TA5 - Use Cases

TA5 “Use Cases”

Structured, quality assured individual phenotype and exposure-related health data are generated in clinical trials and epidemiological and public health studies. Clinical trials and (prospective) epidemiological studies are the most appropriate study designs to investigate (1) the onset and dynamics of measurable phenotype profiles and diseases on individual and population level and (2) the efficacy of diagnostic and therapeutic interventions. Access to detailed information on a large and unselected number of participants and patients is pivotal to advance patient risk stratification, to support personalised medicine, to find new interventional options and to improve patient care. Nowadays, even more data become available through large primary data collections (e.g., for cohort studies) and secondary data sources such as disease registries or health insurance data. The sharing and reuse of such data for research purposes are currently limited for several reasons: (1) lack of standardised metadata and methodological diversity in the collection of health information across studies, (2) incomplete knowledge of relevant studies and the nature of data collected in the research community, (3) regulatory, governance, ethical and legal challenges of data access and of bringing data together across populations or data sources and (4) lack of knowledge and skills of potential data users and limitations of data analytical infrastructures to use study data.
While TA2, TA3 and TA6 will develop necessary concepts and services related to data and metadata harmonisation and standardisation, data and metadata repositories, data access and data analyses, the main objective of TA5 is to implement or to at least explore the possibilities to implement these infrastructure components in specific use cases which reflect core needs of the scientific community related to health data research.

Contact

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Prof. Dr. Iris Pigeot

TA5-Lead
Measure-Lead: T5.3 “Use case ‘Secondary data and record linkage’”
Phone: +49 (0)228 73-60351
                                          
Leibniz Institute for Prevention Research and Epidemiology – BIPS GmbH
Achterstraße 30
D-28359 Bremen 
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Prof. Dr. Matthias Schulze

TA5-Lead
Phone: +49 (0)33 200 88 - 2434
                                          
German Institute of Human Nutrition Potsdam-Rehbruecke
Arthur-Scheunert-Allee 114-116
14558 Nuthetal 
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Prof. Dr. Ute Nöthlings 

Measure-Lead T5.1 “Use case ‘Nutritional epidemiology’”
Phone: +49 (0)228 73 60490
                                          
University of Bonn,
Institute for Nutrition and Food Sciences
Fiedrich-Hirzebruch-Allee 7
53115 Bonn
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Prof. Dr. Tobias Pischon

Phone: +49 (0)30 9406-4563
                                          
Max Delbrück Center for Molecular Medicine
Robert-Rössle-Straße 10
13125 Berlin, Deutschland
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Prof. Dr. Hajo Zeeb

Measure-Lead T5.2 “Use case ‘Epidemiology of chronic diseases’”
E-Mail: zeeb@leibniz-bips.de
Phone: +49 (0)421 218-56-902
                                          
Leibniz Institute for Prevention Research and Epidemiology – BIPS GmbH
Achterstraße 30
D-28359 Bremen
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Prof. Dr. Wolfgang Ahrens

Measure-Lead T5.3 “Use case ‘Secondary data and record linkage’”
Phone: +49 (0)421 218-56822
                                          
Leibniz Institute for Prevention Research and Epidemiology – BIPS GmbH
Achterstraße 30
D-28359 Bremen 
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Dr. Oana Brosteanu

Measure-Lead T5.4 “Use case ‘Clinical trials’”
Phone: +49 (0)341 97 16251
                                          
Leipzig University,
Institute for Medical Informatics, Statistics and Epidemiology (IMISE)
Härtelstraße 16-18
04107 Leipzig
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Matthias Löbe

Measure-Lead T5.4 “Use case ‘Clinical trials’”
Phone: +49 (0)341 97 16113
                                          
Leipzig University,
Institute for Medical Informatics, Statistics and Epidemiology (IMISE)
Härtelstraße 16-18
04107 Leipzig
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Prof. Dr. Horst Hahn

Measure-Lead T5.6 “Use case ‘Radiomics / imaging AI’”
Phone: +49 (0)421 218-59002
                                          
Fraunhofer Institute for Digital Medicine MEVIS
Max-von-Laue-Str. 2
28359 Bremen
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