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强化疾病管理有效性的理由:揭示隐藏的偏见。

Strengthening the case for disease management effectiveness: un-hiding the hidden bias.

作者信息

Linden Ariel, Adams John L, Roberts Nancy

机构信息

Linden Consulting Group, Portland, OR 97124, USA.

出版信息

J Eval Clin Pract. 2006 Apr;12(2):140-7. doi: 10.1111/j.1365-2753.2005.00612.x.

Abstract

As is the case with most health care program evaluations, disease management (DM) programs typically follow an observational study design, indicating that randomization to treatment or control was not performed. The foremost limitation of observational studies, compared to randomized studies, is that the only biases that can be controlled for are those associated with observed variables. Hidden bias refers to all those unobserved covariates that may distort the conclusions of the study. This paper introduces a sensitivity analysis that is used to determine the magnitude of hidden bias necessary to alter the conclusion that a DM program intervention was indeed effective.

摘要

与大多数医疗保健项目评估一样,疾病管理(DM)项目通常采用观察性研究设计,这意味着未进行治疗或对照的随机分组。与随机研究相比,观察性研究的首要局限性在于,唯一可以控制的偏差是那些与观察变量相关的偏差。隐藏偏差是指所有那些可能扭曲研究结论的未观察到的协变量。本文介绍了一种敏感性分析方法,用于确定改变疾病管理项目干预确实有效的结论所需的隐藏偏差的大小。

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