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

Area of Science:

• Public Health
• Health Systems Management
• Epidemiology

Background:

• The COVID-19 pandemic placed immense pressure on global health systems, overwhelming intensive care units.
• High hospitalization rates necessitated urgent evaluation of regional pandemic management strategies.

Purpose of the Study:

• To develop a Data Envelopment Analysis (DEA) model for assessing regional (city, country, clinical commissioning groups) effectiveness against the COVID-19 pandemic.
• To provide data-driven insights for authorities to enhance pandemic management and implement emergency action plans.

Main Methods:

• Employed Data Envelopment Analysis (DEA) to calculate efficiency scores for sixteen selected countries.
• Utilized a super-efficiency DEA method to further differentiate country performance based on efficiency levels.
• Analyzed countries that had experienced the COVID-19 outbreak for at least five weeks post-100 confirmed cases.

Main Results:

• Developed 80 DEA models (16 per week) to track efficiency changes over five weeks.
• Observed a dramatic decrease in the percentage of efficient countries, from 43.75% in week one to 25% by week five.
• Noted that China and South Korea enhanced their effectiveness post-intervention, contrasting with most European nations.

Conclusions:

• The study provides a framework for understanding the efficacy of national policies and management strategies during the COVID-19 pandemic.
• The DEA model aids policymakers in rapidly identifying ineffective strategies and adopting successful approaches from peer nations for improved decision-making.