DEVELOPING APPROPRIATE ANALYTICAL METHODS FOR COST-EFFECTIVENESS ANALYSES THAT USE CLUSTER RANDOMISED TRIALS

开发适当的分析方法以使用整群随机试验进行成本效益分析

基本信息

项目摘要

In all societies, people recognise the importance of improving the population?s health, but there are limits on how much we are prepared to spend on health care. Organisations such as NICE, help decide which health care options (e.g. new drugs or doctors) represent the best value for money. NICE make their recommendations, based on studies that consider the relative costs of different options, but also how much they improve people?s health. However, there are concerns about the scientific quality of these studies. One way of collecting the evidence is through a study called a ?cluster randomised trial?. This study is specially designed to try and give accurate results. However, for the study to provide accurate results it is also essential that it uses appropriate methods of analysis. Studies that have used these ?cluster randomised trials? to assess costs and outcomes have not used appropriate methods to report their results. A key feature of this study is that which drug or service a patient receives depends on which cluster (e.g. a hospital) they attend. However, these studies have not recognised that patients who are in particular cluster (e.g. a hospital) are likely to be more similar (for example in their social background) to each other, than to patients attending other hospitals. A big concern is that by using these methods which are inappropriate, the studies are providing inaccurate results. This research will develop careful scientific methods for studies that compare costs and health outcomes using these ?cluster randomised trials?. It will find out which of these new methods is the best by carefully considering them in different situations. We will take studies that have already provided results, and redo them using these new methods. We will test the methods across different medical areas (e.g. maternity services, heart disease, sleeping disorders). The research will provide recommendations on which method is best under different circumstances. The study will provide instructions and training opportunities to teach future researchers how to use these new methods. The investigation will produce scientific publications for international journals. We will also provide information on the methods for policy-makers, and members of the public via our project website. By providing better methods for deciding which drugs and health services should be provided, this research will help to ensure that scarce health care resources are used in the best ways for improving the population s health.
在所有社会中,人们都认识到改善人口的重要性。我们的健康状况很好,但我们准备在医疗保健上花费的金额是有限的。NICE等组织帮助决定哪些医疗保健选择(例如新药或医生)代表最佳性价比。NICE提出他们的建议,基于研究,考虑不同选择的相对成本,但也有多少他们改善人?的健康。然而,人们对这些研究的科学质量表示担忧。收集证据的一种方法是通过一项名为"一个?群集随机试验。这项研究是专门设计的,试图给出准确的结果。然而,为了使研究提供准确的结果,使用适当的分析方法也是至关重要的。使用这些的研究?群集随机试验?评估成本和成果的工作没有使用适当的方法报告其结果。这项研究的一个关键特征是,患者接受的药物或服务取决于他们参加的集群(例如医院)。然而,这些研究并没有认识到,在特定的集群(例如,一家医院)中的患者可能比在其他医院就诊的患者更相似(例如,在他们的社会背景中)。一个很大的问题是,通过使用这些不适当的方法,研究提供了不准确的结果。这项研究将开发仔细的科学方法,比较成本和健康结果的研究,使用这些?群集随机试验?通过在不同的情况下仔细考虑这些新方法,它会发现哪种方法是最好的。我们将采用已经提供结果的研究,并使用这些新方法重新进行研究。我们将在不同的医疗领域(如产科服务,心脏病,睡眠障碍)测试这些方法。该研究将提供关于在不同情况下哪种方法最好的建议。这项研究将提供指导和培训机会,教未来的研究人员如何使用这些新方法。调查将为国际期刊提供科学出版物。我们还将通过我们的项目网站向政策制定者和公众提供有关方法的信息。通过提供更好的方法来决定应该提供哪些药物和卫生服务,这项研究将有助于确保稀缺的卫生保健资源以最佳方式用于改善人口的健康。

项目成果

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Richard Grieve其他文献

Complier-average causal effects for multivariate outcomes: an instrumental variable approach with application to health economics
  • DOI:
    10.1186/1745-6215-16-s2-o44
  • 发表时间:
    2015-11-16
  • 期刊:
  • 影响因子:
    2.000
  • 作者:
    Karla DiazOrdaz;Angelo Franchini;Richard Grieve
  • 通讯作者:
    Richard Grieve
Correction to: Impact on mortality of prompt admission to critical care for deteriorating ward patients: an instrumental variable analysis using critical care bed strain
  • DOI:
    10.1007/s00134-018-5254-1
  • 发表时间:
    2018-05-01
  • 期刊:
  • 影响因子:
    21.200
  • 作者:
    Steve Harris;Mervyn Singer;Colin Sanderson;Richard Grieve;David Harrison;Kathryn Rowan
  • 通讯作者:
    Kathryn Rowan
USE OF EVIDENCE-BASED PREVENTIVE MEDICAL THERAPIES 1-3 YEARS POST-MYOCARDIAL INFARCTION IN THE PROSPECTIVE GLOBAL TIGRIS REGISTRY
  • DOI:
    10.1016/s0735-1097(19)30777-6
  • 发表时间:
    2019-03-12
  • 期刊:
  • 影响因子:
  • 作者:
    Dirk Westermann;David Brieger;Timothy Collier;Stuart J. Pocock;Mauricio G. Cohen;Shaun G. Goodman;Christopher B. Granger;Richard Grieve;Jose C. Nicolau;Tabassome Simon;Satoshi Yasuda;Gunnar Brandrup-Wognsen;Kirsten L. Rennie;Karolina Andersson Sundell;Ji Yan Chen
  • 通讯作者:
    Ji Yan Chen
Cost-Effectiveness and Resource Allocation (CERA) – directions for the future
  • DOI:
    10.1186/1478-7547-7-14
  • 发表时间:
    2009-07-23
  • 期刊:
  • 影响因子:
    2.500
  • 作者:
    Rob Baltussen;Arnab Acharya;Kathryn Antioch;Dan Chisholm;Richard Grieve;Joses Kirigia;Tessa Tan Torres-Edejer;Damian G Walker;David Evans
  • 通讯作者:
    David Evans
189 Does living in a rural area reduce access to cancer treatment more for ethnic minorities? A population-based study on treatment for early stage non-small-cell lung cancer (NSCLC)
居住在农村地区是否会更多地减少少数民族获得癌症治疗的机会?一项基于人群的早期非小细胞肺癌(NSCLC)治疗研究
  • DOI:
    10.1016/j.lungcan.2025.108298
  • 发表时间:
    2025-02-01
  • 期刊:
  • 影响因子:
    4.400
  • 作者:
    Eva Kagenaar;David Lugo-Palacios;Richard Grieve;Andrew Hutchings;Ajay Aggarwal;Stephen O'Neill;Bernard Rachet;Corinne Faivre-Finn;John Edwards
  • 通讯作者:
    John Edwards

Richard Grieve的其他文献

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{{ truncateString('Richard Grieve', 18)}}的其他基金

HOD2: Instrumental Variable approaches for estimating heterogeneity of treatment effects to inform personalisation using electronic health records
HOD2:用于估计治疗效果异质性的工具变量方法,以使用电子健康记录为个性化提供信息
  • 批准号:
    MR/T025212/1
  • 财政年份:
    2021
  • 资助金额:
    $ 46.63万
  • 项目类别:
    Research Grant
Improving analytical methods for reducing selection bias in health economic evaluation
改进分析方法以减少卫生经济评估中的选择偏差
  • 批准号:
    ES/G00188X/1
  • 财政年份:
    2009
  • 资助金额:
    $ 46.63万
  • 项目类别:
    Research Grant

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