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Healthcare systems and Covid19: Lessons to be learnt from efficient countries

Author

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  • Muhammed Ordu
  • Hediye Kirli Akin
  • Eren Demir

Abstract

Background The novel coronavirus is rapidly spreading over the world and puts the health systems of countries under intense pressure. High hospitalization levels due to the pandemic outbreak have caused the intensive care units to work above capacity. Purpose A data envelopment analysis (DEA) based modelling approach was developed to evaluate the effectiveness of regions (i.e. city, country or clinical commissioning groups) against the pandemic outbreak. The objective is to enable related authorities better manage the struggle against the outbreak and put in place the emergency action plans immediately. Methodology/Approach DEA method was used to measure the efficiency scores of countries. Super efficiency DEA method was also applied to countries based on the level of efficiencies they have achieved. Sixteen countries were selected that have been facing with Covid19 pandemic outbreak for at least 5 consecutive weeks after their 100th confirmed case. Results A total of 80 DEA models were developed, that is, 16 DEA models for each week. The percentage of efficient countries decreased dramatically over time, from 43.75% in the first week to 25% in the fifth week. Unlike most European countries, China and South Korea increased their effectiveness after first week of implementing all the necessary measures. Conclusion This study sheds light into better understanding the effectiveness of policies adopted by countries and their management strategy in dealing with Covid19 pandemic. Our model will enable political leaders to identify inadequate policies as quickly as possible and learn from their peers for more effective decisions.

Suggested Citation

  • Muhammed Ordu & Hediye Kirli Akin & Eren Demir, 2021. "Healthcare systems and Covid19: Lessons to be learnt from efficient countries," International Journal of Health Planning and Management, Wiley Blackwell, vol. 36(5), pages 1476-1485, September.
    • Handle: RePEc:bla:ijhplm:v:36:y:2021:i:5:p:1476-1485
    DOI: 10.1002/hpm.3187
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    References listed on IDEAS

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    1. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    2. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    3. A. Charnes & W. W. Cooper & E. Rhodes, 1981. "Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through," Management Science, INFORMS, vol. 27(6), pages 668-697, June.
    4. 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.
    5. Khushalani, Jaya & Ozcan, Yasar A., 2017. "Are hospitals producing quality care efficiently? An analysis using Dynamic Network Data Envelopment Analysis (DEA)," Socio-Economic Planning Sciences, Elsevier, vol. 60(C), pages 15-23.
    6. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, January.
    7. Kao, Ling-Jing & Lu, Chi-Jie & Chiu, Chih-Chou, 2011. "Efficiency measurement using independent component analysis and data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 210(2), pages 310-317, April.
    8. Po, Rung-Wei & Guh, Yuh-Yuan & Yang, Miin-Shen, 2009. "A new clustering approach using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 199(1), pages 276-284, November.
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    1. Giménez, Víctor & Prior, Diego & Thieme, Claudio & Tortosa-Ausina, Emili, 2024. "International comparisons of COVID-19 pandemic management: What can be learned from activity analysis techniques?," Omega, Elsevier, vol. 122(C).
    2. Raluca-Elena Caunic & Anca-Laura Asandului, 2023. "Considerations Of Efficiency Of The Romanian Public Hospitals During The Covid-19 Pandemic," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 31, pages 145-153, June.
    3. Claudio Thieme & Víctor Giménez & Diego Prior & Emili Tortosa-Ausina, 2023. "Health vs. Wealth: A Cross-country Analysis of Managerial Effectiveness of the COVID-19," Working Papers 2023/10, Economics Department, Universitat Jaume I, Castellón (Spain).
    4. Gökçe Manavgat & Martine Audibert, 2024. "Healthcare system efficiency and drivers: Re-evaluation of OECD countries for COVID-19," Post-Print hal-04350906, HAL.

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