What determines healthcare utilization and related out-of-pocket expenditures in Tajikistan? Lessons from a national survey

Int J Public Health. 2009;54(4):260-6. doi: 10.1007/s00038-009-8044-2.

Abstract

Objectives: The government of Tajikistan is currently exploring the ways to test the possible introduction of a Basic Benefit Package which is to provide healthcare for the most vulnerable groups within the population. In this context, the objective of this study is to analyze individual, household, geographical and systemic factors which explain healthcare utilization and out-of-pocket expenditures in Tajikistan.

Methods: Using a nationally-representative survey, the author examines the determinants of healthcare utilization and its related out-of-pocket expenditures. Two empirical multivariate models are employed: binomial logit regression to estimate the determinants of healthcare utilization and Tobit regression to estimate the determinants of out-of-pocket expenditures.

Results: An increase in the ability to pay is associated with a higher propensity to utilize healthcare. Likewise, being a woman, being elderly, having higher educational attainment and having chronic illness also increase the propensity to utilize healthcare. Conversely, needing to travel a long distance to health post reduces the likelihood of utilization. An increase in ability to pay, being female and using specialized healthcare facilities increases the amount of out-of-pocket expenditures. In contrast, using ancillary healthcare personnel and outpatient facilities reduced the amount of out-of-pocket expenditures.

Conclusions: Linking receipt of the package with targeted social assistance and development of Community Based social insurance scheme can improve accessibility and affordability of healthcare.

MeSH terms

  • Age Factors
  • Chronic Disease
  • Cross-Sectional Studies
  • Female
  • Health Care Reform
  • Health Care Surveys
  • Health Expenditures / trends*
  • Health Services / economics
  • Health Services / statistics & numerical data*
  • Health Services Accessibility*
  • Humans
  • Male
  • Multivariate Analysis
  • Public Assistance / trends*
  • Sex Factors
  • Socioeconomic Factors
  • Tajikistan
  • Time Factors
  • Travel
  • Vulnerable Populations