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      Inequality in the distribution of health resources and health services in China: hospitals versus primary care institutions

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          Abstract

          Background

          Equity is one of the major goals of China’s recent health system reform. This study aimed to evaluate the equality of the distribution of health resources and health services between hospitals and primary care institutions.

          Methods

          Data of this study were drawn from the China Health Statistical Year Books. We calculated Gini coefficients based on population size and geographic size, respectively, for the indicators: number of institutions, number of health workers and number of beds; and the concentration index (CI) for the indicators: per capita outpatient visits and annual hospitalization rates.

          Results

          The Gini coefficients against population size ranged between 0.17 and 0.44 in the hospital sector, indicating a relatively good equality. The primary care sector showed a slightly higher level of Gini coefficients (around 0.45) in the number of health workers. However, inequality was evident in the geographic distribution of health resources. The Gini coefficients exceeded 0.7 in the geographic distribution of institutions, health workers and beds in both the hospital and the primary care sectors, indicating high levels of inequality. The CI values of hospital inpatient care and outpatient visits to primary care institutions were small (ranging from -0.02 to 0.02), indicating good wealth-related equality. The CI values of outpatient visits to hospitals ranged from 0.16 to 0.21, indicating a concentration of services towards the richer populations. By contrast, the CI values of inpatient care in primary care institutions ranged from -0.24 to -0.22, indicating a concentration of services towards the poorer populations. The eastern developed region also had a high internal inequality compared with the other less developed regions.

          Conclusion

          Significant inequality in the geographic distribution of health resources is evident, despite a more equitable per capita distribution of resources. Richer people are more likely to use well-resourced hospitals for outpatient care. By contrast, poorer people are more likely to use poorly-resourced primary care institutions for inpatient care. There is a risk of the emergence of a two-tiered health care delivery system.

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          Most cited references24

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          Horizontal equity in health care utilization in Brazil, 1998–2008

          Introduction This study assesses trends in horizontal equity in the utilization of healthcare services from 1998 to 2008--a period of major economic and social change in Brazil. Methods Data are from nationally representative surveys repeated in 1998, 2003, and 2008. We apply established methods for assessing horizontal inequity in healthcare access (the principle that people with the same healthcare needs should have similar access to healthcare services). Horizontal inequity is calculated as the difference between observed healthcare utilization and utilization predicted by healthcare needs. Outcomes examined include the probability of a medical, dental, or hospital visit during the past 12 months; any health service use in the past two weeks; and having a usual source of healthcare. We use monthly family income to measure differences in socioeconomic position. Healthcare needs include age, sex, self-rated health, and chronic conditions. Non-need factors include income, education, geography, health insurance, and Family Health Strategy coverage. Results The probability of having at least one doctor visit in the past 12 months became substantially more equitable over time, ending with a slightly pro-rich orientation in 2008. Any hospitalization in the past 12 months was found to be pro-poor in all periods but became slightly less so in 2008. Dental visits showed the largest absolute decrease in horizontal inequity, although they were still the most inequitably (pro-rich) distributed outcome in 2008. Service use in the past two weeks showed decreased inequity in 2003 but exhibited no significant change between 2003 and 2008. Having a usual source of care became less pro-rich over time and was nearly income-neutral by 2008. Factors associated with greater inequities include income, having a private health plan, and geographic location. Factors associated with greater equity included health needs, schooling, and enrolment in the Family Health Strategy. Conclusions Healthcare utilization in Brazil appears to have become increasingly equitable over the past 10 years. Although this does not imply that equity in health outcomes has improved correspondingly, it does suggest that government policies aimed at increasing access, especially to primary care, have helped to make healthcare utilization in Brazil fairer over time.
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            Regional inequality in health and its determinants: evidence from China.

