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Estimating Lifetime Costs of Social Care: A Bayesian Approach Using Linked Administrative Datasets from Three Geographical Areas

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  • Adam Steventon
  • Adam Roberts

Abstract

We estimated lifetime costs of publicly funded social care, covering services such as residential and nursing care homes, domiciliary care and meals. Like previous studies, we constructed microsimulation models. However, our transition probabilities were estimated from longitudinal, linked administrative health and social care datasets, rather than from survey data. Administrative data were obtained from three geographical areas of England, and we estimated transition probabilities in each of these sites flexibly using Bayesian methods. This allowed us to quantify regional variation as well as the impact of structural and parameter uncertainty regarding the transition probabilities. Expected lifetime costs at age 65 were £20,200–27,000 for men and £38,700–49,000 for women, depending on which of the three areas was used to calibrate the model. Thus, patterns of social care spending differed markedly between areas, with mean costs varying by almost £10,000 (25%) across the lifetime for people of the same age and gender. Allowing for structural and parameter uncertainty had little impact on expected lifetime costs, but slightly increased the risk of very high costs, which will have implications for insurance products for social care through increasing requirements for capital reserves. Copyright © 2014 John Wiley & Sons, Ltd.

Suggested Citation

  • Adam Steventon & Adam Roberts, 2015. "Estimating Lifetime Costs of Social Care: A Bayesian Approach Using Linked Administrative Datasets from Three Geographical Areas," Health Economics, John Wiley & Sons, Ltd., vol. 24(12), pages 1573-1587, December.
  • Handle: RePEc:wly:hlthec:v:24:y:2015:i:12:p:1573-1587
    DOI: 10.1002/hec.3110
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    1. Adelina Comas-Herrera & Rebecca Butterfield & José-Luis Fernández & Joshua M. Wiener, 2012. "Barriers to Opportunities for Private Long-term Care Insurance in England: What Can We Learn from Other Countries?," Chapters, in: Alistair McGuire & Joan Costa-Font (ed.), The LSE Companion to Health Policy, chapter 15, Edward Elgar Publishing.
    2. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    3. Eugenio Zucchelli & Andrew M Jones & Nigel Rice, 2012. "The evaluation of health policies through dynamic microsimulation methods," International Journal of Microsimulation, International Microsimulation Association, vol. 5(1), pages 2-20.
    4. H. Xie & T. J. Chaussalet & P. H. Millard, 2005. "A continuous time Markov model for the length of stay of elderly people in institutional long‐term care," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(1), pages 51-61, January.
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    1. Hu, Bo & Cartagena-Farias, Javiera & Brimblecombe, Nicola & Jadoolal, Shari & Wittenberg, Raphael, 2023. "Projected costs of informal care for older people in England," LSE Research Online Documents on Economics 121157, London School of Economics and Political Science, LSE Library.

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