MLTC-M Community of Practice in Statistical Methods for Multimorbidity Research

MLTC-M 多发病统计方法实践社区

• 批准号: MR/X004457/1
• 负责人: Richard Allen
• 金额: $ 5.01万
• 依托单位: University of Leicester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FX004457%2F1
• 关键词: MLTC; Community; Practice; Statistical; Methods

According to the NHS, two out of three of individuals aged over 65 have more than one long term health condition. Having two or more conditions, also known as multimorbidities, can cause complications as both conditions have to be taken into account when treating an individual. For example, we may want to give a patient a drug to treat one of their conditions but this treatment could potentially make their other conditions worse. Alternatively if someone is on two different drugs we don't always know how those drugs interact and whether having both drugs could cause adverse side effects. Medical research generally focuses on one condition at a time and therefore results from medical studies may not be applicable in practice where patients may have many other conditions. To tackle this problem a number of studies have recently been set up to investigate multimorbidities. These include exploring which conditions tend to occur together, investigating multimorbidities that lead to hospitalisation or identifying biological processes that cause similar diseases to occur throughout the body.There are a number of shared analytical methods that will be used in these studies and each study group contains specialists in cutting edge statistical techniques. We aim to set up a "Community of Practice" that will facilitate collaborations between these projects to ensure that the highest quality scientific methods are used for studying multimorbidities. This will allow expertise to be shared across the studies and to the wider scientific community. This community will hold regular meetings to share developments in the field, as well as providing a platform for early career researchers to present their work in a supportive and constructive environment. Workshops will allow small teams of experts to develop protocols for best practice that can be directly implemented in each of the studies. These results will also be shared amongst the wider scientific community through online repositories and video tutorials. There will be dedicated support for early career researchers to develop skills in applying these methods and for general career development. This community of practice will allow research into multimorbidities to be performed efficiently and to the highest standard to ensure the highest possible impact on patient outcomes.

根据NHS的数据，65岁以上的人中有三分之二有一种以上的长期健康状况。有两个或两个以上的条件，也被称为多病，可能会导致并发症，因为这两个条件都必须考虑到当治疗一个人。例如，我们可能想给病人一种药物来治疗他们的一种疾病，但这种治疗可能会使他们的其他疾病恶化。或者，如果有人服用两种不同的药物，我们并不总是知道这些药物如何相互作用，以及两种药物是否会导致不良副作用。医学研究通常集中在一个条件下的时间，因此从医学研究的结果可能不适用于实践中，病人可能有许多其他条件。为了解决这个问题，最近已经建立了一些研究来调查多发病。这些研究包括探索哪些疾病倾向于同时发生，调查导致住院的多病或确定导致全身发生类似疾病的生物过程。这些研究中将使用许多共享的分析方法，每个研究小组都包含尖端统计技术的专家。我们的目标是建立一个“实践社区”，促进这些项目之间的合作，以确保使用最高质量的科学方法来研究多发病。这将使专门知识能够在各项研究中分享，并与更广泛的科学界分享。该社区将定期举行会议，分享该领域的发展，并为早期职业研究人员提供一个平台，在支持性和建设性的环境中展示他们的工作。讲习班将使小型专家小组能够制定可在每项研究中直接实施的最佳做法议定书。这些成果也将通过在线知识库和视频教程在更广泛的科学界中分享。将专门支持早期职业研究人员发展应用这些方法的技能和一般职业发展。这个实践社区将允许对多病的研究有效地进行，并达到最高标准，以确保对患者结果产生最大可能的影响。