Reducing out-of-pocket expenditures to reduce poverty: a disaggregated analysis at rural-urban and state level in India

Out-of-pocket (OOP) expenditure on health care has significantimplications for poverty in many developing countries. Thispaper aims to assess the differential impact of OOP expenditureand its components, such as expenditure on inpatient care, outpatientcare and on drugs, across different income quintiles, betweendeveloped and less developed regions in India. It also attemptsto measure poverty at disaggregated rural-urban and state levels. Based on Consumer Expenditure Survey (CES) data from the NationalSample Survey (NSS), conducted in 1999–2000, the shareof households’ expenditure on health services and drugswas calculated. The number of individuals below the state-specificrural and urban poverty line in 17 major states, with and withoutnetting out OOP expenditure, was determined. This also enabledthe calculation of the poverty gap or poverty deepening in eachregion. Estimates show that OOP expenditure is about 5% of total householdexpenditure (ranging from about 2% in Assam to almost 7% inKerala) with a higher proportion being recorded in rural areasand affluent states. Purchase of drugs constitutes 70% of thetotal OOP expenditure. Approximately 32.5 million persons fellbelow the poverty line in 1999–2000 through OOP payments,implying that the overall poverty increase after accountingfor OOP expenditure is 3.2% (as against a rise of 2.2% shownin earlier literature). Also, the poverty headcount increaseand poverty deepening is much higher in poorer states and ruralareas compared with affluent states and urban areas, exceptin the case of Maharashtra. High OOP payment share in totalhealth expenditures did not always imply a high poverty headcount;state-specific economic and social factors played a role. The paper argues for better methods of capturing drugs expenditurein household surveys and recommends that special attention bepaid to expenditures on drugs, in particular for the poor. Targetedpolicies in just five poor states to reduce OOP expenditurecould help to prevent almost 60% of the poverty headcount increasethrough OOP payments.