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Artificial intelligence is transforming healthcare by supporting clinical decision making with data-driven insights. Yet, as hospitals adopt AI tools, questions arise about hospital negligence and medical liability when AI contributes to patient harm. Understanding the legal theories behind hospital liability for AI-driven care is essential for risk management professionals aiming to reduce hospital risk and protect patients. How AI Changes Clinical Decision Making Hospitals

Artificial intelligence continues to evolve rapidly, reshaping how platforms deliver information and interact with users. Two powerful techniques, Reinforcement Learning from Human Feedback (RLHF) and Retrieval-Augmented Generation (RAG), have emerged as key drivers in improving AI performance. Understanding their advantages helps clarify why platforms like OpenEvidence are gaining traction in delivering accurate, context-aware, and user-friendly AI experiences in healthcare.

Healthcare organizations rely heavily on vendors for a range of services, from medical supplies to IT support. These partnerships are essential but can also expose organizations to risks if agreements are not carefully crafted. Vendor agreements must protect the healthcare provider while ensuring compliance with laws and smooth cooperation. This post highlights three critical provisions every healthcare organization should include in vendor contracts: indemnity, cooperation w

Congress has introduced the AI Kill Switch Act, a legislative proposal designed to ensure human control over AI technologies. This post explores the purpose of this act, its key provisions, and the potential impact on AI development and safety in health care operations. What Is the AI Kill Switch Act? The AI Kill Switch Act requires developers and operators of advanced AI systems to include a reliable mechanism that allows humans to immediately deactivate or shut down the AI

Utilization management (UM) plays a crucial role in healthcare by ensuring that patients receive appropriate care while controlling costs. Yet, traditional UM processes often involve time-consuming manual reviews and complex decision-making. AI offers a powerful way to improve efficiency, accuracy, and outcomes in utilization management. This post explores how AI technologies are beginning to transform UM and considerations for healthcare organizations adopting these tools. A

A nationally recognized expert in the development of regulatory and ethical compliance standards for AI sued her former employer, Mayo Clinic, for what she alleges is "a narrative of institutional wrongdoing" involving AI. Portions of the complaint shed light on concerning revelations of purported AI error rates. The Allegations According to the lawsuit, filed in July 2026, the former employee raised concern's about the hospital's process for de-identifying patient data in it