Table_1_Medical implementation practice and its medical performance evaluation of a giant makeshift hospital during the COVID-19 pandemic: An innovative model response to a public health emergency in Shanghai, China.docx

IntroductionIn confronting the sudden COVID-19 epidemic, China and other countries have been under great pressure to block virus transmission and reduce fatalities. Converting large-scale public venues into makeshift hospitals is a popular response. This addresses the outbreak and can maintain smooth operation of a country or region's healthcare system during a pandemic. However, large makeshift hospitals, such as the Shanghai New International Expo Center (SNIEC) makeshift hospital, which was one of the largest makeshift hospitals in the world, face two major problems: Effective and precise transfer of patients and heterogeneity of the medical care teams.MethodsTo solve these problems, this study presents the medical practices of the SNIEC makeshift hospital in Shanghai, China. The experiences include constructing two groups, developing a medical management protocol, implementing a multi-dimensional management mode to screen patients, transferring them effectively, and achieving homogeneous quality of medical care. To evaluate the medical practice performance of the SNIEC makeshift hospital, 41,941 infected patients were retrospectively reviewed from March 31 to May 23, 2022. Multivariate logistic regression method and a tree-augmented naive (TAN) Bayesian network mode were used.ResultsWe identified that the three most important variables were chronic disease, age, and type of cabin, with importance values of 0.63, 0.15, and 0.11, respectively. The constructed TAN Bayesian network model had good predictive values; the overall correct rates of the model-training dataset partition and test dataset partition were 99.19 and 99.05%, respectively, and the respective values for the area under the receiver operating characteristic curve were 0.939 and 0.957.ConclusionThe medical practice in the SNIEC makeshift hospital was implemented well, had good medical care performance, and could be copied worldwide as a practical intervention to fight the epidemic in China and other developing countries.

引言在面对突发新冠疫情之际，我国及其他国家在阻断病毒传播和降低死亡率方面承受着巨大压力。将大规模公共场所临时改造成医院成为一种常见的应对策略。这一措施旨在应对疫情爆发，并能在疫情期间维持国家或地区医疗体系的顺畅运行。然而，如上海世博中心临时医院（SNIEC）等大型临时医院面临两大问题：患者有效且精确的转移以及医疗团队构成的异质性。方法为了解决这些问题，本研究呈现了上海世博中心临时医院的医疗实践。这些经验包括构建两组，制定医疗管理方案，实施多维管理模式以筛选患者，有效转移患者，并实现医疗护理的同质性。为了评估SNIEC临时医院的医疗实践绩效，对2022年3月31日至5月23日期间回顾性审查了41,941名感染患者。本研究采用了多元逻辑回归方法和树增强朴素贝叶斯网络模型。结果我们发现，三个最重要的变量分别为慢性疾病、年龄和病房类型，其重要性值分别为0.63、0.15和0.11。构建的TAN贝叶斯网络模型具有良好的预测价值；模型训练数据集和测试数据集的整体正确率分别为99.19%和99.05%，对应的受试者工作特征曲线下面积分别为0.939和0.957。结论SNIEC临时医院的医疗实践实施得当，医疗护理绩效良好，可作为全球范围内应对我国及其他发展中国家疫情的实际干预措施进行复制推广。