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      Decomposing inequality in catastrophic health expenditure for self-reported hypertension household in Urban Shaanxi, China from 2008 to 2013: two waves’ cross-sectional study

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          Abstract

          Objective

          Despite the latest wave of China’s healthcare reform initiated in 2009 has achieved unprecedented progress in rural areas, little is known for specific vulnerable groups’ catastrophic health expenditure (CHE) in urban China. This study aims to estimate the trend of incidence, intensity and inequality of CHE in hypertension households (households with one or more than one hypertension patient) in urban Shaanxi, China from 2008 to 2013.

          Methods

          Based on the fourth and the fifth National Health Service Surveys of Shaanxi, we identified 460 and 1289 households with hypertension in 2008 and 2013, respectively for our analysis. We classified hypertension households into two groups: simplex households (with hypertension only) and mixed households (with hypertension plus other non-communicable diseases). CHE would be identified if out-of-pocket healthcare expenditure was equal to or higher than 40% of a household’s capacity to pay. Concentration index and its decomposition based on Probit regressions were employed to measure the income-related inequality of CHE.

          Results

          We find that CHE occurred in 11.2% of the simplex households and 22.1% of the mixed households in 2008, and the 21.5% of the simplex households and the 46.9% of mixed households incurred CHE in 2013. Furthermore, there were strong pro-poor inequalities in CHE in the simplex households (−0.279 and −0.283) and mixed households (−0.362 and −0.262) both in 2008 and 2013. The majority of observed inequalities in CHE could be associated with household economic status, household head’s health status and having elderly members.

          Conclusion

          We find a sharp increase of CHE occurrence and the sustained strong pro-poor inequalities for simplex and mixed households in urban Shaanxi Province of China from 2008 to 2013. Our study suggests that more concerns are needed for the vulnerable groups such as hypertension households in urban areas of China.

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          Most cited references26

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          The bounds of the concentration index when the variable of interest is binary, with an application to immunization inequality.

          When the health sector variable whose inequality is being investigated is binary, the minimum and maximum possible values of the concentration index are equal to micro-1 and 1-micro, respectively, where micro is the mean of the variable in question. Thus as the mean increases, the range of the possible values of the concentration index shrinks, tending to zero as the mean tends to one and the concentration index tends to zero. Examples are presented on levels of and inequalities in immunization across 41 developing countries, and on changes in coverage and inequalities in selected countries. Copyright (c) 2004 John Wiley & Sons, Ltd.
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            Inequality in household catastrophic health care expenditure in a low-income society of Iran.

            We assessed change in household catastrophic health care expenditures (CHE) and inequality in facing such expenditures in south-west Tehran. A cluster-sampled survey was conducted in 2003 using the World Health Survey questionnaire. We repeated the survey on the same sample in 2008 (635 and 603 households, respectively). We estimated the proportion of households facing CHE using the 'household's capacity to pay'. We identified the determinants of the household CHE using regression analysis and used the concentration index to measure socio-economic inequality and decompose it into its determinants factors. Findings showed that the proportion of household facing CHE had no significant change in this period (12.6% in 2003 vs 11.8% in 2008). The key determinants of CHE for both years were health care utilization and health care insurance status. Socio-economic status was the main contributor to inequality in CHE, while unequal utilization of dentistry and outpatient services had reduced the inequality in CHE between socio-economic groups. We observed no significant change in the CHE proportion despite policy interventions aimed at reducing such expenditures. Any solution to the problem of CHE should include interventions aimed at the determinants of CHE. It is essential to increase the depth of social insurance coverage by expanding the basic benefit package and reducing co-payments.
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              Non-evidence-based policy: how effective is China's new cooperative medical scheme in reducing medical impoverishment?

              In recent years, many lower to middle income countries have looked to insurance as a means to protect their populations from medical impoverishment. In 2003, the Chinese government initiated the New Cooperative Medical System (NCMS), a government-run voluntary insurance program for its rural population. The prevailing model of NCMS combines medical savings accounts with high-deductible catastrophic hospital insurance (MSA/Catastrophic). To assess the effectiveness of this approach in reducing medical impoverishment, we used household survey data from 2006 linked to claims records of health expenditures to simulate the effect of MSA/Catastrophic on reducing the share of individuals falling below the poverty line (headcount), and the amount by which household resources fall short of the poverty line (poverty gap) due to medical expenses. We compared the effects of MSA/Catastrophic to Rural Mutual Health Care (RMHC), an experimental model that provides first dollar coverage for primary care, hospital services and drugs with a similar premium but a lower ceiling. Our results show that RMHC is more effective at reducing medical impoverishment than NCMS. Under the internationally accepted poverty line of US$1.08 per person per day, the MSA/Catastrophic models would reduce the poverty headcount by 3.5-3.9% and the average poverty gap by 11.8-16.4%, compared with reductions of 6.1-6.8% and 15-18.5% under the RMHC model. The primary reason for this is that NCMS does not address a major cause of medical impoverishment: expensive outpatient services for chronic conditions. As such, health policymakers need first to examine the disease profile and health expenditure pattern of a population before they can direct resources to where they will be most effective. As chronic diseases impose a growing share of the burden on the population in developing countries, it is not necessarily true that insurance coverage focusing on expensive hospital care alone is the most effective at providing financial risk protection.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2019
                9 May 2019
                : 9
                : 5
                : e023033
                Affiliations
                [1 ] departmentSchool of Public Policy and Administration , Xi’an Jiaotong University , Xi’an, China
                [2 ] departmentGlobal Health Institute , Xi’an Jiaotong University , Xi’an, China
                [3 ] departmentInternational Business School , Xi’an Jiaotong-Liverpool University , Suzhou, China
                [4 ] departmentSchool of Public Health , Xi’an Jiaotong University School of Medicine , Xi’an, Shaanxi, China
                [5 ] departmentInstitute of Chinese Medical Sciences , University of Macau , Taipa, Macao
                [6 ] departmentDepartment of Health Policy and Management , Yale School of Public Health , New Haven, CT, USA
                [7 ] departmentDepartment of Economics , Yale University , New Haven, CT, USA
                Author notes
                [Correspondence to ] Dr Zhongliang Zhou; zzliang1981@ 123456163.com and Dr Xi Chen; xi.chen@ 123456yale.edu
                Article
                bmjopen-2018-023033
                10.1136/bmjopen-2018-023033
                6528006
                31076467
                3f720411-fe14-478c-9f2c-e033060cf606
                © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 18 March 2018
                : 25 December 2018
                : 01 February 2019
                Funding
                Funded by: Shaanxi provincial youth star of science and technology;
                Funded by: NIH;
                Funded by: the U.S. PEPPER Center Scholar Award;
                Funded by: FundRef http://dx.doi.org/10.13039/501100004543, China Scholarship Council;
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Funded by: Xi’an Jiaotong University;
                Funded by: National Program for Support of Top-notch Young Professionals;
                Funded by: FundRef http://dx.doi.org/10.13039/100001547, China Medical Board;
                Funded by: Shaanxi Soft Science;
                Categories
                Health Policy
                Research
                1506
                1703
                Custom metadata
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                Medicine
                catastrophic health expenditure,inequality,decomposition,hypertension,concentration index
                Medicine
                catastrophic health expenditure, inequality, decomposition, hypertension, concentration index

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