Statistical characterization of managerial risk factors: a case of state-run hospitals in India

Public healthcare institutions are the crucial component in the social and economic development of a nation, particularly India. However, public hospitals in India confront multiple operational risk factors that compromise patient satisfaction. Although all the risk factors are essentially critical, the impact potential of any risk factor is ultimately determined by its ability to induce other risk factors. The current research derives motivation from these scenarios and investigates the characteristics of crucial operational risk factors experienced in the public healthcare sector in a South Indian state. Extensive questionnaire-based surveys were conducted among civilians and healthcare professionals in two phases, i.e., prior to the COVID-19 crisis and during the COVID-19 crisis, for identifying significant risk factors. The collected data is analysed using statistical techniques like exploratory factor analysis (EFA) and partial least squares based structural equation modelling (PLS-SEM) to characterise the inter-relationships between risk factors. The research discloses the translational effect of administrative/infrastructure constraints in public hospitals in compromising the operational performance indirectly through human-related issues rather than having a direct influence. More precisely, the presented model indicates that risk factors like the physical infrastructure limitations and shortage of staff will overburden the existing employees, resulting in human-related issues, including attitudinal issues of employees and community mistrusts and misbelieves. The results reveal seemingly resolvable budget allocation issues, but at the same time alarms the authorities to execute immediate countermeasures. Ultimately, this research seeks to empower public hospital administrators with interesting insights and managerial implications drawn from the statistical models.