Optimization of Strategic Decision-Making in Hospital Management through the Use of Neutrosophic Z-Numbers for Uncertainty Assessment.

Abstract

Hospital management faces the critical challenge of making strategic decisions under pressure in environments characterized by uncertainty and multiple variables. This study addresses the need to optimize such decisions in order to improve both the quality and warmth of healthcare delivery. The relevance of this topic lies in its direct impact on user satisfaction and organizational efficiency, particularly in contexts where resources are limited and demands are high. Although existing literature explores decision-making methods, few approaches incorporate the inherent indeterminacy of complex environments such as hospitals. To address this gap, the present work employs Neutrosophic Z-Numbers, a mathematical tool that simultaneously models uncertainty, truth, and indeterminacy. By applying this approach, real hospital scenarios were analyzed, evaluating factors such as costs, service quality, and patient satisfaction. The results reveal that Neutrosophic Z-Numbers enable more precise prioritization of strategies, identifying robust solutions in the face of ambiguity. This study contributes to the field by introducing an innovative theoretical framework for hospital management and offering practical guidelines for implementing strategic decisions that optimize resources and improve care, thereby strengthening organizational resilience in dynamic contexts.