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首页> 外文期刊>International Journal of Environmental Research and Public Health >Combining Theory-Driven Evaluation and Causal Loop Diagramming for Opening the ‘Black Box’ of an Intervention in the Health Sector: A Case of Performance-Based Financing in Western Uganda
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Combining Theory-Driven Evaluation and Causal Loop Diagramming for Opening the ‘Black Box’ of an Intervention in the Health Sector: A Case of Performance-Based Financing in Western Uganda

机译:将理论驱动的评估与因果图相结合,以打开卫生部门干预活动的“黑匣子”:乌干达西部基于绩效的融资案例

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Increased attention on “complexity” in health systems evaluation has resulted in many different methodological responses. Theory-driven evaluations and systems thinking are two such responses that aim for better understanding of the mechanisms underlying given outcomes. Here, we studied the implementation of a performance-based financing intervention by the Belgian Technical Cooperation in Western Uganda to illustrate a methodological strategy of combining these two approaches. We utilized a systems dynamics tool called causal loop diagramming (CLD) to generate hypotheses feeding into a theory-driven evaluation. Semi-structured interviews were conducted with 30 health workers from two districts (Kasese and Kyenjojo) and with 16 key informants. After CLD, we identified three relevant hypotheses: “success to the successful”, “growth and underinvestment”, and “supervision conundrum”. The first hypothesis leads to increasing improvements in performance, as better performance leads to more incentives, which in turn leads to better performance. The latter two hypotheses point to potential bottlenecks. Thus, the proposed methodological strategy was a useful tool for identifying hypotheses that can inform a theory-driven evaluation. The hypotheses are represented in a comprehensible way while highlighting the underlying assumptions, and are more easily falsifiable than hypotheses identified without using CLD.
机译:卫生系统评价中对“复杂性”的日益关注导致了许多不同的方法论回应。理论驱动的评估和系统思考就是两个这样的响应,旨在更好地理解给定结果所基于的机制。在这里,我们研究了比利时技术合作公司在乌干达西部实施的基于绩效的融资干预措施,以说明结合这两种方法的方法论策略。我们利用了一种称为因果回路图(CLD)的系统动力学工具来生成假设,并将其馈入理论驱动的评估中。对来自两个地区(Kasese和Kyenjojo)的30名卫生工作者以及16名主要信息提供者进行了半结构化访谈。在CLD之后,我们确定了三个相关的假设:“成功的成功”,“增长和投资不足”以及“监管难题”。第一个假设导致绩效的提高,因为更好的绩效会导致更多的激励,进而会导致更好的绩效。后两个假设指出了潜在的瓶颈。因此,所提出的方法论策略是一种有用的工具,可用于识别可以为理论驱动的评估提供依据的假设。假设以突出的基本假设以可理解的方式表示,并且比不使用CLD识别的假设更容易证伪。

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