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Evaluation of the Efficiency of European Health Systems Using Fuzzy Data Envelopment Analysis
Juan Cándido Gómez-Gallego1, María Gómez-Gallego2, Javier Fernando García-García2
1Applied Economics Department, Faculty of Economics, University of Murcia, 30100 Murcia, Spain.
Healthcare (Basel, Switzerland)
|October 23, 2021
Summary
This study reveals that traditional Data Envelopment Analysis (DEA) overestimates health system efficiency. Fuzzy Data Envelopment Analysis (FDEA) and DEA scores correlate positively, but bias is linked to income inequality and economic freedom.
Area of Science:
- Health Economics
- Operations Research
- Econometrics
Background:
- Health system efficiency studies often rely on average output values, potentially misrepresenting true performance.
- Ignoring the representativeness of average statistics can lead to significant estimation problems in efficiency assessments.
Purpose of the Study:
- To evaluate the technical efficiency of European health systems using Data Envelopment Analysis (DEA) and Fuzzy Data Envelopment Analysis (FDEA) models.
- To assess the bias introduced by conventional DEA models in efficiency estimation.
- To examine the relationship between efficiency estimation bias and macroeconomic variables like income inequality and economic freedom.
Main Methods:
- Application of various DEA and FDEA models to assess technical efficiency in European health systems.
- Comparative analysis of efficiency scores derived from traditional DEA and FDEA approaches.
- Statistical evaluation of the correlation between efficiency bias and macroeconomic indicators (income inequality, economic freedom).
Main Results:
- Positive correlations were observed between DEA and FDEA efficiency scores.
- Traditional DEA models were found to overestimate health system efficiency scores.
- The magnitude of the efficiency bias demonstrated a positive association with income inequality and a negative association with economic freedom.
Conclusions:
- FDEA offers a more nuanced approach to health system efficiency compared to traditional DEA.
- Income inequality and economic freedom are significant factors influencing the bias in health system efficiency estimations.
- Policy interventions addressing income inequality and promoting economic freedom may impact the accuracy of health system efficiency assessments.
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