2013年-CEPS欧洲政策研究中心_Assessing_Needs_of_Care_in_European_Nations_35页_705kb

Summary of ENEPRI Policy Brief No. 14: Assessing Needs of Care in European Nations

Core Content

This ENEPRI Policy Brief summarizes the findings and policy implications of the ANCIEN research project, which examined the future of long-term care (LTC) for the elderly in Europe. The project, funded by the European Commission under the 7th Framework Programme, involved 20 partners from EU member states and was conducted over 44 months. It aimed to understand how LTC needs, demand, supply, and use will evolve and how different LTC systems perform.

Main Questions Addressed

The project focused on two central questions:

1. How will need, demand, supply and use of LTC develop?
2. How do different systems of LTC perform?

These questions were explored through seven work packages, each contributing unique insights into LTC systems, their structure, and future challenges.

Key Findings

1. Typology of LTC Systems

• Approach 1: Based on the organisation and financing of LTC systems, a typology was developed for 21 EU countries.

  • Nordic countries, France, and Germany are characterised by highly developed systems and generous public funding.
  • New EU member states (e.g., Hungary, Poland, Romania) typically have less public funding, but organisational differences are significant.
  • Intermediate systems include countries like Austria, England, Finland, Italy, Latvia, Slovenia, and Spain, which have moderate financial generosity and organisational depth.

• Approach 2: Based on use and financing, a typology was developed for 14 countries.

  • Cluster A: Informal care oriented, low private financing (Belgium, Czech Republic, Germany, Slovakia).
  • Cluster B: Generous, accessible, and formalised (Denmark, Netherlands, Sweden).
  • Cluster C: Informal care oriented, high private financing (Austria, England, Finland, France, Spain).
  • Cluster D: High private financing, informal care seems necessity (Hungary, Italy).

2. Demographic and Epidemiological Projections

• The EUROPOP 2008 mortality forecasts were used to project LTC needs in Germany, Spain, the Netherlands, and Poland.

• Projections considered:

  • Demographic changes (aging population).
  • Life extension (double ageing).
  • Epidemiological changes (impact of smoking and obesity on disability).

• Life expectancy at age 65:

  • Germany: 20.1 years for women, 16.8 years for men in 2008.
  • Spain: 20.96 years for women, 17.14 years for men in 2008.
  • The Netherlands: 19.94 years for women, 16.59 years for men in 2008.
  • Poland: 18.56 years for women, 14.50 years for men in 2008.

• Disability prevalence:

  • In the Delay scenario (2040), the number of disabled elderly in Germany, Spain, and the Netherlands increases by 7–11%, while in Poland, it increases by 22% due to higher prevalence of disability and faster life expectancy growth.
  • Convergence scenario (Poland with Germany) reduces the impact of life extension on disability prevalence by 5 percentage points, but disability remains high due to historical prevalence.

3. Risk Factors and Disability

• Smoking significantly reduces life expectancy and disability duration, particularly for men.
• Obesity increases the risk of disability, especially for women.
• The EUROPOP methodology assumes that mortality and incidence changes are risk factor-dependent, but not risk factor-independent.

Policy Implications and Recommendations

• Data Collection and Standardisation:

  • An international database on LTC provision and use is recommended to improve research comparability.
  • Existing databases like OECD Health Data and WHO Health For All should be expanded to include LTC data.

• System Typology:

  • The typology helps to better understand the complexity of LTC systems and their performance.
  • It is important to consider both organisational depth and financial generosity when assessing LTC systems.

• Outcome Orientation:

  • Research should focus on the outcomes of LTC systems rather than just their structure.
  • There is no general proxy for LTC outcomes like life expectancy, so outcome-based analysis is essential for policy development.

• Policy Learning Across Countries:

  • While it is unrealistic to expect countries to copy each other’s LTC systems, they can still learn from one another.
  • Cluster analysis shows that LTC systems vary significantly due to historical, cultural, and economic factors.

• Scenario Analysis:

  • The biological scenario is a more realistic basis for projections, as it accounts for the timing of disability relative to death.
  • The Delay scenario offers a more conservative estimate and is recommended for policy planning due to its stability.

Conclusion

The ANCIEN project provides a comprehensive framework for understanding the future of LTC in Europe, highlighting the need for data standardisation, outcome-based research, and cross-country learning. It also underscores the significant impact of demographic and epidemiological changes on LTC needs, and the importance of considering risk factors like smoking and obesity in projections. The typology of LTC systems serves as a useful tool for policy-makers to assess and improve LTC provision in the context of an aging population.