Epidemiologic measures and policy formulation: lessons from potential outcomes
Epidemiologic measures and policy formulation: lessons from potential outcomes
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DOI：
10.1186/1742-7622-2-5
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发表时间：
2005-05-27
影响因子：
2.3
通讯作者：
Greenland, Sander
中科院分区：
文献类型：
--
作者：
Greenland, Sander
本文对卫生政策文献中以牺牲干预分析为代价关注假设结果去除的常见做法进行了批评。本文首先介绍了潜在结果框架内的因果效应测量方法，重点介绍了与基于流行病学数据制定政策特别相关的基本概念模型、定义和缺陷。有人认为，出于政策目的，应在多变量结果框架内分析干预效果，以捕捉发病率和死亡率主要来源的影响。这一框架可以澄清人口健康汇总措施所捕获和遗漏的内容，并表明汇总措施的概念可以而且应该扩展到多维指数。
This paper provides a critique of the common practice in the health-policy literature of focusing on hypothetical outcome removal at the expense of intervention analysis. The paper begins with an introduction to measures of causal effects within the potential-outcomes framework, focusing on underlying conceptual models, definitions and drawbacks of special relevance to policy formulation based on epidemiologic data. It is argued that, for policy purposes, one should analyze intervention effects within a multivariate-outcome framework to capture the impact of major sources of morbidity and mortality. This framework can clarify what is captured and missed by summary measures of population health, and shows that the concept of summary measure can and should be extended to multidimensional indices.