Inequity in out-of-pocket payments for hospitalisation in India: Evidence from the National Sample Surveys, 1995-2014.

OBJECTIVE: We report inequity in out-of-pocket payments (OOPP) for hospitalisation in India between 1995 and 2014 contrasting older population (60 years or more) with a population under 60 years (younger population).

METHODS: We used data from nationwide healthcare surveys conducted in India by the National Sample Survey Organisation in 1995-96, 2004 and 2014 with the sample sizes ranging from 333,104 to 629,888. We used generalised linear and fractional response models to study the determinants of OOPP and their burden (share of OOPP in household consumption expenditure) at a constant price. The relationship between predicted OOPP and its burden with monthly per capita consumption expenditure (MPCE) quintiles and selected socioeconomic characteristics were used to examine vertical and horizontal inequities in OOPP.

RESULTS: The older population had higher OOPP for hospitalisation at all time points (range: 1.15-1.48 times) and a greater increase between 1995-96 and 2014 than the younger population (2.43 vs 1.88 times). Between 1995-96 and 2014, the increase in predicted mean OOPP for hospitalisation was higher for the poorest than the richest (3.38 vs 1.85 times) older population. The increase in predicted mean OOPP was higher for the poorest (2.32 vs 1.46 times) and poor (2.87 vs 1.05 times) older population between 1995-96 and 2004 than in the latter decade. In 2014, across all MPCE quintiles, the burden of OOPP was higher for the less developed states, females, private hospitals, and non-communicable disease and injuries, more so for the older than the younger population. In 2014, the predicted absolute OOPP for hospitalisation was positively associated with MPCE quintiles; however, the burden of OOPP was negatively associated with MPCE quintiles indicating a regressive system of healthcare financing.

CONCLUSION: High OOPP for hospitalisation and greater inequity among older population calls for better risk pooling and prepayment mechanisms in India.