ECONOMIC EVALUATION OF THE IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE SYSTEMS IN REGIONAL EPIDEMIOLOGICAL RISK MANAGEMENT: AN INTERDISCIPLINARY APPROACH

The article examines the methodological tools for evaluating the economic efficiency of intelligent systems in healthcare. Given the regional asymmetry of the Russian Federation, traditional monitoring models face limitations, necessitating the implementation of AI-based predictive analytics. The author conducts a comparative analysis of CBA, CEA, ROI, and HTA methods, validated through Russian (MosmedAI, North Ossetia-Alania) and global (BlueDot, CDC) cases. The theoretical framework synthesizes W. Oates’s fiscal federalism, L. von Bertalanffy’s general systems theory, and A. Bogdanov’s tectology. It is proven that a hybrid evaluation model mitigates ethical barriers to monetizing human life while ensuring budgetary transparency and an increase in quality-adjusted life years (QALY). A set of recommendations for the institutionalization of AI within the “Healthcare” National Project is proposed.