Background: Artificial intelligence (AI) is increasingly entering hospital practice through diagnostic, predictive, workflow, operational, and generative applications. Hospitals often govern these systems as procurement or information-technology projects rather than as clinical–organizational interventions requiring indication, evaluation, monitoring, accountability, and withdrawal. Objective: To refine the concept of an “AI Hospital Formulary” as an operational, proportional, and accountable framework for the safe, equitable, and sustainable adoption of hospital AI. Design and Methods: This is a perspective article using a structured, non-systematic narrative synthesis and conceptual framework development. Targeted literature and policy sources were identified through purposive searches and citation chaining through 20 July 2026. The synthesis compares the formulary with existing oversight approaches, maps its lifecycle gates to regulatory and risk management duties, and applies the framework to a worked example based on published evaluations of the Epic Sepsis Model. The EQUATOR reporting-guideline selection tool was consulted, and SANRA was used to strengthen the narrative synthesis component. Framework: The revised framework combines a hospital-wide AI register, a standardized formulary monograph, six lifecycle gates, proportional review pathways, governance-of-governance safeguards, cloud and data-sovereignty controls, continuous monitoring of technical and behavioral feedback loops, and explicit renewal or deprescribing criteria. The worked example shows how version-specific evidence can lead to local validation, controlled implementation, restriction, suspension, or renewal rather than automatic adoption. Conclusions: Hospitals should not merely purchase, install, and update AI systems. They should prescribe, monitor, audit, renew, restrict, and, when necessary, deprescribe them. The AI Hospital Formulary is proposed as a complementary institutional layer that converts external standards and existing governance approaches into documented portfolio decisions at the hospital level.
Francisco Epelde (Wed,) studied this question.