Progress on the application of system dynamics model in the field of health management.
10.3724/zdxbyxb-2025-0415
- Author:
Qiwei WU
1
;
Huijie ZHOU
2
;
Binyu ZHAO
3
;
Jing SHAO
4
Author Information
1. Department of Nursing, the Fourth Affiliated Hospital of Zhejiang University School of Medicine, International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu 322000, Zhejiang Province, China. qiweiwu@zju.edu.cn.
2. Department of Nursing, Wenzhou People's Hospital, Wenzhou 325000, Zhejiang Province, China.
3. Department of Nursing, the Fourth Affiliated Hospital of Zhejiang University School of Medicine, International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu 322000, Zhejiang Province, China.
4. Department of Nursing, the Fourth Affiliated Hospital of Zhejiang University School of Medicine, International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu 322000, Zhejiang Province, China. shaoj@zju.edu.cn.
- Publication Type:English Abstract
- Keywords:
Applied research;
Health management;
Modelling study;
Review;
System dynamics model
- MeSH:
Humans;
Health Policy;
Models, Theoretical
- From:
Journal of Zhejiang University. Medical sciences
2025;54(5):676-684
- CountryChina
- Language:Chinese
-
Abstract:
Health management is highly complex due to interactions across multiple levels and factors. System dynamics model (SDM) offers a holistic perspective and a dynamic analytical framework for understanding such complex systems. It has been applied across various domains of health management, including psychological interventions, chronic disease management, rehabilitation, optimization of medical services, and health policy development. By identifying key factors and pathways influencing health behaviors, determining critical targets for interventions, conducting cost-benefit analyses and process optimization, and simulating the long-term effects of health policies, SDM provides quantitative support for decision-making from individual-level interventions to macro-level policies. This article reviews the application of SDM in these four major areas within health management, discusses its advantages and limitations, and serves as a reference for researchers and practitioners aiming to utilize SDM in future studies. The goal is to advance health management toward greater personalization and precision, thereby offering stronger support for health interventions and policy development.
