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

Minjie Chen; Yiling Fan; Qingrong Xu; Hua Huang; Xinyi Zheng; Dongdong Xiao; Weilin Fang; Jun Qin; Junhua Zheng; Enhong Dong

doi:10.3389/fpubh.2022.1019073

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

Front Public Health. 2023 Jan 6:10:1019073. doi: 10.3389/fpubh.2022.1019073. eCollection 2022.

Authors

Minjie Chen¹, Yiling Fan², Qingrong Xu³, Hua Huang⁴, Xinyi Zheng⁵, Dongdong Xiao⁶, Weilin Fang⁶, Jun Qin⁷, Junhua Zheng⁶, Enhong Dong^{8

9}

Affiliations

¹ Department of Outpatient and Emergency Management, Renji Hospital, School of Medicine in Shanghai Jiao Tong University, Shanghai, China.
² Department of Neurosurgery, Renji Hospital, School of Medicine in Shanghai Jiao Tong University, Shanghai, China.
³ Department of Orthopaedics, Renji Hospital, School of Medicine in Shanghai Jiao Tong University, Shanghai, China.
⁴ Department of Administration, Renji Hospital, School of Medicine in Shanghai Jiao Tong University, Shanghai, China.
⁵ Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China.
⁶ Department of Urology, Renji Hospital, School of Medicine in Shanghai Jiao Tong University, Shanghai, China.
⁷ Department of Gastroenterology, Renji Hospital, School of Medicine in Shanghai Jiao Tong University, Shanghai, China.
⁸ School of Nursing and Health Management, Shanghai University of Medicine and Health Sciences, Shanghai, China.
⁹ Institute of Healthy Yangtze River Delta, Shanghai Jiao Tong University, Shanghai, China.

Abstract

Introduction: In 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.

Methods: To 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.

Results: We 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.

Conclusion: The 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.

Keywords: COVID-19 pandemic; China; TAN Bayesian network; giant makeshift hospital; performance.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Bayes Theorem
COVID-19* / epidemiology
China / epidemiology
Hospitals
Humans
Pandemics
Public Health
Retrospective Studies

Grants and funding

This research was funded by National Social Science Foundation of China Projects (Grant Nos. 18BGL242, 19BGL246, 22AZD082, and 18ZDA088); Shanghai 2021 Science and Technology Innovation Action Plan Soft Science Key Project (Grant No. 21692104900); National Nature Science Foundation of China (Grant No. 81700532). The funders had no role in the question design, analysis or interpretation.