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      Has equity in government subsidy on healthcare improved in China? Evidence from the China’s National Health Services Survey

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          Abstract

          Background

          Monitoring the equity of government healthcare subsidies (GHS) is critical for evaluating the performance of health policy decisions. China’s low-income population encounters barriers in accessing benefits from GHS. This paper focuses on the distribution of China’s healthcare subsidies among different socio-economic populations and the factors that affect their equitable distribution. It examines the characteristics of equitable access to benefits in a province of northeastern China, comparing the equity performance between urban and rural areas.

          Methods

          Benefit incidence analysis was applied to GHS data from two rounds of China’s National Health Services Survey (2003 and 2008, N = 27,239) in Heilongjiang province, reflecting the information in 2002 and 2007 respectively. Concentration index (CI) was used to evaluate the absolute equity of GHSs in outpatient and inpatient healthcare services. A negative CI indicates disproportionate concentration of GHSs among the poor, while a positive CI indicates the GHS is pro-rich, a CI of zero indicates perfect equity. In addition, Kakwani index (KI) was used to evaluate the progressivity of GHSs. A positive KI denotes the GHS is regressive, while a negative value denotes the GHS is progressive.

          Results

          CIs for inpatient care in urban and rural residents were 0.2036 and 0.4497 respectively in 2002, and those in 2007 were 0.4433 and 0.5375. Likewise, CIs for outpatient care are positive in both regions in 2002 and 2007, indicating that both inpatient and outpatient GHSs were pro-rich in both survey periods irrespective of region. In addition, KIs for inpatient services were −0.3769 (urban) and 0.0576 (rural) in 2002 and those in 2007 were 0.0280 and 0.1868. KIs for outpatient service were -0.4278 (urban) and -0.1257 (rural) in 2002, those in 2007 were −0.2572 and −0.1501, indicating that equity was improved in GHS in outpatient care in both regions but not in inpatient services.

          Conclusions

          The benefit distribution of government healthcare subsidies has been strongly influenced by China’s health insurance schemes. Their compensation policies and benefit packages need reform to improve the benefit equity between outpatient and inpatient care both in urban and rural areas.

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          Most cited references17

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          Explaining trends in inequities: evidence from Brazilian child health studies.

          There is considerable international concern that child-health inequities seem to be getting worse between and within richer and poorer countries. The "inverse equity hypothesis" is proposed to explain how such health inequities may get worse, remain the same, or improve over time. We postulate that as new public-health interventions and programmes initially reach those of higher socioeconomic status and only later affect the poor, there are early increases in inequity ratios for coverage, morbidity, and mortality indicators. Inequities only improve later when the rich have achieved new minimum achievable levels for morbidity and mortality and the poor gain greater access to the interventions. The hypothesis was examined using three epidemiological data sets for time trends in child-health inequities within Brazil. Time trends for inequity ratios for morbidity and mortality, which were consistent with the hypothesis, showed both improvements and deterioration over time, despite the indicators showing absolute improvements in health status between rich and poor.
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            • Record: found
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            • Article: not found

            Measurement of Tax Progressivity: An International Comparison

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              How to do (or not to do) ... a benefit incidence analysis.

              Benefit incidence analysis (BIA) considers who (in terms of socio-economic groups) receive what benefit from using health services. While traditionally BIA has focused on only publicly funded health services, to assess whether or not public subsidies are 'pro-poor', the same methodological approach can be used to assess how well the overall health system is performing in terms of the distribution of service benefits. This is becoming increasingly important in the context of the growing emphasis on promoting universal health systems. To conduct a BIA, a household survey dataset that incorporates both information on health service utilization and some measure of socio-economic status is required. The other core data requirement is unit costs of different types of health service. When utilization rates are combined with unit costs for different health services, the distribution of benefits from using services, expressed in monetary terms, can be estimated and compared with the distribution of the need for health care. This paper aims to provide an introduction to the methods used in the 'traditional' public sector BIA, and how the same methods can be applied to undertake an assessment of the whole health system. We consider what data are required, potential sources of data, deficiencies in data frequently available in low- and middle-income countries, and how these data should be analysed.
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                Author and article information

                Contributors
                lei.si@utas.edu.au
                cms@njmu.edu.cn
                Andrew.Palmer@utas.edu.au
                Journal
                Int J Equity Health
                Int J Equity Health
                International Journal for Equity in Health
                BioMed Central (London )
                1475-9276
                10 January 2017
                10 January 2017
                2017
                : 16
                : 6
                Affiliations
                [1 ]Menzies Institute for Medical Research, University of Tasmania, Medical Science 1 Building, 17 Liverpool St (Private Bag 23), Hobart, TAS 7000 Australia
                [2 ]School of Health Administration, Anhui Medical University, Meishan Road 81, Hefei, 230032 Anhui Province People’s Republic of China
                [3 ]School of Health Policy & Management, Nanjing Medical University, 211166 Nanjing, China
                Article
                516
                10.1186/s12939-017-0516-z
                5223563
                e5387741-456f-4c36-a294-2d5aa374e33c
                © 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
                : 26 October 2016
                : 3 January 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 71503137
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                Health & Social care
                benefit incidence analysis,equity,government health subsidy,healthcare
                Health & Social care
                benefit incidence analysis, equity, government health subsidy, healthcare

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