für medizinische Biometrie, Epidemiologie und Informatik (IMBEI), Universitätsmedizin Mainz, 55101, Mainz, Deutschland
| | - Sebastian Mate
- Lehrstuhl für Medizinische Informatik, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Deutschland
| | - Ines Leb
- Lehrstuhl für Medizinische Informatik, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Deutschland
| | - Hans-Ulrich Prokosch
- Lehrstuhl für Medizinische Informatik, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Deutschland
| | - Frank Ückert
- Medizinische Informatik in der Translationalen Onkologie, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120, Heidelberg, Deutschland
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Gözil R, Kadioglu D, Calgüner E, Erdogan D, Bahcelioglu M, Elmas C. Branching patterns of rabbit oculomotor and trochlear nerves demonstrated by Sihler's stain technique. Biotech Histochem 2009. [DOI: 10.1080/bih.77.1.21.25] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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Gözil R, Kadioglu D, Calgüner E, Erdogan D, Bahcelioglu M, Elmas C. Branching patterns of rabbit oculomotor and trochlear nerves demonstrated by Sihler's stain technique. Biotech Histochem 2002; 77:21-5. [PMID: 11991327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2023] Open
Abstract
A modified Sihler's stain technique was used to visualize the branching patterns of oculomotor and trochlear nerves. The levator palpebrae, superior rectus, inferior rectus, medial rectus, inferior oblique, superior oblique and tensor trochlea muscles were isolated from the eyes of normal rabbits and processed using modified Sihler's technique. The distributions and terminal ramifications of the oculomotor and trochlear nerves were observed. Two distinct divisions and terminal branches of the oculomotor nerve were shown in detail together with the trochlear nerve distribution. The application of Sihler's technique enables researchers to trace nerve branching within relatively transparent muscles, whereas the nerve fibers are counterstained and clearly visible. This technique could be useful for detailed studies of the motor control of extraocular muscles.
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Affiliation(s)
- R Gözil
- Gazi University, Faculty of Medicine, Department of Anatomy, Besevler, Ankara, Turkey
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Kadioglu D, Harrison RG. The ultrastructure of the adrenal cortex of the Mongolian gerbil (M. unguiculatus). J Anat 1975; 120:179-89. [PMID: 1184455 PMCID: PMC1231732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Ultrastructurally, the adrenal cortex of the Mongolian gerbil can be divided into two main regions and one narrow interposed border zone. The outer region corresponds to the zona glomerulosa and zona fasciculata of the rat adrenal cortex, whereas the inner region corresponds to the rat zona reticularis. The mitochondria are variable in shape, size and internal structure but generally lamelliform or tubulo-vesicular with a dense matrix in the outer region and plate-like and tubular in the inner region. Some of the mitochondria in the border region are of the polylaminar membranous type. The endoplasmic reticulum is abundant and smooth in the outer region but less prominent in the inner regions, where it is both smooth and rough. The concentric whorled membranes of rough endoplasmic reticulum are a characteristic feature of the border zone. Lipid vacuoles are abundant in the outer region. Lysosomes are numerous in the inner region and tend to form groups of 4 or 5. Aminoglutethimide causes a less conspicuous alteration in the adrenal cortex of the Mongolian gerbil than in the rat. The main alterations consist of a profound increase of lipid and lysosomes, a decrease in the number of SER profiles, and complete disappearance of the whorled membranes of RER.
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Kadioglu D, Harrison RG. The functional relationships of mitochondria in the rat adrenal cortex. J Anat 1971; 110:283-96. [PMID: 5143833 PMCID: PMC1271096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
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