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A framework for predicting gross institutional long-term care cost arising from known commitments at local authority level

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  • C Pelletier

    (University of Westminster)

  • T J Chaussalet

    (University of Westminster)

  • H Xie

    (University of Westminster)

Abstract

As the UK population ages, it is forecasted that there will be an unsustainable increase in the need for, and therefore in the costs of long-term care. Although several studies have been performed to estimate these costs, they do not take into account the impact of survival patterns on costs. Focussing only on residents already in care (known commitments), we have developed, in association with an English local authority, a framework for estimating the future gross cost incurred by this group, built around a survival model. We apply this framework to forecast the cost over a given period of time, of maintaining a group of individuals in residential and nursing care, funded by the local authority. One of the novelties in the model is that it translates survival inputs and unit fees for care into cost in a manner, which was useful and meaningful to decision makers.

Suggested Citation

  • C Pelletier & T J Chaussalet & H Xie, 2005. "A framework for predicting gross institutional long-term care cost arising from known commitments at local authority level," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(2), pages 144-152, February.
    • Handle: RePEc:pal:jorsoc:v:56:y:2005:i:2:d:10.1057_palgrave.jors.2601892
    DOI: 10.1057/palgrave.jors.2601892
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    References listed on IDEAS

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    1. Czado, Claudia & Rudolph, Florian, 2002. "Application of survival analysis methods to long-term care insurance," Insurance: Mathematics and Economics, Elsevier, vol. 31(3), pages 395-413, December.
    2. McNamee, Paul & Gregson, Barbara A. & Buck, Debbie & Bamford, Claire H. & Bond, John & Wright, Ken, 1999. "Costs of formal care for frail older people in England:: the resource implications study of the MRC cognitive function and ageing study (RIS MRC CFAS)," Social Science & Medicine, Elsevier, vol. 48(3), pages 331-341, February.
    3. 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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    Cited by:

    1. H Xie & T J Chaussalet & W A Thompson & P H Millard, 2007. "A simple graphical decision aid for the placement of elderly people in long-term care," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(4), pages 446-453, April.
    2. S McClean & P Millard, 2007. "Where to treat the older patient? Can Markov models help us better understand the relationship between hospital and community care?," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(2), pages 255-261, February.

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