课题基金 / 基金详情

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

The Care Life Cycle: Responding to the Health and Social Care Needs of an Ageing Society
护理生命周期:应对老龄化社会的健康和社会护理需求
批准号:
EP/H021698/1
负责人:
Jane Falkingham
金额:
$357.83万
依托单位:
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
项目状态:
已结题
起止时间:
2010 至 --

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中文摘要
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英文摘要
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.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
A note on the use of Bayesian methods in official statistics
关于官方统计中使用贝叶斯方法的说明
DOI: --
发表时间: 2017
期刊:
影响因子: --
作者: [[]]
通讯作者: []
Embracing Uncertainty in Complex Models of Social Care
拥抱复杂社会关怀模式中的不确定性
DOI: --
发表时间: 2014
期刊:
影响因子: --
作者: [Bijak J]
通讯作者: Bijak J
Dealing with uncertainty in migration research
应对移民研究中的不确定性
DOI: --
发表时间: 2014
期刊:
影响因子: --
作者: [Bijak J]
通讯作者: Bijak J
Methods for Forecasting Migration: Evaluation and Policy Implications
预测移民的方法:评估和政策影响
DOI: --
发表时间: 2015
期刊:
影响因子: --
作者: [Bijak J]
通讯作者: Bijak J
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