Inequity & burden of out-of-pocket health spending: District level evidences from India

ABSTRACT

Background & objectives: Numerous studies have highlighted the regressive and immiserating impact of out-of-pocket (OOP) health spending in India. However, most of these studies have explored this issue at the national or up to the State level, with an associated risk of overlooking intra-State diversities in the health system and health-seeking behaviour and their implication on the financial burden of healthcare. This study was aimed to address this issue by analyzing district level diversities in inequity, financial burden and impoverishing impact of OOP health spending. Methods: A household survey of 62,335 individuals from 12,134 households, covering eight districts across three States, namely Gujarat, Haryana and Rajasthan was conducted during 2014-2015. Other than general household characteristics, the survey collected information on household OOP [sum total of expenditure on doctor consultation, drugs, diagnostic tests etc. on inpatient depatment (IPD), outpatient depatment (OPD) or chronic ailments] and household monthly consumption expenditure [sum total of monthly expenditure on food, clothing, education, healthcare (OOP) and others]. Gini index of consumption expenditure, concentration index and Kakwani index (KI) of progressivity of OOP, catastrophic burden (at 20% threshold) and poverty impact (using district-level poverty thresholds) were computed, for these eight districts using the survey data. The concentration curve (of OOP expenditure) and Lorenz curve (of consumption expenditure) for the eight districts were also drawn. Results: The distribution of OOP was found to be regressive in all the districts, with significant inter-district variations in equity parameters within a State (KI ranges from ?0.062 to ?0.353). Chhota Udepur, the only tribal district within the sample was found to have the most regressive distribution (KI of ?0.353) of OOP. Furthermore, the economic burden of OOP was more pronounced among the rural sample (CB of 19.2% and IM of 8.9%) compared to the urban sample (CB of 9.4% and IM of 3.7%). Interpretation & conclusions: The results indicate that greater decentralized planning taking into account district-level health financing patterns could be an effective way to tackle inequity and financial vulnerability emerging out of OOP expenses on healthcare.