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Improving LQAS for monitoring and evaluation of health programs in resource-poor settings.

机译：改进用于监测和评估资源匮乏地区卫生计划的LQAS。

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摘要

Originally used for industrial quality control, lot quality assurance sampling (LQAS) has become an increasingly popular tool for decentralized monitoring and evaluation (M&E) of health programs in resource-poor settings. In this thesis, we present new methods to improve upon existing practices in LQAS.;A review of LQAS is presented in the first chapter. It is intended both to establish clear operational principles for its use as an evaluation tool and to clarify a number of misconceptions which have become commonplace in the literature.;The second chapter is concerned with two innovations in LQAS motivated by specific applications in health. The first of these involves extending the traditional LQAS tool for two-way classification to three categories in order to handle the problem of intestinal schistosomiasis in schoolchildren. The second discusses the integration of cluster sampling and LQAS to assess the burden of global acute malnutrition (GAM) in children.;The following chapter is devoted to Bayes-LQAS ( B-LQAS) to allow the incorporation of prior beliefs into the classification procedure. Ultimately, we cast the B-LQAS problem in the decision theoretic framework, considering both zero-one and piecewise linear utility functions. We focus on choosing LQASdesigns, consisting of the sample size and decision rule, under a range of assumed prior distributions. Using data from Mandera District, Kenya, we show that strong prior information indicating high levels of GAM prevalence suggests that decision rules should be modified to achieve maximum expected utility. We also discuss multiple classification in the Bayesian framework. Returning to schistosomiasis, we show how to appropriately incorporate prior beliefs when performing three-way classification.;The last chapter is focused on the use of LQAS for routine M&E of health programs. An adaptive Bayesian approach to choosing decision rules over the course of a finite time horizon is presented. Data collected over the course of seven time points in Bara District, Nepal on competency to prepare oral rehydration therapy are considered, and these results indicate that optimal designs are dependent on data trends and are less sensitive to the choice of LQAS design.
机译：批次质量保证抽样（LQAS）最初用于工业质量控制，已成为资源匮乏环境中卫生计划的分散监视和评估（M＆E）的一种越来越流行的工具。在本文中，我们提出了新的方法来改进LQAS的现有实践。;第一章对LQAS进行了综述。它既旨在建立明确的操作原则以用作评估工具，又可以澄清许多误解，这些误解在文献中已变得司空见惯。第二章是关于LQAS的两项创新，这些创新是由健康中的特定应用所激发的。其中的第一步涉及将用于双向分类的传统LQAS工具扩展到三个类别，以解决小学生的肠道血吸虫病问题。第二部分讨论了整群抽样和LQAS的集成以评估儿童的全球急性营养不良（GAM）的负担。;下一章专门讨论Bayes-LQAS（B-LQAS），以便将先前的信念纳入分类程序。最终，我们将B-LQAS问题转换为决策理论框架，同时考虑了零一和分段线性效用函数。我们专注于在一系列假定的先验分布下选择由样本量和决策规则组成的LQASdesigns。使用来自肯尼亚曼德拉区的数据，我们显示出有力的先验信息表明GAM流行率很高，这表明应该修改决策规则，以实现最大的预期效用。我们还讨论了贝叶斯框架中的多个分类。回到血吸虫病，我们展示了在进行三向分类时如何适当地整合先前的信念。上一章着重于将LQAS用于健康计划的常规M＆E。提出了一种在有限时间范围内选择决策规则的自适应贝叶斯方法。考虑了在尼泊尔巴拉地区七个时间点上收集的有关准备口服补液治疗能力的数据，这些结果表明最佳设计取决于数据趋势，并且对LQAS设计的选择不那么敏感。

著录项

  • 作者

    Olives, Casey Stevens.;

  • 作者单位

    Harvard University.;

  • 授予单位 Harvard University.;
  • 学科 Biology Biostatistics.;Statistics.;Health Sciences Public Health.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 138 p.
  • 总页数 138
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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