            Health inequality is a problem with great political importance all over the world. Urban-rural inequality in health has attracted great attentions in recent years in China, but very few researches have been undertaken into regional discrepancies in health. This research aims at measuring the degree of regional health inequality in China and identifying its determinants. Indicators for health, socioeconomic status, health resources and health services delivery were selected through Delphi consultations from 18 experts. With cross-sectional data from 31 provinces, composite health indexes were generated. The regional inequality in health was described by Lorenz curve and measured by Gini coefficient. The determinants of health inequality were identified through canonical correlation analysis. The results showed that there existed distinct regional disparities in health in China, which were mainly reflected in "Maternal & Child Health" and "Infectious Diseases", not in the most commonly used health indicator average life expectancy. The regional health inequality in China was increasing with the rapid economic growth. The regional health inequality was associated with not only the distribution of wealth, but also the distribution of health resources and primary health care services. Policy makers need to be aware of three major challenges when they try to achieve and maintain equality in distribution of health: First, the most commonly used health indicators are not necessarily sensitive enough to detect health inequalities. Second, increase in health inequality is often accompanied with rapid economic growth and increase in life expectancy. Countries in transition are facing the greatest challenge in developing a fair and equitable health care system. Finally, investment in health resources does bring about differences in distribution of health. However, primary health care plays a more important role than hospital services in reducing regional disparities in health.
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              How does the New Cooperative Medical Scheme influence health service utilization? A study in two provinces in rural China

              Background Many countries are developing health financing mechanisms to pursue the goal of universal coverage. In China, a rural health insurance system entitled New Cooperative Medical Scheme (NCMS) is being developed since 2003. Although there is concern about whether the NCMS will influence the serious situation of inequity in health service utilization in rural China, there is only limited evidence available. This paper aims to assess the utilisation of outpatient and inpatient services among different income groups and provinces under NCMS in rural China. Methods Using multistage sampling processes, a cross-sectional household survey including 6,147 rural households and 22,636 individuals, was conducted in six counties in Shandong and Ningxia Provinces, China. Chi-square test, Poisson regression and log-linear regression were applied to analyze the association between NCMS and the utilization of outpatient and inpatient services and the length of stay for inpatients. Qualitative methods including individual interview and focus group discussion were applied to explain and complement the findings from the household survey. Results NCMS coverage was 95.9% in Shandong and 88.0% in Ningxia in 2006. NCMS membership had no significant association with outpatient service utilization regardless of income level and location. Inpatient service utilization has increased for the high income group under NCMS, but for the middle and low income, the change was not significant. Compared with non-members, NCMS members from Ningxia used inpatient services more frequently, while members from Shandong had a longer stay in hospital. High medical expenditure, low reimbursement rate and difference in NCMS policy design between regions were identified as the main reasons for the differences in health service utilization. Conclusions Outpatient service utilization has not significantly changed under NCMS. Although utilization of inpatient service in general has increased under NCMS, people with high income tend to benefit more than the low income group. While providing financial protection against catastrophic medical expenditure is the principal focus of NCMS, this study recommends that outpatient services should be incorporated in future NCMS policy development. NCMS policy should also be more equity oriented to achieve its policy goal.
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                Author and article information

                Contributors
                lucky1230405@163.com
                xyjdyx@126.com
                18768429445@163.com
                984077581@qq.com
                c.liu@latrobe.edu.au
                Journal
                Int J Equity Health
                Int J Equity Health
                International Journal for Equity in Health
                BioMed Central (London )
                1475-9276
                3 March 2017
                3 March 2017
                2017
                : 16
                : 42
                Affiliations
                [1 ]ISNI 0000 0001 2230 9154, GRID grid.410595.c, School of Medicine, , Hangzhou Normal University, ; Hangzhou, Zhejiang 310036 China
                [2 ]ISNI 0000 0001 0599 1243, GRID grid.43169.39, School of Public Policy and Administration, , Xi’an Jiaotong University, ; Xi’an, Shaanxi 710000 China
                [3 ]ISNI 0000 0001 2342 0938, GRID grid.1018.8, School of Psychology and Public Health, , La Trobe University, ; Melbourne, 3086 Australia
                Article
                543
                10.1186/s12939-017-0543-9
                5335774
                28253876
                da5b6372-1b4b-427f-8001-c8bfe4181327
                © 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
                : 22 September 2016
                : 24 February 2017
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                Health & Social care
                equity,hospitals,primary care institutions,health resources,health services
                Health & Social care
                equity, hospitals, primary care institutions, health resources, health services

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