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Evaluating Health Interventions Over Time: Empirical Tests of the Validity of the Single Interrupted Time Series Design.

机译：评估随时间变化的健康干预措施：单次中断时间序列设计有效性的经验检验。

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摘要

Single interrupted time series (ITS) is a quasi-experimental evaluation design used frequently in the health policy literature. This manuscript investigates the validity of single ITS through two within-study comparisons (WSCs), comparing the results of a randomized controlled trial (RCT) with the results that would have been obtained had a single ITS design been employed.;In Part 1, I discuss the theory underlying both within-study comparisons and single ITS. I propose an assessment framework to determine whether results from a given design should be deemed "concordant" with an RCT for a given intervention. This framework aims to unify metrics for concordance used in the existing literature, and considers both practical and statistical significance. After summarizing best practices of single ITS analysis, I propose two falsification tests to determine whether the single ITS design is well suited for the trend stability of a particular dataset. These tests draw from literature on determining structural breaks in time series data, as well as work on the optimal binning of data in the regression discontinuity design.;In Part 2, I conduct two within-study comparisons for single ITS. The first study evaluates a behavior change campaign in Uganda aimed at increasing uptake of rapid diagnostic tests for malaria. The WSC finds that single ITS estimates are highly concordant with that of the RCT, producing almost identical results in both point estimate and standard error. This result is robust to multiple specifications. The second study evaluates the effect of the expansion of Medicaid on emergency department use in Oregon. In this case, the single ITS estimates are so discordant with the RCT as to produce statistically significant results in the wrong direction. This result is also robust to multiple specification decisions.;In comparing these differing results, I note important differences between the two datasets. The Uganda data passed the falsification tests for trend stability proposed in Part 1, while the Oregon data failed. Additionally, the Oregon sample is likely subject to a manifestation of self-selection known as "Ashenfelter's dip," whereas the Uganda sample is not. The implication of this shift in outcomes just before the intervention's introduction is especially damaging to single ITS, in comparison to traditionally "weaker" pre-post designs.;In Part 3, I attempt to generate hypotheses as to when single ITS should and should not be used. First, samples defined by self-selection are particularly problematic for single ITS analysis. Second, the advantages of relying on time trends must be weighed against the additional strong assumptions that the single ITS design carries with it. Third, trend stability in the pre period is a crucial factor in getting reliable estimates from single ITS. Fourth, the robustness of results in both WSCs suggests that whether to evaluate a given program with a single ITS design is a more important decision than how to implement ITS.
机译：单次中断时间序列（ITS）是卫生政策文献中经常使用的准实验评估设计。该手稿通过两次研究内比较（WSC）来研究单个ITS的有效性，将随机对照试验（RCT）的结果与采用单个ITS设计获得的结果进行了比较;在第1部分中，我将讨论研究内比较和单个ITS的基础理论。我提出了一个评估框架，以确定对于给定的干预措施，是否应将给定设计的结果与RCT视为“一致”。该框架旨在统一现有文献中使用的一致性指标，并同时考虑实际和统计意义。在总结了单个ITS分析的最佳实践之后，我提出了两个伪造测试，以确定单个ITS设计是否非常适合特定数据集的趋势稳定性。这些测试来自有关确定时间序列数据的结构性断裂的文献，以及在回归不连续性设计中对数据的最佳分类的研究。在第2部分中，我对单个ITS进行了两次研究内比较。第一项研究评估了乌干达的一项行为改变运动，旨在增加对疟疾的快速诊断测试的吸收。 WSC发现，单个ITS估计与RCT高度一致，在点估计和标准误上产生几乎相同的结果。该结果对多种规格均具有鲁棒性。第二项研究评估了医疗补助计划的扩展对俄勒冈州急诊部门使用的影响。在这种情况下，单个ITS估算值与RCT不一致，从而在错误的方向上产生了统计上显着的结果。该结果对于多个规格决策也很可靠。在比较这些不同的结果时，我注意到两个数据集之间的重要差异。乌干达数据通过了第1部分中提议的趋势稳定性伪造测试，而俄勒冈数据则失败了。此外，俄勒冈州的样本很可能会经历自我选择的表现，即“灰身大战”，而乌干达的样本则没有。与传统的“较弱的”事前设计相比，在干预措施引入之前，这种结果转移的隐含尤其会对单个ITS造成损害。；在第3部分中，我试图就单个ITS何时应该和不应该何时生成假设。使用。首先，对于单ITS分析，通过自选定义的样本尤其成问题。其次，必须权衡依赖于时间趋势的优势和单个ITS设计所附带的其他强有力的假设。第三，前期的趋势稳定性是从单个ITS获得可靠估计的关键因素。第四，两个WSC中结果的稳健性表明，是否使用单个ITS设计评估给定程序是比如何实施ITS更重要的决定。

著录项

  • 作者

    Svoronos, Theodore.;

  • 作者单位

    Harvard University.;

  • 授予单位 Harvard University.;
  • 学科 Public health.;Statistics.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 103 p.
  • 总页数 103
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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