Liu Shuai,1 Chunni Zhou,1 Jinyi Zhou,2 Hao Hu,3 Yunfeng Lai,4 Lijun Fan,1 Wei Du,1 Meng Li1 

1School of Public Health, Southeast University, Nanjing, People’s Republic of China; 2Department of Non-Communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, People’s Republic of China; 3State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, People’s Republic of China; 4School of Public Health and Management, Guangzhou University of Chinese Medicine, Guangzhou, People’s Republic of China

Correspondence: Meng Li, School of Public Health, Southeast University, 87, Dingjiaqiao Road, Gulou District, Nanjing, 210009, People’s Republic of China, Email meng-li@seu.edu.cn

Background: This systematic review aims to comprehensively assess the current application of discrete event simulation (DES) models in managing chronic obstructive pulmonary disease (COPD). By synthesizing and analyzing multiple studies, we incorporate the latest evidence, evaluate research quality, identify gaps, and provide recommendations for the future application of DES in COPD management.
Methods: We systematically searched six electronic databases including PubMed, Web of Science, Embase, Cochrane, Econlit, and China National Knowledge Infrastructure (CNKI) for articles published up to August 22, 2024. Reference lists of the included articles were also manually checked. Depending on the study type, we assessed quality using either the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 checklist or the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Practice Guidelines.
Results: Out of the 273 records identified, nine studies met the inclusion criteria. All of these studies focused on health economic evaluations using DES in COPD management, and were conducted in high-income countries. The studies were divided into three groups based on the modeling systems they used: cost-effectiveness analyses of different pharmacological treatments (n=3), economic evaluations of case detection strategies (n=3), and assessments of various interventions on COPD healthcare services (n=3). All studies reported model validation methods (n=9); however, only two studies performed subgroup analysis.
Conclusion: This review highlights the current use of DES in COPD management and suggests avenues for future research and resource allocation to enhance the effectiveness of COPD interventions.

Keywords: discrete event simulation, chronic obstructive pulmonary disease, personalized medicine, systematic review