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Efficiency Evaluation of the Healthcare System in Albania

Author

Listed:
  • Silvana Mustafaj
  • Amalia Tola
  • Elfrida Dishmema
  • Etleva Muca

Abstract

The effectiveness of a country’s healthcare system serves as a key metric to assess its economic development, as it directly influences the well-being and life expectancy of its population. The healthcare system is an important sector of great public interest, and as such it is expected to operate efficiently, addressing well and in time people’s needs. The paper reveals the findings from the efficiency analysis of the healthcare system in Albania, in terms of public expenditure in healthcare, from 2007 to 2021. Its purpose is to provide a comprehensive view of the system’s advancement during this timeframe, identifying the years with efficiency and inefficiency. Additionally, the paper suggests potential applications of the model results, to enhance efficiency in future healthcare management. The assessment of healthcare system efficiency in Albania, is based on the analysis of secondary data, using the nonparametric approach, Data Envelopment Analysis. The results of the analysis indicate fluctuating efficiency levels of the healthcare system over the course of those fifteen years. In terms of public spending, the healthcare system in Albania proved to be efficient during the years 2008, 2013, and 2015, while it showed levels of inefficiency during the other years including the Covid-19 pandemic.

Suggested Citation

  • Silvana Mustafaj & Amalia Tola & Elfrida Dishmema & Etleva Muca, 2025. "Efficiency Evaluation of the Healthcare System in Albania," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 3, pages 909-926, September.
    • Handle: RePEc:nwe:eajour:y:2025:i:3:p:909-926
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    References listed on IDEAS

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    1. Panos Kanavos & Olivier Wouters & Jonathan Cylus & Irene Papanicolas & Peter C. Smith, 2017. "Using Data Envelopment Analysis to Address the Challenges of Comparing Health System Efficiency," Global Policy, London School of Economics and Political Science, vol. 8, pages 60-68, March.
    2. Deepak Kumar Behera & Umakant Dash, 2020. "Is health expenditure effective for achieving healthcare goals? Empirical evidence from South-East Asia Region," Asia-Pacific Journal of Regional Science, Springer, vol. 4(2), pages 593-618, June.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    4. repec:bla:glopol:v:8:y:2017:i:s2:p:60-68 is not listed on IDEAS
    5. Angel Higuerey & Christian Viñan-Merecí & Zulema Malo-Montoya & Valentín-Alejandro Martínez-Fernández, 2020. "Data Envelopment Analysis (DEA) for Measuring the Efficiency of the Hotel Industry in Ecuador," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
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