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Forecasting the use of elderly care: a static micro-simulation model

Author

Listed:
  • Evelien Eggink

    (The Netherlands Institute for Social Research/SCP)

  • Isolde Woittiez

    (The Netherlands Institute for Social Research/SCP)

  • Michiel Ras

    (The Netherlands Institute for Social Research/SCP)

Abstract

This paper describes a model suitable for forecasting the use of publicly funded long-term elderly care, taking into account both ageing and changes in the health status of the population. In addition, the impact of socioeconomic factors on care use is included in the forecasts. The model is also suitable for the simulation of possible implications of some specific policy measures. The model is a static micro-simulation model, consisting of an explanatory model and a population model. The explanatory model statistically relates care use to individual characteristics. The population model mimics the composition of the population at future points in time. The forecasts of care use are driven by changes in the composition of the population in terms of relevant characteristics instead of dynamics at the individual level. The results show that a further 37 % increase in the use of elderly care (from 7 to 9 % of the Dutch 30-plus population) between 2008 and 2030 can be expected due to a further ageing of the population. However, the use of care is expected to increase less than if it were based on the increasing number of elderly only (+70 %), due to decreasing disability levels and increasing levels of education. As an application of the model, we simulated the effects of restricting access to residential care to elderly people with severe physical disabilities. The result was a lower growth of residential care use (32 % instead of 57 %), but a somewhat faster growth in the use of home care (35 % instead of 32 %).

Suggested Citation

  • Evelien Eggink & Isolde Woittiez & Michiel Ras, 2016. "Forecasting the use of elderly care: a static micro-simulation model," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(6), pages 681-691, July.
    • Handle: RePEc:spr:eujhec:v:17:y:2016:i:6:d:10.1007_s10198-015-0714-9
    DOI: 10.1007/s10198-015-0714-9
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    References listed on IDEAS

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    1. Ruth Hancock & Adelina Comas-Herrera & Raphael Wittenberg & Linda Pickard, 2003. "Who Will Pay for Long-Term Care in the UK? Projections Linking Macro- and Micro-Simulation Models," Fiscal Studies, Institute for Fiscal Studies, vol. 24(4), pages 387-426, December.
    2. Karlsson, Martin & Mayhew, Les & Plumb, Robert & Rickayzen, Ben, 2006. "Future costs for long-term care: Cost projections for long-term care for older people in the United Kingdom," Health Policy, Elsevier, vol. 75(2), pages 187-213, January.
    3. Adelina Comas-Herrera & Alessandra di Maio & Alessandro Pozzi & Concepció Patxot & Cristiano Gori & Heinz Rothgang & Joan Costa i Font & Linda Pickard & Raphael Wittenberg, "undated". "How Does Demography affect Long-Term Care Expenditures Projections?," Studies on the Spanish Economy 231, FEDEA.
    4. M. Duée & C. Rebillard, 2004. "Old age disability in France: a long run projection," Documents de Travail de l'Insee - INSEE Working Papers g2004-02, Institut National de la Statistique et des Etudes Economiques.
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    Cited by:

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    3. Bührer, Christian & Fetzer, Stefan & Hagist, Christian, 2020. "Adverse selection in the German Health Insurance System – the case of civil servants," Health Policy, Elsevier, vol. 124(8), pages 888-894.

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