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

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 su...

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Veröffentlicht in:The European Journal of Health Economics. - Springer Science + Business Media. - 17(2016), 6, Seite 681-691
1. Verfasser: Eggink, Evelien (VerfasserIn)
Weitere Verfasser: Woittiez, Isolde, Ras, Michiel
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2016
Zugriff auf das übergeordnete Werk:The European Journal of Health Economics
Schlagworte:Mathematics Health sciences Social sciences Behavioral sciences
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520 |a 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 %). 
540 |a © Springer-Verlag Berlin Heidelberg 2016 
650 4 |a Mathematics  |x Applied mathematics  |x Analytics  |x Predictive analytics  |x Analytical forecasting  |x Forecasting models 
650 4 |a Health sciences  |x Medical treatment  |x Inpatient treatment 
650 4 |a Health sciences  |x Health care industry  |x Health care services  |x Home care services 
650 4 |a Social sciences  |x Population studies  |x Human populations  |x Persons  |x Adults  |x Older adults 
650 4 |a Health sciences  |x Medical conditions  |x Disorders  |x Physical disorders  |x Musculoskeletal disorders  |x Muscular disorders 
650 4 |a Health sciences  |x Medical specialties  |x Geriatrics  |x Eldercare 
650 4 |a Behavioral sciences  |x Psychology  |x Clinical psychology  |x Mental illness 
650 4 |a Behavioral sciences  |x Sociology  |x Human societies  |x Social structures  |x Social stratification  |x Social classes 
650 4 |a Social sciences  |x Population studies  |x Population characteristics 
650 4 |a Mathematics  |x Pure mathematics  |x Probability theory  |x Probabilities  |x Probability forecasts 
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700 1 |a Woittiez, Isolde  |e verfasserin  |4 aut 
700 1 |a Ras, Michiel  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t The European Journal of Health Economics  |d Springer Science + Business Media  |g 17(2016), 6, Seite 681-691  |w (DE-627)320494462  |w (DE-600)2011428-X  |x 16187601  |7 nnns 
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856 4 0 |u https://www.jstor.org/stable/24774193  |3 Volltext 
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