Publications by authors named "Stefanie Rudolph"

The COVID-19 pandemic has spurred large-scale, interinstitutional research efforts. To enable these efforts, researchers must agree on data set definitions that not only cover all elements relevant to the respective medical specialty but also are syntactically and semantically interoperable. Therefore, the German Corona Consensus (GECCO) data set was developed as a harmonized, interoperable collection of the most relevant data elements for COVID-19-related patient research.

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The German government initiated the Network University Medicine (NUM) in early 2020 to improve national research activities on the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. To this end, 36 German Academic Medical Centers started to collaborate on 13 projects, with the largest being the National Pandemic Cohort Network (NAPKON). The NAPKON's goal is creating the most comprehensive Coronavirus Disease 2019 (COVID-19) cohort in Germany.

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Article Synopsis
  • The COVID-19 pandemic has led to a lot of research, resulting in fragmented information that needs standardization for effective comparison.
  • A new dataset called the "German Corona Consensus Dataset" (GECCO) has been developed to create uniformity across COVID-19 data using international standards for better data interoperability.
  • GECCO consists of 81 core data elements related to COVID-19 patients, including demographics and medical history, mapped to recognized health terminologies and designed for machine-readable data exchange, with plans for future enhancements.
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This article describes the DataBox project which offers a perspective of a new health data management solution in Germany. DataBox was initially conceptualized as a repository of individual lung cancer patient data (structured and unstructured). The patient is the owner of the data and is able to share his or her data with different stakeholders.

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