An AI-Driven Integrated Analytical Framework for Hospital Planning

Abstract

In the context of increasing complexity for precise matching of healthcare demand and supply, this study proposes an AI-integrated analytical framework to support strategic hospital resource planning. By employing AI-driven analytics of hospital resource requirements and generating operational planning schemes through multistage analytical and optimization framework, the strategic allocation of hospital resources, represented by bed capacity, can be adjusted to achieve the synergistic optimization of hospital strategic goals. The study further employs a simulation technique to evaluate the impact of the proposed plans on key strategic indicators. Empirical results demonstrate that the proposed plan enhances core strategic indicators while maintaining the admission patterns of departments. It also ensures the fairness of healthcare resource allocation, with good control of operational risks. This research helps establish a strategic resource planning paradigm by providing an AI-driven strategic planning tool that can dynamically respond to external demand changes and consider multiple metrics, including healthcare safety, service quality, and operational efficiency.