From raw data to a score: comparing quantitative methods that construct multi-level composite implementation strength scores of family planning programs in Malawi.

IF 3.2 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Anooj Pattnaik, Diwakar Mohan, Scott Zeger, Mercy Kanyuka, Fannie Kachale, Melissa A Marx
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引用次数: 1

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

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从原始数据到分数:比较构建马拉维计划生育方案多层次复合执行强度分数的定量方法。
背景:捕获实施强度的数据可以跨内容和卫生系统级别以多种方式组合在一起,以创建一个总结性衡量标准,帮助我们探索和比较跨设施集水区的项目实施情况。摘要指数可以使国家政策制定者更容易了解和解决不同司法管辖区计划实施力度的差异。在本文中,我们描述了一个指数的发展,我们用来描述马拉维国家计划生育方案的地区一级执行力度。方法:为了开发该指数,我们使用了2017年马拉维国家卫生机构和社区卫生工作者实施强度评估调查期间收集的数据,以测试不同的方法来组合领域内和跨领域的指标(4种方法:简单相加、加权相加、主成分分析、探索性因素分析),并将卫生机构和社区卫生工作者各级的得分结合起来(两种方法——简单平均和混合效应模型),为马拉维的每个卫生机构创建集水区一级的综合得分。我们探索了每个模型捕获变化和预测几年保护的程度,以及进行每种类型的分析和结果的可解释性的可行性。结果:我们发现四种方法在卫生系统个体水平和综合水平上结合指标数据的方式差异不大。然而,在综合卫生系统各级的得分以获得卫生设施集水区一级的得分时,存在重大差异。与简单平均法相比,混合效应模型得到的分数能够更好地区分集水区分数之间的差异。使用混合效应组合方法的评分也显示出更多的剂量-反应关系与两年的保护。结论:采用混合效应组合法计算得出的综合衡量指标反映了马拉维国家计划生育方案在卫生设施集水区一级实施力度的变化情况。然而,创建索引的最佳方法应该基于所列出的优点和缺点,尤其是分析人员的能力和结果的可解释性。最终,由此产生的总结测量可以帮助决策者了解在其卫生系统中实施的规划的多个方面的综合效果,并比较不同地区规划的优势。
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来源期刊
Population Health Metrics
Population Health Metrics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
6.50
自引率
0.00%
发文量
21
审稿时长
29 weeks
期刊介绍: Population Health Metrics aims to advance the science of population health assessment, and welcomes papers relating to concepts, methods, ethics, applications, and summary measures of population health. The journal provides a unique platform for population health researchers to share their findings with the global community. We seek research that addresses the communication of population health measures and policy implications to stakeholders; this includes papers related to burden estimation and risk assessment, and research addressing population health across the full range of development. Population Health Metrics covers a broad range of topics encompassing health state measurement and valuation, summary measures of population health, descriptive epidemiology at the population level, burden of disease and injury analysis, disease and risk factor modeling for populations, and comparative assessment of risks to health at the population level. The journal is also interested in how to use and communicate indicators of population health to reduce disease burden, and the approaches for translating from indicators of population health to health-advancing actions. As a cross-cutting topic of importance, we are particularly interested in inequalities in population health and their measurement.
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