long-term care use and supply in europe: projections for germany ...

LONG-TERM CARE USE AND SUPPLY IN EUROPE | 31
applies estimated probabilities of the variable of interest (e.g. type of care) to the cell numbers, which
are changing over time. The present model is static, in that it uses prevalence rates of LTC use (rates that
indicate the probability to use a particular type of care at a given moment in time) rather than incidence
rates (rates that indicate the transition probability between types of care). The model takes account of
variables that have been identified in Chapters 2 and 3 as the main drivers of LTC utilisation: age and
gender, the level of disability (number of limitations in activities of daily living), household composition
and a limited number of other relevant characteristics.
The projection model broadly consists of two parts: 1) the distribution of the future numbers of older
persons by age, gender, disability and other relevant characteristics (see section 4.1.1); 2) the application
of estimated probabilities of using different types of LTC care to the projected population numbers in
each group, to produce projected numbers of care users (see section 4.1.2). The projections are made for
the 2010-2060 period at 5-year intervals. Figure 4.1 provides a schematic overview of the projection
model.
Figure 4.1 Schematic overview of the projection model
Projected numbers of persons 65+
Groups by age (A), gender (G), disability (D), other (O)
Logit model/prevalences residential care use
Numbers of persons residing at home by A, G, D, O
Multinomial model home care use
Numbers of
persons
using no
LTC*
Numbers of
users of formal
care only*
Numbers of users
of informal and
formal care*
Numbers of
users of
informal care
only*
Numbers of
residential
care users*
* By A, G, D, O
The current report is not the first to produce projections of LTC use for different European countries,
using a standardised projection methodology. The 2003 European Study of Long-Term Care
Expenditure, (Comas-Herrera et al., 2003 and 2006) presented projections of future numbers of LTC
clients and future expenditures for Germany, Spain, Italy and the United Kingdom, using cell-based or
macro-simulation models. Based on a similar methodology, the European Commission and the Ageing
Working Group have jointly conducted LTC projection exercises for the EU Member States, reported in
the successive reports on the budgetary impact of population ageing (Economic Policy Committee and
European Commission, 2005, 2006, 2008, 2009). At the time of writing, new projections, using the 2006
projection exercise model, are being prepared, to be presented to the ECOFIN Council in May 2012
(Economic Policy Committee and European Commission, 2011).
The projection methodology proposed in the present study offers some advantages over the methods
applied in the above-mentioned European studies. First, it is based on cross-nationally harmonized
survey data (SHARE), using identical definitions and measurements of the different types of care in all
countries involved. In contrast, the existing projections mostly rely on administrative care utilisation
data. Despite major efforts to improve the comparability of the LTC use data, the applied boundaries of