Through the Looking-Glass: The Current AI Landscape in German Hospitals from a Cybersecurity Perspective

Abstract

Due to demographic changes, an increasing shortage of skilled healthcare workers in Germany, particularly in hospitals, is anticipated in the coming years. Reasons include but are not limited to fewer young professionals entering the workforce and an increasing variety and prevalence of illnesses among older individuals. A promising approach to address this shortage is the integration of artificial intelligence (AI) applications into daily hospital operations. The introduction of AI in hospitals alters the attack surface, leading to new threat scenarios against which hospitals, as part of critical infrastructure, must be protected. Since there is currently no detailed overview of AI applications in German hospitals, and the range of medical specialties is vast, this study aims to systematically document AI applications in German hospitals that are planned, being implemented, or routinely used. The structure of our analysis is based on IT-supported hospital processes (e.g., diagnosis, treatment, laboratory, and administration). Our study aims to provide insights into the current security-related handling of AI applications throughout the phases of the AI life cycle, including data collection, data processing, training, inference, and integration. Additionally, the study will serve as a foundation for further research in the field of IT security for AI applications.

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