A Secure and Interoperable Big Data Platform for AI-Driven Healthcare Solutions: Insights From the GATEKEEPER Project

Abstract

Digital innovation in the healthcare industry is transforming the delivery of healthcare services and enhancing their inherent capabilities. At the heart of this revolutionary process are healthcare data platforms, which enable organizations to aggregate and leverage patient data. However, the application of Big Data Analytics (BDA) and Artificial Intelligence (AI) in this sector presents important challenges, including technical, ethical, social, economic, organizational, and political-legal issues. The multi-disciplinary and cross-sectoral nature of the health and life-science contexts introduces barriers to communication and data sharing among various stakeholders, and exacerbates technical challenges such as interoperability, data protection, security management, compliance with laws and regulations, and support for AI applications. This paper presents the AI Big Data Platform (BDP) for healthcare, developed within the GATEKEEPER project, addressing the challenges associated with implementing state-of-the-art solutions in the healthcare context. This AI BDP facilitates the extraction of value from big volumes of heterogeneous and sensitive patient data while preserving privacy. It provides key features in interoperability, end-to-end security, multitenancy, and support for computationally intensive AI workloads. The AI Big Data Platform’s services are utilized by 8 GATEKEEPER pilots, deployed into 7 different countries, to implement 9 Reference Use Cases (RUC) 1, and involving approximately 200 users.

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