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Big Data in der Gesundheitsförderung und Prävention: Ergebnisse einer Delphi-Studie mit einem Schwerpunkt auf vulnerable Gruppen

BACKGROUND: The use of large and diverse amounts of data (Big Data) can lead to the gaining of health-related insights. The relevance is underlined by current challenges, for example in connection with digitization, health care in exceptional situations and the increasing importance of personalizati...

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Detalles Bibliográficos
Autores principales: Spranger, Julia, Niederberger, Marlen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8247614/
http://dx.doi.org/10.1007/s11553-021-00871-8
Descripción
Sumario:BACKGROUND: The use of large and diverse amounts of data (Big Data) can lead to the gaining of health-related insights. The relevance is underlined by current challenges, for example in connection with digitization, health care in exceptional situations and the increasing importance of personalization processes in health research. The potential of Big Data for research on vulnerable groups is controversial, but particularly relevant against the background of relatively persistent socially determined health inequalities. OBJECTIVES: The study examines how experts in the field of health data analysis assess the potential of Big Data in health promotion and prevention, especially for research on vulnerable groups. MATERIALS AND METHODS: In a Delphi study, experts were surveyed in two rounds using an online questionnaire to identify consensus and dissent on the potential of Big Data. RESULTS AND CONCLUSIONS: From the experts’ point of view, Big Data holds potential for health promotion and prevention, especially in the clinical setting and in the personalization of health-related measures. People with rare diseases and older people could benefit from Big Data analyses, for example through faster diagnostic processes or personalized digital health applications. The experts disagreed on the extent to which research institutions, health insurers or companies should be allowed to use or share such data.