Carolin Martina Rauter|Sabine Wöhlke|Silke Schicktanz
My Data, My Choice? – German Patient Organizations’ Attitudes towards Big Data-Driven Approaches in Personalized Medicine. An Empirical-Ethical Study
Universitätsmedizin Göttingen|Universitätsmedizin Göttingen|Universitätsmedizin Göttingen
abstract personalized medicine pm operates biological data optimize therapy prevention achieve cost reduction associated data may consist large variations informational subtypes eg genetic characteristics epigenetic modifications biomarkers even individual lifestyle factors present innovations field information technology already enabled procession increasingly large amounts data volume various sources variety varying quality terms data accuracy veracity facilitate generation analyzation messy data sets within short highly efficient time period velocity provide insights previously unknown connections correlations different items value developments characteristics big data approaches big data become important catchphrase closely linked emerging foundations approaches pm however ethical concerns pointed experts debate already moral concerns stakeholders patient organizations pos need reflected context well used empiricalethical approach including websiteanalysis 27 telephoneinterviews gaining indepth insight german pos perspectives pm big data results show pos stakeholders way comparing perspectives political engagement minority pos currently actively involved research around pm big datadriven research led four stakeholder subclassifications mediators support research projects facilitating researchers access patient community simultaneously selecting projects preferably support cooperators tend contribute directly research projects providing implemeting patient perspectives financers provide financial resources independents keep control collected samples associated patientrelated information strong interest making autonomous decisions scientific use detailed terminology involvement pos stakeholders facilitates adressing aims goals based results independents subgroup promising candidate future collaborations scientific research additionally identified gaps pos knowledge pm big data based findings approaches developed increase data statistical literacy way full potential stakeholder involvement pos made accessible discourses around pm big data