Accidental Injury is a traumatic event which not only influences physical, psychological, and social wellbeing of the households but also exerts extensive financial burden on them. Despite the devastating economic burden of injuries, in India, there is limited data available on injury epidemiology. This paper aims to, first, examine the socio-economic differentials in Out of Pocket Expenditure (OOPE) on accidental injury; second, to look into the level of Catastrophic Health Expenditure (CHE) at different threshold levels; and last, to explore the adjusted effect of various socio-economic covariates on the level of CHE.
Data was extracted from the key indicators of social consumption in India: Health, National Sample Survey Organisation (NSSO), conducted by the Government of India during January–June-2014. Logistic regression analysis was employed to analyse the various covariates of OOPE and CHE associated to accidental injury.
Binary Logistic analysis has demonstrated a significant association between socioeconomic status of the households and the level of OOPE and CHE on accidental injury care. People who used private health services incurred 16 times higher odds of CHE than those who availed public facilities. The result shows that if the person is covered via any type of insurance, the odd of CHE was lower by about 28% than the uninsured. Longer duration of stay and death due to accidental injury was positively associated with higher level of OOPE. Economic status, nature of healthcare facility availed and regional affiliation significantly influence the level of OOPE and CHE.
Despite numerous efforts by the Central and State governments to reduce the financial burden of healthcare, large number of households are still paying a significant amount from their own pockets. There are huge differentials in cost for the treatment among public and private healthcare providers for accidental injury. It is expected that the findings would provide insights into the prevailing magnitude of accidental injuries in India, the profile of the population affected, and the level of OOPE among households.