The Care Life Cycle: Responding to the Health and Social Care Needs of an Ageing Society

英国的人口正在老龄化，这对政府来说是一个重大问题，因为老年人是卫生和社会保健服务的主要使用者。随着卫生人力本身的老龄化，人口老龄化不仅增加了对护理的需求，还影响到护理专业人员的供应。然而，老龄化只是影响保健和社会护理供应和需求的一系列复杂问题中的一个因素。这些因素包括残疾和疾病状况的变化、新技术的发展以及收入和财富水平的变化。劳动力受到许多人口、政治和经济因素的影响。人们经常强调预测未来卫生人力的挑战，但迄今为止还没有研究全面处理卫生和社会保健的需求和供应方面的问题。要实现这一点，需要的不仅仅是简单地将不同子系统的模型加在一起——重要的是这些子系统相互作用和反馈的方式。为了在理解整个系统方面取得进展，必须采用复杂性科学的方法。复杂性科学是一门新兴学科，它试图对英国卫生和社会保健系统所展示的那种规模和连通性相结合的系统进行建模、理解和管理。它在生物、环境和物理系统中有着非常广泛的应用，但在这里，我们感兴趣的是将其应用于社会科学领域，这带来了独特的挑战。在这项研究计划中，我们将汇集来自社会科学和复杂性科学的研究人员团队，以便并肩工作，开发英国卫生保健和社会保健系统中涉及的社会经济过程和组织的模型。本研究解决了开发有效的新型建模工具和技术的关键挑战，并鼓励采用更复杂的方法将这一科学向前推进，为这一重要现实问题的政策提供信息。总的来说，这项研究提供的复杂性科学的回报部分来自于在构建、分析和理解所提出的模型的过程中产生的新工具和方法的进步，而社会科学的回报部分来自于这些模型产生的对健康和社会保健的新理解。但是，在建模者和政策制定者之间的界面上，这两个领域的发现也将带来巨大的回报。特别是，这是一个真正的机会，可以在复杂性科学家如何指导、呈现和描述他们的工作以达到最大效果方面取得进展，这是该领域一直无法做到的。我们雄心勃勃的工作计划旨在应对上述研究挑战，在现代复杂性科学和社会科学长期记录的单一框架下，整合严格的实证研究、复杂的建模以及与相关政策制定者和规划者的反思参与。我们将通过模型、论文、数据集、理论、公众参与和知识交流、博士和博士后培训、会议和研讨会等形式，逐步提高我们对卫生保健周期的理解为政策变化提供信息的程度。同时，我们将在开发复杂性科学的基本工具、概念和方法方面取得进展，特别是在现实世界多尺度社会系统的政策制定背景下。

The UK's population is ageing, and this presents a major problem for government since older people are the major users of health and social care services. As well as increasing the demand for care, population ageing is affecting the supply of care professionals, as the health workforce itself ages. However, ageing is only one factor in a complex set of issues influencing both the supply of and demand for health and social care. These include changes in the profile of disability and disease, the development of new technologies, and changes in levels of income and wealth. The workforce is influenced by many demographic, political and economic factors. The challenges in forecasting the future health workforce have been frequently highlighted, but no research to date has dealt comprehensively with both the demand and supply side of health and social care. To achieve this will require more than simply adding together models of the different sub-systems - what is important is the way that these sub-systems interact and feedback on each other. In order to make progress on understanding the whole system, a complexity science approach must be taken. Complexity science is an emerging discipline that attempts to model, understand and manage systems that combine scale and connectivity of the kind exhibited by the UK's health and social care systems. It has very broad application to biological, environmental, and physical systems, but here we are interested in applying it within a social science domain that poses unique challenges.In this research programme, we shall bring together teams of researchers from both social science and complexity science in order to work side by side to develop models of the socio-economic processes and organisations implicated in the UK's health care and social care systems. This research addresses the key challenges of developing effective novel modelling tools and techniques, and encouraging more sophisticated ways of carrying this science forward to inform policy on this vital real-world problem. In general then, the pay-off for complexity science offered by this research is to be found partly in the new tools and methodological advances that will be generated in the course of building, analysing and understanding the proposed models, and the pay-off for social science is to be found partly in the new understanding of health and social care that the models generate. But there will also be significant pay-off for both fields in the discoveries made at the interface between modellers and policy makers. In particular, there is a real opportunity to make progress on how complexity scientists can direct, present, and describe their work to maximum effect, something that the field has not always been able to do.Our ambitious programme of work aims to meet the research challenges described above, integrating rigorous empirical studies, sophisticated modelling and reflective engagement with relevant policy makers and planners, under a single framework informed both by modern complexity science and a long-standing track record in the social sciences. We will deliver a step change in the degree to which our understanding of the health care cycle can inform policy change in the form of models, papers, datasets, theory, public engagement and knowledge exchange, PhD and post-doctoral training, conferences and workshops. Simultaneously, we will make progress in developing the fundamental tools, concepts and methodologies of complexity science, particularly in the context of policy making for real-world multi-scale social systems.