How social policies can improve financial accessibility of healthcare: a multi-level analysis of unmet medical need in European countries

Int J Equity Health. 2016 Mar 5;15:41. doi: 10.1186/s12939-016-0335-7.


Background: The article explores in how far financial accessibility of healthcare (FAH) is restricted for low-income groups and identifies social protection policies that can supplement health policies in guaranteeing universal access to healthcare. The article is aimed to advance the literature on comparative European social epidemiology by focussing on income-related barriers of healthcare take-up.

Method: The research is carried out on the basis of multi-level cross-sectional analyses using 2012 EU-SILC data for 30 European countries. The social policy data stems from EU-SILC beneficiary information.

Results: It is argued that unmet medical needs are a reality for many individuals within Europe - not only due to direct user fees but also due to indirect costs such as waiting time, travel costs, time not spent working. Moreover, low FAH affects not only the lowest income quintile but also the lower middle income class. The study observes that social allowance increases the purchasing power of both household types, thereby helping them to overcome financial barriers to healthcare uptake.

Conclusion: Alongside healthcare system reform aimed at improving the pro-poor availability of healthcare facilities and financing, policies directed at improving FAH should aim at providing a minimum income base to the low-income quintile. Moreover, categorical policies should address households exposed to debt which form the key vulnerable group within the low-income classes.

MeSH terms

  • Cross-Sectional Studies
  • Fees and Charges
  • Health Care Costs*
  • Health Care Reform / economics
  • Health Care Reform / statistics & numerical data
  • Health Policy / economics*
  • Health Services Accessibility / economics*
  • Health Services Accessibility / statistics & numerical data
  • Humans
  • Needs Assessment / statistics & numerical data*
  • Poverty
  • Vulnerable Populations / statistics & numerical data