Artificial intelligence-driven improvement of hospital logistics management resilience: a practical exploration based on H Hospital

TL;DR

This study demonstrates that AI integration significantly enhances hospital logistics resilience, especially when combined with adaptive management and continuous improvement processes, based on a comprehensive case study at H Hospital.

Contribution

It provides empirical evidence on AI's role in improving hospital logistics resilience and highlights the importance of management systems and PDCA cycle in this process.

Findings

94.7% staff perceived AI benefits

AI improved equipment maintenance and resource allocation

AI's positive effect on resilience is mediated by PDCA cycle

Abstract

Hospital logistics management faces growing pressure from internal operations and external emergencies, with artificial intelligence (AI) holding untapped potential to boost its resilience. This study explores AI's role in enhancing logistics resilience via a mixed-methods case study of H Hospital, combining 12 key informant interviews and a full survey of 151 logistics staff, with the PDCA cycle as the analytical framework. Thematic and quantitative analyses (hierarchical regression, structural equation modeling) were adopted for data analysis. Results showed 94.7% staff perceived AI application, with the strongest improvements in equipment maintenance (41.1%) and resource allocation (33.1%), but limited effects in emergency response (18.54%) and risk management (15.23%). AI integration positively correlated with logistics resilience (\b{eta}=0.642, p<0.001), with management system adaptability as a positive moderator (\b{eta}=0.208, p<0.01). The PDCA cycle fully mediated the AI-resilience relationship. We conclude AI effectively enhances logistics resilience, dependent on adaptive management systems and structured continuous improvement mechanisms. Targeted strategies are proposed to form an AI-driven closed-loop resilience mechanism, offering empirical guidance for AI-hospital logistics integration and resilient health system construction.