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10.1002/hpm.3187

http://scihub22266oqcxt.onion/10.1002/hpm.3187
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33934402!8239712!33934402
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suck abstract from ncbi


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pmid33934402      Int+J+Health+Plann+Manage 2021 ; 36 (5): 1476-1485
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  • Healthcare systems and Covid19: Lessons to be learnt from efficient countries #MMPMID33934402
  • Ordu M; Kirli Akin H; Demir E
  • Int J Health Plann Manage 2021[Sep]; 36 (5): 1476-1485 PMID33934402show ga
  • 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.
  • |*COVID-19[MESH]
  • |*Delivery of Health Care[MESH]
  • |Europe[MESH]
  • |Humans[MESH]
  • |Pandemics[MESH]


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