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Biometry --- Medical statistics --- Multivariate analysis

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"Much of the data collected in the statutory health insurance system is of great value for the further development and improvement of health care. Social and health data as personal data are also subject to a tight legal framework in terms of data protection law. Their use in other contexts requires a deep understanding of the regulations at European and national level.This volume provides an overview of the current legal framework and an important orientation for the legally secure use of social and health data. The plant makes it possible to develop solutions and products that improve the quality of care. The first part sets out the social law framework for the use of social data for research. The second part provides an overview of how research data is handled after the application of the GDPR and corresponding national adjustments to the legal framework."

Epidemiology & medical statistics --- Medicine --- health care --- data protection --- data science

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"The field of international medical terminology is complex. In the first part of the book, recommendations are published in which the experts involved advocate the use of internationally used terminologies (e.g. LOINC, SNOMED CT) to ensure an international exchange of information. Here it becomes particularly clear that detailed solutions can only be gradually approached and that a national strategy is urgently required.In the second part, experts from science, associations and industry provide the most important technical background information on individual topics and terminology systems, e.g. on ICD-11, SNOMED CT, LOINC and identifiers in the pharmaceutical sector, on terminology servers and semantic management, metadata, acceptance factors and definitions as well as future ones Importance of terminology systems in research and care."

Epidemiology & medical statistics --- research data --- terminology --- medical documentation --- epSOS --- international nomenclatura --- interoperability

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The trust of patients and test subjects is an indispensable prerequisite for the success of medical research projects that cannot be carried out without the collection, long-term storage and analysis of clinical data and samples. Medical research today mainly works in networks in increasingly larger research networks. Accordingly, the importance of data protection and data security continues to increase. The TMF published generic data protection concepts for medical research associations in 2003 for the first time. On this basis, numerous research projects were able to develop and coordinate their data protection concepts more quickly. The experience gained has been incorporated into the fundamental revision of the generic concepts. The new concept of the complexity of medical research processes takes account of this with a modular structure and was also embedded in a comprehensive guideline.

Epidemiology & medical statistics --- data protection --- medical research --- E-Health --- clinical study

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The benefit of cohort studies and registers in patient-oriented collaborative research depends largely on the quality of the data recorded there. Supply and quality research depend on scientifically proven methods and procedures to ensure high data quality. This guideline contains corresponding recommendations for the management of data quality in registers, cohort studies and data repositories. In the second edition, a significantly expanded set of indicators is provided and the use of the indicators is described as an example for different types of empirical research projects. The guideline is rounded off by a current literature review and analysis. It is therefore an important part of the range of measures to improve and ensure data quality in medical research.

Medicine --- Research --- Methodology. --- Health Workforce --- Epidemiology & medical statistics --- data repository --- source data verification --- cohort study --- quality indicators