Methods for the Indirect estimation of health state utilities

健康状态效用的间接估计方法

• 批准号: G0901490/1
• 负责人: Christopher McCabe
• 金额: $ 24.84万
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2010
• 资助国家: 英国
• 起止时间: 2010 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=G0901490%2F1
• 关键词: Methods; Indirect; estimation; health; state

Decisions made by NICE on the use of treatments in the NHS are based on the evidence for both clinical and cost-effectiveness. The methods used by NICE include the quality adjusted life year (QALY) which is a measure of both the length and quality of life gained from a treatment. A QALY can be measured using a health related quality of life questionnaire. But information from these sorts of questionnaires is not always available and often must be inferred from another source. This research aims to improve the methods used for making such inferences (often referred to as mapping) by reducing bias in the estimates that are produced and accurately describing how uncertain these estimates are. We aim to achieve our objectives in three ways. First, we will look at how closely each instrument of health related quality of life measures the same domains, or aspects of health. This will help us determine the degree to which mapping from one instrument to the other will be reliable. We will then examine ways in which we can make more explicit the uncertainty in the estimates that arise from mapping between instruments. Finally, we will look at ways that we can combine information from both instruments to improve the mapping process. To conduct our research we will be using a range of existing data sets. These data sets contain information about a number of different instruments for measuring health related quality of life. These instruments are the EQ-5D, EQ-5D Child friendly version, SF-36, EORTC-QLQ30, KIDSCREEN26 and HUI2. The data in these data sets has been collected for a number of different studies, including the Health Survey for England 1996 and clinical trials for the treatment of cancer. No new data will be collected, all patient data will be anonymised and unlinked so that no individuals can be identified and ethical approval will be sought as appropriate before any data is used. As a result of this research we will develop a tool kit for researchers to use when making inferences about health related quality of life data from alternative sources. We will also work to promote the understanding of these methods to the public to improve the transparency of NICE?s decision making processes.

NICE关于在NHS中使用治疗的决定是基于临床和成本效益的证据。NICE使用的方法包括质量调整生命年（QALY），这是从治疗中获得的生命长度和质量的衡量标准。QALY可以使用健康相关的生活质量问卷来测量。但来自此类调查问卷的信息并不总是可用，通常必须从另一个来源推断。本研究旨在通过减少产生的估计值的偏差并准确描述这些估计值的不确定性来改进用于进行此类推断（通常称为映射）的方法。我们打算通过三种方式实现我们的目标。首先，我们将研究与健康相关的生活质量的每种工具如何密切测量健康的相同领域或方面。这将帮助我们确定从一台仪器到另一台仪器的映射的可靠程度。然后，我们将研究如何更明确地说明由工具之间的映射引起的估计中的不确定性。最后，我们将研究如何将两种仪器的信息联合收割机结合起来，以改进绘图过程。为了进行研究，我们将使用一系列现有的数据集。这些数据集包含了一些不同的测量与健康有关的生活质量的工具的信息。这些工具是EQ-5D、EQ-5D儿童友好版、SF-36、EORTC-QLQ 30、KIDSCREEN 26和HUI 2。这些数据集中的数据是为许多不同的研究收集的，包括1996年英格兰健康调查和癌症治疗的临床试验。将不会收集新数据，所有患者数据将匿名和解除链接，以便无法识别任何个人，并在使用任何数据之前酌情寻求伦理批准。作为这项研究的结果，我们将开发一个工具包，供研究人员使用时，从替代来源的健康相关的生活质量数据进行推断。我们还将努力向公众宣传这些方法，以提高NICE的透明度。的决策过程。