Occupational and geographical differentials in financial protection against healthcare out-of-pocket payments in Nepal: evidence for universal health coverage

Abstract Background . The low-and middle-income countries including Nepal aim to address financial hardship against healthcare out-of-pocket (OOP) payments through risk-pooling arrangements. World Health Organization (WHO) has recommended member states to establish pooling arrangements so that the financial risks owing to health uncertainty can be spread across population. This study aims to analyse the situation of financial protection across occupations and geography using nationally representative annual household survey (AHS) in Nepal. Methods. We measured catastrophic health expenditure (CHE) due to OOP using two approaches: budget share approach at 10% and 25% threshold, and capacity-to-pay approach at 40% threshold. Impoverishment impact due to OOP was measured at absolute and relative poverty lines. These estimates were disaggregated across occupations and geography. The inequality in financial risk protection was measured using concentration index. The analysis was based on the cross-sectional AHS 2014-15, the most recent round that provided information on occupations and consumption. AHS employed standard consumption measurement tool (COICOP). International Standard Classification of Occupations (ISCO) was used to categorize occupations. Results. Among the agricultural workers, we found a CHE of 10.7% at 10% threshold and 5.2% at 40% threshold. Among ‘plant operators and craft workers’, the corresponding figures were 10% and 4.8%. Impoverishment impact was higher in these households at all poverty lines. CHE was higher among unemployed households. A negative concentration index for CHE and impoverishment impact was found for agricultural workers and ‘plant operators and craft workers’. In rural areas, we found a CHE of 11.5% at 40% threshold and a high impoverishment impact. Across province, CHE was 12% in Madhesh and 14.3% in Lumbini at 10% threshold, and impoverishment impact was 1.9% in Madhesh, Karnali and Sudurpachim at US $1.90 a day poverty line. Conclusion. Households belonging to informal occupations such as agricultural workers, plant operators and craft workers, elementary occupations and unemployed were more prone to CHE and impoverishment impact due to healthcare OOP payments. There was wide urban/rural and provincial differential in financial protection status. The results can be useful to policymakers engaged in designing risk-pooling arrangements to make progress towards UHC.