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      Does equity in healthcare spending exist among Indian states? Explaining regional variations from national sample survey data

      research-article
      1 , 2 ,
      International Journal for Equity in Health
      BioMed Central
      Equity, Inequalities, Healthcare utilisation, GLRM, OOPE

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          Abstract

          Background

          Equity and justice in healthcare payment form an integral part of health policy and planning. In the majority of low and middle-income countries (LMICs), healthcare inequalities are further aggravated by Out of Pocket Expenditure (OOPE). This paper examines the pattern of health equity and regional disparities in healthcare spending among Indian states by applying Andersen’s behavioural model of healthcare utilization.

          Methods

          The present study uses data from the 66 th quinquennial round of Consumer Expenditure Survey, of the National Sample Survey Organization (NSSO), conducted in 2009–10 by Ministry of Statistics and Programme Implementation (MoSPI), Government of India (GoI). To measure equity and regional disparities in healthcare expenditure, states have been categorized under three heads on the basis of monthly OOPE i.e., Category A (OOPE > =INR 100); Category B (OOPE between INR 50 to 99) and Category C (OOPE < INR 50). Multiple Generalised Linear Regression Model (GLRM) has been employed to explore the effect of various socio-economic covariates on the level of OOPE.

          Results

          The gap in the ratio of average healthcare spending between the poorest and richest households was maximum in Category A states (richest/poorest = 14.60), followed by Category B (richest/poorest 11.70) and Category C (richest/poorest 11.40). Results also indicate geographical concentration of lower level healthcare spending among Indian states (e.g., Odisha, Chhattisgarh and all the north-eastern states). Results from the multivariate analysis suggest that people residing in urban areas, having higher economic status, belonging to non-Muslim communities, non-Scheduled Tribes (STs), and non-poor households spend more on healthcare than their counterparts.

          Conclusions

          In spite of various efforts by the government to reduce the burden of healthcare spending, widespread inequalities in healthcare expenditure are prevalent. Households with high healthcare needs (SCs/STs, and the poor) are in a more disadvantaged position in terms of spending on health care. It has also been observed that spending on healthcare was comparatively lower among backward or isolated states. No doubt, the overall social security measures should be enhanced, but at the same time, looking at the regional differences, more priority should be assigned to the disadvantaged states to reduce the burden of OOPE. It is proposed that there is need to increase government spending, especially for the disadvantaged states and population, to minimise the burden of OOPE.

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          Most cited references52

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          What are the economic consequences for households of illness and of paying for health care in low- and middle-income country contexts?

          This paper presents the findings of a critical review of studies carried out in low- and middle-income countries (LMICs) focusing on the economic consequences for households of illness and health care use. These include household level impacts of direct costs (medical treatment and related financial costs), indirect costs (productive time losses resulting from illness) and subsequent household responses. It highlights that health care financing strategies that place considerable emphasis on out-of-pocket payments can impoverish households. There is growing evidence of households being pushed into poverty or forced into deeper poverty when faced with substantial medical expenses, particularly when combined with a loss of household income due to ill-health. Health sector reforms in LMICs since the late 1980s have particularly focused on promoting user fees for public sector health services and increasing the role of the private for-profit sector in health care provision. This has increasingly placed the burden of paying for health care on individuals experiencing poor health. This trend seems to continue even though some countries and international organisations are considering a shift away from their previous pro-user fee agenda. Research into alternative health care financing strategies and related mechanisms for coping with the direct and indirect costs of illness is urgently required to inform the development of appropriate social policies to improve access to essential health services and break the vicious cycle between illness and poverty.
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            Reforming the health sector in developing countries: the central role of policy analysis.

            Policy analysis is an established discipline in the industrialized world, yet its application to developing countries has been limited. The health sector in particular appears to have been neglected. This is surprising because there is a well recognized crisis in health systems, and prescriptions abound of what health policy reforms countries should introduce. However, little attention has been paid to how countries should carry out reforms, much less who is likely to favour or resist such policies. This paper argues that much health policy wrongly focuses attention on the content of reform, and neglects the actors involved in policy reform (at the international, national sub-national levels), the processes contingent on developing and implementing change and the context within which policy is developed. Focus on policy content diverts attention from understanding the processes which explain why desired policy outcomes fail to emerge. The paper is organized in 4 sections. The first sets the scene, demonstrating how the shift from consensus to conflict in health policy established the need for a greater emphasis on policy analysis. The second section explores what is meant by policy analysis. The third investigates what other disciplines have written that help to develop a framework of analysis. And the final section suggests how policy analysis can be used not only to analyze the policy process, but also to plan.
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              Coping with out-of-pocket health payments: empirical evidence from 15 African countries

              OBJECTIVE: To explore factors associated with household coping behaviours in the face of health expenditures in 15 African countries and provide evidence for policy-makers in designing financial health protection mechanisms. METHODS: A series of logit regressions were performed to explore factors correlating with a greater likelihood of selling assets, borrowing or both to finance health care. The average partial effects for different levels of spending on inpatient care were derived by computing the partial effects for each observation and taking the average across the sample. Data used in the analysis were from the 2002-2003 World Health Survey, which asked how households had financed out-of-pocket payments over the previous year. Households selling assets or borrowing money were compared to those that financed health care from income or savings. Those that used insurance were excluded. For the analysis, a value of 1 was assigned to selling assets or borrowing money and a value of 0 to other coping mechanisms. FINDINGS: Coping through borrowing and selling assets ranged from 23% of households in Zambia to 68% in Burkina Faso. In general, the highest income groups were less likely to borrow and sell assets, but coping mechanisms did not differ strongly among lower income quintiles. Households with higher inpatient expenses were significantly more likely to borrow and deplete assets compared to those financing outpatient care or routine medical expenses, except in Burkina Faso, Namibia and Swaziland. In eight countries, the coefficient on the highest quintile of inpatient spending had a P-value below 0.01. CONCLUSION: In most African countries, the health financing system is too weak to protect households from health shocks. Borrowing and selling assets to finance health care are common. Formal prepayment schemes could benefit many households, and an overall social protection network could help to mitigate the long-term effects of ill health on household well-being and support poverty reduction.
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                Author and article information

                Contributors
                rinshudwivedi999@gmail.com
                +918984360073 , jpp_pradhan@yahoo.co.uk
                Journal
                Int J Equity Health
                Int J Equity Health
                International Journal for Equity in Health
                BioMed Central (London )
                1475-9276
                14 January 2017
                14 January 2017
                2017
                : 16
                : 15
                Affiliations
                [1 ]Research Scholar Department of Humanities and Social Sciences, National Institute of Technology, Rourkela, Odisha 769 008 India
                [2 ]Department of Humanities and Social Sciences, National Institute of Technology, Rourkela, Odisha 769 008 India
                Article
                517
                10.1186/s12939-017-0517-y
                5237520
                28088198
                0e638339-44da-4ac5-83e4-933346260231
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 17 March 2016
                : 3 January 2017
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                Health & Social care
                equity,inequalities,healthcare utilisation,glrm,oope
                Health & Social care
                equity, inequalities, healthcare utilisation, glrm, oope

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