Practical Reflections on AI-Powered KPI Performance Improvement from the Perspective of Hospital Managers
Keywords:
Artificial Intelligence, Hospital Management, KPI Performance, Refined Management, High-Quality DevelopmentAbstract
In the context of high-quality development in public hospitals, Key Performance Indicators (KPI) have become an important management tool for hospital managers to enhance medical quality, operational efficiency, and service levels. However, traditional hospital KPI management exhibits significant shortcomings in data integration, dynamic monitoring, and decision support, struggling to meet the demands of refined management. This study aims to systematically analyze the mechanism through which Artificial Intelligence (AI) enhances hospital KPI performance from the perspective of hospital managers, construct an analytical framework for AI-empowered hospital KPI management, and explore its implementation pathways in management practice. Employing a normative research method, this paper summarizes the limitations of traditional hospital KPI management and synthesizes the empowering role of AI on KPI performance across aspects such as medical quality control, operational efficiency improvement, cost management, and patient experience optimization. The results indicate that by enhancing the real-time and prospective nature of data analysis, AI contributes to transforming hospital KPI management from outcome-oriented to process-oriented, and from experience-driven to data-driven. The study posits that systematically integrating AI into the hospital performance management system helps increase the scientific rigor and sustainability of managerial decision-making, providing crucial support for the high-quality development of hospitals. This research offers theoretical reference and managerial insights for hospital managers advancing the practice of AI-empowered performance management.
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