ANCIEN Overview of ANCIEN and classification of long-term care systems Esther Mot (Netherlands Bureau for Economic Policy Analysis, CPB), Peter Willemé (Federal Planning Bureau) iHEA, 8th World Congress on Health Economics, Toronto, July

Long-term care for the elderly

ANCIEN, general information  Assessing Needs of Care in European Nations  research for EC in 7th Framework Programme  January 2009 – August 2012  21 EU-countries included

Typologies of LTC systems Results of Work package 1  managed by Institute for Advanced Studies, Vienna  typology report: Kraus, M., M. Riedel, E. Mot, P. Willemé, G. Röhrling, T. Czypionka (2010), A typology of systems of Long-Term Care in Europe

ANCIEN, objectives  describe and characterise systems of LTC in Europe  analyse the need for care (in relation to demography and lifestyle)  analyse developments in the supply and demand for formal and informal care  analyse the potential role of technology in solving LTC problems

ANCIEN, objectives continued  analyse efforts to improve the quality of LTC  project the use of LTC on the basis of developments in need and supply  evaluate the performance of different types of LTC systems

Aims of Work Package 1  description of LTC-systems in Europe  development of typologies  designed for analysis of LTC systems (as opposed to more general welfare state typologies)  selection of countries to model needs (demography, lifestyle) supply (formal and informal) use of care

WP1, steps  data on LTC collected by national experts standardised format problems with data collection  country reports  typologies

Characteristics for typology Who carries the most responsibility for LTC: formal system or family/person?:  public spending on LTC  private spending on LTC  role of formal versus informal care  support for informal care givers  is there an entitlement?  how strict are eligibility criteria?

Characteristics for typology, 2  How is formal system organised: quality assurance type of providers centralised or not? coordination and integration of care  What about freedom of choice? role of cash benefits? free choice of providers?

WP1, two methods of clustering  mostly organisational, 21 countries for example choice of provider, quality assurance  use and financing of care, 14 countries

Use and financing typology  selection of 8 metric variables for 14 countries  factor analysis on 8 variables, 4 variables used  cluster-analysis

Variables  public spending* (related to GDP and needs)  share of private expenditures*  informal care use*  IC support*  formal care use  role of cash benefits  accessibility  targeting

Result

Result, by cluster informal care oriented, low private financing Belgium*, Czech Republic, Germany, Slovakia * medium spender low spending, low private, high IC use, high IC support, cash benefits modest generous, accessible and formalized Denmark, the Netherlands, Sweden high spending, low private, low IC use, high IC support, cash benefits modest informal care oriented, high private financing Austria, England, Finland, France, Spain medium spending, high private, high IC use, high IC support, cash benefits high high private financing, informal care seems necessity Hungary, Italy low spending, high private, high IC use, low IC support, cash benefits medium

Star plot of LTC systems

Countries to be modelled (considering data availability)  Germany  the Netherlands  Spain  Poland (simplified models)

Conclusion  most new member states only to be analysed with organisational approach, but NMS not in 1 cluster (in both typologies)  3 variables crucial for countries with better data: needs-corrected public spending, private funding, informal care support

Conclusion 2  stable clustering of Nordic countries with generous systems with large role for formal care (under different approaches): Sweden, Denmark, Netherlands  important role for informal care in all other clusters distinction by private financing, IC support, use of formal care, role of cash benefits

Conclusion 3  large impact of available information  different clustering with richer dataset  clustering especially for LTC is different

More information:  general information country reports on LTC systems typology report  (Institute for Advanced Studies)  (CPB)  (FPB)