Department of International Health, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St, E5541, Baltimore, MD, 21205, USA.
National Statistical Office, Zomba, Malawi.
Popul Health Metr. 2022 Sep 1;20(1):18. doi: 10.1186/s12963-022-00295-2.
Data that capture implementation strength can be combined in multiple ways across content and health system levels to create a summary measure that can help us to explore and compare program implementation across facility catchment areas. Summary indices can make it easier for national policymakers to understand and address variation in strength of program implementation across jurisdictions. In this paper, we describe the development of an index that we used to describe the district-level strength of implementation of Malawi's national family planning program.
To develop the index, we used data collected during a 2017 national, health facility and community health worker Implementation Strength Assessment survey in Malawi to test different methods to combine indicators within and then across domains (4 methods-simple additive, weighted additive, principal components analysis, exploratory factor analysis) and combine scores across health facility and community health worker levels (2 methods-simple average and mixed effects model) to create a catchment area-level summary score for each health facility in Malawi. We explored how well each model captures variation and predicts couple-years protection and how feasible it is to conduct each type of analysis and the resulting interpretability.
We found little difference in how the four methods combined indicator data at the individual and combined levels of the health system. However, there were major differences when combining scores across health system levels to obtain a score at the health facility catchment area level. The scores resulting from the mixed effects model were able to better discriminate differences between catchment area scores compared to the simple average method. The scores using the mixed effects combination method also demonstrated more of a dose-response relationship with couple-years protection.
The summary measure that was calculated from the mixed effects combination method captured the variation of strength of implementation of Malawi's national family planning program at the health facility catchment area level. However, the best method for creating an index should be based on the pros and cons listed, not least, analyst capacity and ease of interpretability of findings. Ultimately, the resulting summary measure can aid decision-makers in understanding the combined effect of multiple aspects of programs being implemented in their health system and comparing the strengths of programs across geographies.
能够捕捉实施力度的数据可以通过多种方式在内容和卫生系统层面进行组合,以创建一个总结性指标,帮助我们探索和比较各个设施服务区的项目实施情况。总结指标可以使国家政策制定者更容易理解和解决司法管辖区内项目实施力度的差异。在本文中,我们描述了一个指数的开发,我们用它来描述马拉维国家计划生育项目在地区一级的实施力度。
为了开发该指数,我们使用了 2017 年在马拉维进行的全国性卫生机构和社区卫生工作者实施力度评估调查中收集的数据,测试了在域内和跨域内组合指标的不同方法(4 种方法-简单加性、加权加性、主成分分析、探索性因子分析),并在卫生机构和社区卫生工作者层面上组合分数(2 种方法-简单平均值和混合效应模型),为马拉维的每个卫生机构创建一个服务区的总结分数。我们探讨了每种模型在捕捉变异和预测夫妇年保护方面的表现,以及每种分析类型的可行性和由此产生的可解释性。
我们发现,在组合卫生系统个体和综合层面上的指标数据方面,这四种方法的差异不大。然而,当组合卫生系统层面的分数以获得卫生机构服务区层面的分数时,差异很大。与简单平均值方法相比,混合效应模型产生的分数能够更好地区分服务区分数之间的差异。使用混合效应组合方法的分数也表现出与夫妇年保护更显著的剂量-反应关系。
从混合效应组合方法计算得出的总结性衡量标准在卫生机构服务区层面上捕捉了马拉维国家计划生育项目实施力度的变化。然而,创建指数的最佳方法应该基于列出的优缺点,尤其是分析员的能力和发现结果的可解释性。最终,这个总结性衡量标准可以帮助决策者了解他们的卫生系统中实施的多个项目的综合效果,并比较不同地理位置的项目的实施力度。