Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Soc Sci Med. 2017 Dec;194:160-167. doi: 10.1016/j.socscimed.2017.09.005. Epub 2017 Sep 22.
Universal Health Coverage (UHC) is one of the targets for the United Nations Sustainable Development Goal 3. The impetus for UHC has led to an increased demand for time-sensitive tools to enhance our knowledge of how health systems function and to evaluate impact of system interventions. We define the field of "health system modeling" (HSM) as an area of research where dynamic mathematical models can be designed in order to describe, predict, and quantitatively capture the functioning of health systems. HSM can be used to explore the dynamic relationships among different system components, including organizational design, financing and other resources (such as investments in resources and supply chain management systems) - what we call "inputs" - on access, coverage, and quality of care - what we call "outputs", toward improved health system "outcomes", namely increased levels and fairer distributions of population health and financial risk protection. We undertook a systematic review to identify the existing approaches used in HSM. We identified "systems thinking" - a conceptual and qualitative description of the critical interactions within a health system - as an important underlying precursor to HSM, and collated a critical collection of such articles. We then reviewed and categorized articles from two schools of thoughts: "system dynamics" (SD)" and "susceptible-infected-recovered-plus" (SIR+). SD emphasizes the notion of accumulations of stocks in the system, inflows and outflows, and causal feedback structure to predict intended and unintended consequences of policy interventions. The SIR + models link a typical disease transmission model with another that captures certain aspects of the system that impact the outcomes of the main model. These existing methods provide critical insights in informing the design of HSM, and provide a departure point to extend this research agenda. We highlight the opportunity to advance modeling methods to further understand the dynamics between health system inputs and outputs.
全民健康覆盖（UHC）是联合国可持续发展目标 3 的目标之一。对 UHC 的推动导致对时间敏感工具的需求增加，以增强我们对卫生系统如何运作的了解，并评估系统干预措施的影响。我们将“卫生系统建模”（HSM）定义为一个研究领域，在这个领域中，可以设计动态数学模型，以描述、预测和定量捕捉卫生系统的功能。HSM 可用于探索不同系统组件之间的动态关系，包括组织设计、融资和其他资源（如资源投资和供应链管理系统）-我们称之为“投入”-对获取、覆盖和护理质量的影响-我们称之为“产出”，以改善卫生系统“结果”，即提高人口健康水平和金融风险保护的公平分配水平。我们进行了系统评价，以确定 HSM 中使用的现有方法。我们确定了“系统思维”-对卫生系统内部关键相互作用的概念性和定性描述-作为 HSM 的一个重要基础前体，并整理了这样的重要文章集。然后，我们从两种思想流派（系统动力学（SD）和“易感-感染-恢复加”（SIR+））回顾和分类文章。SD 强调系统中库存的积累、流入和流出以及因果反馈结构的概念，以预测政策干预的预期和意外后果。SIR+模型将典型的疾病传播模型与另一个模型联系起来，该模型捕获了影响主要模型结果的系统的某些方面。这些现有方法为 HSM 的设计提供了重要的见解，并为扩展这一研究议程提供了一个起点。我们强调有机会推进建模方法，以进一步了解卫生系统投入和产出之间的动态关系。
