Data Protection in Healthcare-Integrated Biobanking

Abstract

Introduction Development of personalized medicine depends on research using clinical biospecimens and data. This interface between clinical care and translational research is increasingly served by hospital-integrated biobanks; yet their implementation is hampered by complex data regulations. Methods A generic data protection concept with a decision and application matrix was developed addressing five criteria: (1) organizational integration into university medicine, (2) biobank governance, (3) ethical and legal aspects, (4) specifications of the BSI (Bundesamt für Sicherheit in der Informationstechnik [Federal Office for Information Security]), and (5) FAIR (findable, accessible, interoperable, and reusable) principles for research data. Applicability was tested for the highest complexity level at Campus Lübeck. Results The data protection concept was approved by the local ethics committee as well as local and national data protection authorities. The concept allows an automated research-guided patient recruitment and data protection-compliant information technology (IT) in connection to national and international research networks. It ensures university and hospital conformity with the EU Data Protection Regulation. Consent behavior of 277,766 patients over five years proved routine practicability (error rate 0.0013%; withdrawals 0.09%). Clinical staff obtained higher consent rates (85.6%) compared with consent rates for use of data only at central patient admission (56.1%); even though consents in central patient admission increased constantly during observation time. Conclusion The generic data protection concept can legitimately enable personalized medicine through biobanking in the clinical context.

Standardizing digital biobanks: integrating imaging, genomic, and clinical data for precision medicine

“…In the second section we will focus on how a CDB could be implemented and standardized, including the identification of key use cases and scenarios addressing specific clinical questions. While always keeping in mind the necessary security and privacy regulations in accessing and retrieving biobank data [ 19 , 20 ], we will tackle the missing aspects to envision workable solutions. Furthermore, our study aims to emphasize the role of biobanks as a tool for predictive research, interpreting them as a source of multifactorial information to set up predictive models supporting decision-making in the healthcare system.…”