Emergency department treatment process planning: a field research, case analysis, and simulation approach

Xiaoyan Huang; Shuai Zhou; Xudong Ma; Zhitao Yang; Yuanyuan Xu; Xiaoxiao Shen; Zengni Zhang; Guang Ning; Erzhen Chen; Na Li; Yong Lu

doi:10.21037/atm-22-1944

Emergency department treatment process planning: a field research, case analysis, and simulation approach

Ann Transl Med. 2022 May;10(10):545. doi: 10.21037/atm-22-1944.

Authors

Xiaoyan Huang^#^{1

2}, Shuai Zhou^#³, Xudong Ma^#⁴, Zhitao Yang³, Yuanyuan Xu⁵, Xiaoxiao Shen⁶, Zengni Zhang⁶, Guang Ning⁷, Erzhen Chen^{2

8}, Na Li⁶, Yong Lu^{1

2

3}

Affiliations

¹ Department of Director's Office, Ruijin Hospital, Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
² Shanghai Venous Thromboembolism Alliance, Shanghai, China.
³ Division of Medical Affairs, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
⁴ Department of Medical Administration, National Health Commission of the People's Republic of China, Beijing, China.
⁵ General Office, Shanghai Hospital Association, Shanghai, China.
⁶ Department of Industrial Engineering and Management, School of Mechanical and Engineering, Shanghai Jiao Tong University, Shanghai, China.
⁷ Department of Endocrinology and Metabolism, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
⁸ Department of Emergency Intensive Care Unit, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

^# Contributed equally.

Abstract

Background: The coronavirus disease 2019 (COVID-19) has forced accelerated optimization of Emergency Department (ED) process, and simulation tools offer an alternative approach to strategic assessment and selection.

Methods: Field research and case analysis methods were used to obtain the treatment process and medical records information from the ED of a general hospital. Minitab was used for analysis of the measurement system, and Arena was applied for simulation modelling. We established a framework for the triage protocol of ordinary and quarantined patients, analysed bottlenecks in the treatment time of the hospital's ED, and proposed an optimised management strategy.

Results: The computed tomography (CT) pre-scheduling strategy simulation results demonstrated that longer CT room preparation times for quarantined people before their arrival (T_p) resulted in reduced CT scan and waiting times for quarantined patients, but these times were longer for ordinary patients. The nucleic acid priority strategy simulation results demonstrated that when the average daily number of ordinary patients (λ_c) was relatively stable, the hospital could guide ordinary patients to perform nucleic acid testing first followed by CT testing. However, when λ_c fluctuated greatly, the hospital could appropriately reduce the proportion of preferential nucleic acid testing. Furthermore, when λ_c was overloaded, the nucleic acid priority strategy showed no advantages. The joint analysis results demonstrated that the optimal strategy selection was significantly affected by the severity of the epidemic. The nucleic acid detection sample size optimisation strategy demonstrated that optimizing the sample size of each batch according to the number of patients could effectively reduce the waiting times for nucleic acid testing (T_n).

Conclusions: Simulation tools are an alternative method for strategic evaluation and selection that do not require external factors.

Keywords: CT testing; Simulation; coronavirus disease 2019 (COVID-19) epidemic; emergency department (ED); nucleic acid detection test.