Artificial Intelligence in Hospital Systems: The Expanding Data Ecosystem and the Need for Ethical Governance (Preprint)

Abstract

<sec> <title>UNSTRUCTURED</title> Abstract Artificial intelligence (AI) is transforming hospital and health care systems by enabling new forms of clinical decision support, operational forecasting, diagnostic automation, and remote physiological surveillance. These facets depend on unprecedented volumes of clinical, behavioral, and operational data that hospitals increasingly share across complex networks involving electronic medical record vendors, cloud infrastructure providers, device manufacturers, and third-party AI developers. Although these partnerships have accelerated technological innovation and generated significant improvements in efficiency and clinical practice, they have also introduced new risks in privacy, cybersecurity, data ownership, equity, algorithmic transparency, and environmental sustainability. This paper examines the expanding hospital data environment underlying AI systems, explores the implications of vendor-mediated data flows, identifies population-level and systemic risks, and proposes a multi-layered governance framework grounded in public health ethics. This analysis argues that because hospital AI systems are dynamic and operate at scale, transparent, equity-driven, and accountable data governance is essential to prevent the amplification of disparities and erosion of public trust in digital health technologies. </sec>

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