Computational modeling and analysis of medical resource shortages in hospital alliance: A simulation-driven approach - Zhenkun Gan; Zhengtang Fu; Peiwu Dong; Yanbing Ju; Yajun Shen (PLoS ONE, 2025)
Hospital alliances, as an innovative model of hospital management, are dedicated to achieving resource sharing across the entire healthcare network. During the COVID-19 pandemic in China, these alliances played a pivotal role in combating the outbreak. However, a significant challenge emerged: the difficulty in accurately quantifying medical resource shortages at individual hospitals hindered the efficient allocation of these critical resources. To address this issue, this study proposes an integrated urgent medical resource evaluation model designed to scientifically assess the urgency of medical resource needs within the alliance. Methodologically, the model innovatively combines the SEIR system dynamics model, complex network analysis, and entropy-weighted TOPSIS to construct a multi-dimensional evaluation framework. A case study has been conducted to validate the effectiveness of the proposed methodology. Contrary to conventional expectations, the findings reveal that small-scale hospitals exhibit higher medical resource urgency compared to their large-scale counterparts within the alliance. Based on these results, we recommend that policymakers prioritize addressing medical resource shortages in small-scale hospitals during pandemics.