Division of Social and Behavioural Sciences, School of Public Health and Family Medicine, University of Cape Town, Falmouth Road, Observatory 7925, Cape Town, South Africa.
Department of Health Policy, London School of Economics and Political Science, Houghton Street, London WC2A 2AE, England, United Kingdom.
Health Policy Plan. 2022 Oct 12;37(9):1177-1187. doi: 10.1093/heapol/czac059.
To better understand and plan health systems featuring multiple levels and complex causal elements, there have been increasing attempts to incorporate tools arising from complexity science to inform decisions. The utilization of new planning approaches can have important implications for the types of evidence that inform health policymaking and the mechanisms through which they do so. This paper presents an empirical analysis of the application of one such tool-system dynamics modelling (SDM)-within a tuberculosis control programme in South Africa in order to explore how SDM was utilized, and to reflect on the implications for evidence-informed health policymaking. We observed group model building workshops that served to develop the SDM process and undertook 19 qualitative interviews with policymakers and practitioners who partook in these workshops. We analysed the relationship between the SDM process and the use of evidence for policymaking through four conceptual perspectives: (1) a rationalist knowledge-translation view that considers how previously-generated research can be taken up into policy; (2) a programmatic approach that considers existing goals and tasks of decision-makers, and how evidence might address them; (3) a social constructivist lens exploring how the process of using an evidentiary planning tool like SDM can shape the understanding of problems and their solutions; and (4) a normative perspective that recognizes that stakeholders may have different priorities, and thus considers which groups are included and represented in the process. Each perspective can provide useful insights into the SDM process and the political nature of evidence use. In particular, SDM can provide technical information to solve problems, potentially leave out other concerns and influence how problems are conceptualized by formalizing the boundaries of the policy problem and delineating particular solution sets. Undertaking the process further involves choices on stakeholder inclusion affecting whose interests may be served as evidence to inform decisions.
为了更好地理解和规划具有多层次和复杂因果要素的卫生系统，越来越多的人试图将复杂性科学工具应用于决策。新规划方法的利用可能会对为卫生决策提供信息的证据类型以及它们的作用机制产生重要影响。本文通过南非结核病控制规划中系统动力学建模（SDM）的应用实例，分析了一种工具的应用，目的是探讨 SDM 的应用方式，并思考其对循证卫生决策制定的影响。我们观察了用于开发 SDM 过程的小组建模研讨会，并对参与这些研讨会的政策制定者和实践者进行了 19 次定性访谈。我们通过四个概念视角分析了 SDM 过程与循证决策之间的关系：（1）理性主义知识转化视角，考虑如何将已产生的研究纳入政策；（2）方案方法，考虑决策者的现有目标和任务，以及证据如何解决这些问题；（3）社会建构主义视角，探讨使用 SDM 等证据规划工具的过程如何影响对问题及其解决方案的理解；（4）规范视角，承认利益相关者可能有不同的优先事项，因此考虑哪些群体在过程中被包括和代表。每个视角都可以为 SDM 过程和证据使用的政治性提供有用的见解。特别是，SDM 可以提供解决问题的技术信息，可能会忽略其他问题，并通过正式划定政策问题的边界和划定特定的解决方案集来影响问题的概念化方式。进行该过程还涉及到利益相关者参与的选择，这会影响谁的利益可能被视为决策依据。
