Determining factors of catastrophic health spending in Bogota, Colombia

Int J Health Care Finance Econ. 2011 Jun;11(2):83-100. doi: 10.1007/s10754-011-9089-3. Epub 2011 Feb 27.

Abstract

This study tests whether the low-income population in Bogota not insured under the General Social Security Health System is able to economically handle unexpected health problems or not. It used data from the Health Services Use and Expenditure Study conducted in Colombia in 2001, for which each household recorded its monthly out-of-pocket health expenditure during the year and the household income was measured as the sum of each member's contribution to the household. Payment capacity or available income and catastrophic health spending were based on the latest methodology proposed by the World Health Organization (WHO) in 2005. A probit model was adjusted to determine the factors that significantly influence the likelihood of a household having catastrophic health spending. The percentage of households with catastrophic health spending in Bogota was 4.9%; incidence was higher in low-income households where none of the members were affiliated to social security, where there had been an in-patient event, and where the heads of household were over 60 years of age. There is no statistical evidence for rejecting the hypothesis under study, which states that low-income households that have no health insurance are more likely to have catastrophic health spending than higher-income households with health insurance.

MeSH terms

  • Catastrophic Illness / economics*
  • Catastrophic Illness / epidemiology
  • Colombia / epidemiology
  • Health Care Reform
  • Health Expenditures / statistics & numerical data*
  • Health Services / economics*
  • Health Services / statistics & numerical data
  • Health Surveys
  • Healthcare Disparities / economics*
  • Humans
  • Incidence
  • Insurance Coverage / economics
  • Insurance Coverage / trends
  • Insurance, Health / economics*
  • Insurance, Health / trends
  • Medically Uninsured*
  • Poverty / statistics & numerical data