What predicts the technical efficiency in healthcare systems of OECD countries? A two-stage DEA approach

Konca M., Top M.

International Journal of Healthcare Management, vol.16, no.1, pp.104-119, 2023 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 16 Issue: 1
  • Publication Date: 2023
  • Doi Number: 10.1080/20479700.2022.2077510
  • Journal Name: International Journal of Healthcare Management
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, Business Source Elite, Business Source Premier
  • Page Numbers: pp.104-119
  • Keywords: Healthcare systems, technical efficiency, data envelopment analysis, panel tobit, Simar and Wilson (2007) regression, DATA ENVELOPMENT ANALYSIS, ECONOMIC COOPERATION, DETERMINANTS, INEFFICIENCIES, MODELS, 2-STEP
  • Hacettepe University Affiliated: Yes


Background: Waste in healthcare systems can only be revealed by performance measurements. Aims: This study revealed the technical efficiency of healthcare systems and their determinants in the Organization for Economic Co-operation and Development countries. Methods: We developed a data envelopment analysis (DEA) model and a panel Tobit regression model. Gross domestic product per capita, the economic growth rate, Gini Coefficient, the unemployment rate, 2008 global financial crisis, alcohol consumption, obesity and smoking rates, the ratio of dependent populations, and the ratio of university graduates were regressors in the panel Tobit. We employed a Simar and Wilson (2007) regression to check the robustness of Tobit results. Results: Gross domestic product per capita and the ratio of university graduates significantly and negatively affected inefficiency scores (p < 0.05). The unemployment rate, Gini Coefficient, 2008 global financial crisis, alcohol consumption, obesity and smoking rates, and the ratio of dependent populations significantly and positively affected inefficiency scores (p < 0.05). The economic growth rate also positively affected inefficiency scores but it was not found to be significant (p > 0.05). Simar and Wilson (2007) results were found to be consistent with Tobit results. Conclusions: Decision-makers should try to reveal the factors affecting the performance of healthcare systems.