ADMISSION UK Multimorbidity Research Collaborative on Multiple Long-Term Conditions in Hospital: from burden and inequalities to underlying mechanisms

为什么多变量很重要？多发病，即患有多种长期健康状况，在住院患者中非常常见。这些患者往往住院时间更长，更有可能死亡，出院时可能需要更长的时间才能恢复。然而，我们为患有多种长期疾病的人提供护理的方式并不理想;在为单一疾病设计的系统中，护理对患者来说可能不令人满意且效率低下-并且对于医疗保健提供者来说昂贵，如NHS。改进的必要性是公认的，但目前很少有研究在医院的病人，以帮助我们知道如何服务需要改变。我们的研究旨在解决这一认识上的差距，并专注于患有多种长期疾病的住院患者。什么是入院？我们已经成立了一个新的研究合作（称为ADMISSION），其中包括来自英国大学（纽卡斯尔，伯明翰，曼彻斯特大都会，伦敦大学学院，邓迪）的数据科学家，统计学家，实验室研究人员，社会科学家和临床团队，以开展研究，这将改变我们对医院患者多种长期疾病的理解。通过汇集这些专业知识，我们将能够利用“大数据”（来自常规NHS和其他数据集）的力量，更好地了解多种长期疾病的模式和原因，以及与它们一起生活的影响。该协作将使用英格兰东北部、伯明翰和邓迪的医院以及英国各地重症监护病房收集的信息，以识别患有长期疾病的患者。我们将特别关注那些同时患有身体健康状况（例如心脏病、肺病、关节炎、福尔斯和行动不便）和心理健康状况（例如痴呆和抑郁）的患者。我们计划的研究分为五个相互关联的工作包，每个工作包都有助于其他工作包的工作。我们的第一个工作包将建立一个从纽卡斯尔医院收集的信息库，并将其与英国伯明翰医院和重症监护室的类似信息库进行比较。我们的第二个工作包将分析这些信息，以发现健康状况的模式，因为这些模式往往聚集在一起，这样我们就可以看到年龄，性别和种族等背景因素对它们的影响（在我们的第三个工作包中）。我们的第四个工作包将使用来自救护车服务，事故和紧急情况，急性入院和全科医生记录的信息，以了解我们如何为患有多种长期疾病的人群提供医疗保健，他们如何通过医疗保健系统以及我们如何能够改善他们的健康和社会护理体验。我们的最终工作包着眼于可以解释导致长期疾病集群的机制;我们将分析来自50万人的遗传和其他信息，这些人签署了英国生物银行研究，以了解基因在不同的条件集群之间如何变化，然后使用从SHARE苏格兰登记处收集的3000名医院患者的血液样本来测试这些想法。录取的最终结果会是什么？这项工作将导致我们对长期疾病如何在医院患者中聚集在一起，为什么它们聚集在一起，以及这些不同的集群如何影响健康和医疗保健服务的理解发生重大变化。有了这样的理解，我们将能够设计新的方法来治疗和预防多种长期疾病，并改善患有这些疾病的人的健康、功能和生活质量。它还将为卫生和社会保健系统的重新设计提供信息，以便它们能够在未来更好地照顾患有多种长期疾病的患者。

Why is multimorbidity important?Multimorbidity, that is living with multiple long-term health conditions, is very common in people admitted to hospital. These patients tend to stay in hospital for longer, are more likely to die, and may take much longer to recover when they are discharged. However, the way we deliver care for people with multiple long-term conditions is not ideal; in a system that was designed for single conditions, care can be unsatisfactory and inefficient for the patient - and is expensive for the healthcare provider, such as the NHS. The need for improvement is recognised, but there is currently little research on multimorbidity in hospital patients to help us to know how services need to be changed. Our research is designed to address this gap in understanding and is focused on people with multiple long-term conditions who are admitted to hospital.What is ADMISSION?We have formed a new Research Collaborative (called ADMISSION) that includes data scientists, statisticians, laboratory researchers, social scientists and clinical teams from UK universities (Newcastle, Birmingham, Manchester Met, UCL, Dundee) to carry out research that will transform our understanding of multiple long-term conditions in hospital patients. By bringing together this expertise we will be able to use the power of 'big data' (from routine NHS and other datasets) to better understand the patterns and causes of multiple long-term conditions, and the effects of living with them. The Collaborative will use information collected by hospitals in the North East of England, Birmingham and Dundee, and from intensive care wards across the UK, to identify patients with long-term conditions. We will pay particular attention to patients who have a combination of physical health conditions (for example heart disease, lung disease, arthritis, falls and poor mobility) and mental health conditions (for example dementia and depression).What will ADMISSION do?Our planned research is divided into five linked work packages, with each helping the work of the others. Our first work package will build a library of information gathered from Newcastle Hospitals and will compare this with similar libraries of information from Birmingham hospitals and intensive care units across the UK. Our second work package will analyse this information to find patterns of health conditions as these tend to cluster together, so that we can look at the effects of background factors such as age, sex, and ethnicity on them (in our third work package). Our fourth work package will use information from ambulance services, accident and emergency, acute hospital admissions and general practice records to understand how we deliver health care to people with clusters of multiple long-term conditions, how they journey through the healthcare system and how we might be able to improve their experience of health and social care. Our final work package looks at the mechanisms that could explain what causes the clusters of long-term conditions; we will analyse genetic and other information from half a million people who signed up to the UK Biobank study to find out how genes vary between different clusters of conditions, and then test these ideas using blood samples collected from 3000 hospital patients in the SHARE Scotland registry. What will the end result of ADMISSION be?This work will lead to a step change in our understanding of how long-term conditions cluster together in hospital patients, why they cluster, and how these different clusters affect health and the delivery of health care. With this understanding we will be able to design new approaches to treat and prevent multiple long-term conditions, and to improve the health, function and quality of life of people who have them. It will also inform the redesign of health and social care systems so that they are better able to care for patients with multiple long-term conditions in the future.