Projecting local care demand from people living with dementia and their carers


The number of older people with dementia, and the cost of caring for them, are expected to rise due to population ageing (reference Wittenberg et al). To plan effectively for their care and support, it is important to understand the level of care required to meet future care needs and associated costs.

Our previous analyses (reference Bhanu et al), using a cell-based projections model and input from a microsimulation model, indicated the number of older people with dementia in England could more than double in the next 25 years. We projected that the total cost of dementia will increase from £23.0 billion in 2015 to £80.1 billion in 2040, and the average cost from £35,100 per person per year in 2015 to £58,900 in 2040.

Our analyses showed that the rise in numbers of older people with dementia and costs of care are likely to vary between different local authorities (reference Wittenberg et al). This is due to local differences in age, gender, education and different supply characteristics which affect local patterns of support.

The proposed research will build on these and our other analyses (reference Fernandez et al) on local needs for care to develop a model that gives NT local authorities projections of the number of older people with dementia receiving unpaid care or using care services and associated costs over the next 25 years.

The research will use:

  • qualitative methods (interviews and workshops with key stakeholders) to understand local factors associated with patterns of need for support with dementia, their geographical concentration across the region, and supply-side constraints likely to affect the type and cost of support for people with dementia and their carers.
  • Audit of local data availability from health and social care administrative records to analyse local patterns of care and support and development of information governance templates that enable sharing and matching of relevant individual-level information.
  • Quantitative modelling of numbers of people living with dementia and patterns and costs of health and social care support services. The analysis will be informed by the findings of the qualitative research, explore a range of macro and micro modelling methods and assess their suitability in light of the data available for local projections modelling and develop local projections models.

The research will address key research needs highlighted during the engagement of ARC-NT with councils, i.e.:

  • Develop a projections tool for local commissioners to plan support services.
  • Train a researcher in the development of projections of demand and expenditure.
  • Develop modelling infrastructure, generalisable to other areas of England, by applying different local evidence to the common modelling structure.
  • Assess local data sources (e.g., administrative records) and develop methods for extracting, matching and analysing such data. Methodological outputs will include a description of the information governance arrangements involved in sharing local administrative data for research. The need for such guidance has been highlighted by NIHR.

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London School of Economics

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