Greener healthcare operations during COVID-19 pandemic: A data envelopment analysis approach

Abstract

This study examines internal greener operations in Indian healthcare during COVID-19 pandemic. Specifically, the research explores the interrelationships among three parallel healthcare lines: general care, emergency care, and biomedical waste (BMW) management to fulfill greener healthcare’s targeted sustainable development goals. We use the three parallel stage data envelopment analysis (DEA) approach model to assess efficiencies of the overall system and the individual parallel stages. We collected panel data for cities in the state of Maharashtra, India during the second wave of pandemic in 2021. We find that the effectiveness of general and emergency medical services depends on the requirements of healthcare resources such as beds and equipment in times of pandemics. By contrast, the capacity of individual BMW treatment processes such as incineration, autoclave, shredder, and deep burial would have a bearing on the efficiency of both BMW management and the total system for greener operations. In the second phase, we evaluated the impact of context-specific exogenous factors using a regression model. We found that literacy level was the most important factor at all three parallel stages separately. Additionally, the total population and number of female vaccinated persons were significant across the system while population density and number of male vaccinated persons were inconsequential factors. Interestingly, the Wilcoxon rank-sum hypothesis test offered no evidence to suggest that performance of general care and BMW management, and emergency care and BMW management were equivalent. Implications of these findings for academic theory, practitioners, and policy makers are offered.