The use of health data can provide valuable insights for both research and industry comprising the potential to improve healthcare services and facilitate the development of innovative solutions for the healthcare sector. However, due to data protection requirements and technical challenges, access to health data is still severely inhibited. To enhance access to and utilization of health data, science and politics increasingly consider data trustee models as a conceivable solution. Yet, such concepts are still in their infancies and hardly known. At the same time, they exhibit strong differences in their design. Thus, to foster awareness about and the development of data trustee models, this study investigates their design characteristics and integrates them into a holistic taxonomy. Additionally, design patterns are explored and archetypes derived. The findings reveal that data trustee models in healthcare follow some overarching design patterns and can be assigned to four dominant archetypes.
Lauf, Florian; Scheider, Simon; Friese, Jana; Kilz, Sarah; Radic, Marija; and Burmann, Anja, "Exploring Design Characteristics of Data Trustees in Healthcare - Taxonomy and Archetypes" (2023). ECIS 2023 Research Papers. 323.