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      Analyzing the efficiency of Chinese primary healthcare institutions using the Malmquist-DEA approach: Evidence from urban and rural areas

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          Abstract

          Background

          China has been increasing the investment in Primary Health Care Institutions (PHCIs) since the launch of the New Health Care System Reform in 2009. It is a crucial concern whether the PHCIs can meet residents' need both in urban and rural with the limited government finance, especially encountering the challenge of the COVID-19. This study aimed to reveal the trend of the primary health service efficiency in the past decade, compare the urban-rural differences, and explore relevant factors.

          Methods

          DEA and Malmquist models were applied to calculate the health service efficiency of PHCIs among 28 provinces in China, with the input variables including the number of institutions, number of beds, number of health technicians, and the outputs variables including the number of outpatients and emergency visits, number of discharged patients. And the Tobit model was used to analyze the factors on the efficiency in urban and rural. A sensitivity analysis for model validations was also carried out.

          Results

          The average technical efficiency (TE) of urban PHCIs fluctuated from 63.3% to 67.1%, which was lower than that in rural (75.8–82.2%) from 2009 to 2019. In terms of dynamic efficiency, the urban PHCIs performed better than the rural, and the trends in the total factor productivity change were associated with favorable technology advancement. The population density and dependency ratio were the key factors on TE in both of the urban and rural PHCIs, and these two factors were positively correlated to TE. In terms of TE, it was negatively correlated with the proportion of total health expenditure as a percentage of GDP in urban PHCIs, while in rural it was positively correlated with the urbanization rate and negatively correlated with GDP per capita. Besides, the tests of Mann–Whitney U, and Kruskal–Wallis H indicated the internal validity and robustness of the chosen DEA and Malmquist models.

          Conclusions

          It needs to reduce the health resource wastes and increase service provision in urban PHCIs. Meanwhile, it is necessary to strengthen medical technology and gaining greater efficiency in rural PHCIs by technology renovation.

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          Most cited references60

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          Measuring the efficiency of decision making units

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            Contribution of primary care to health systems and health.

            Evidence of the health-promoting influence of primary care has been accumulating ever since researchers have been able to distinguish primary care from other aspects of the health services delivery system. This evidence shows that primary care helps prevent illness and death, regardless of whether the care is characterized by supply of primary care physicians, a relationship with a source of primary care, or the receipt of important features of primary care. The evidence also shows that primary care (in contrast to specialty care) is associated with a more equitable distribution of health in populations, a finding that holds in both cross-national and within-national studies. The means by which primary care improves health have been identified, thus suggesting ways to improve overall health and reduce differences in health across major population subgroups.
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              The primary health-care system in China

              China has made remarkable progress in strengthening its primary health-care system. Nevertheless, the system still faces challenges in structural characteristics, incentives and policies, and quality of care, all of which diminish its preparedness to care for a fifth of the world's population, which is ageing and which has a growing prevalence of chronic non-communicable disease. These challenges include inadequate education and qualifications of its workforce, ageing and turnover of village doctors, fragmented health information technology systems, a paucity of digital data on everyday clinical practice, financial subsidies and incentives that do not encourage cost savings and good performance, insurance policies that hamper the efficiency of care delivery, an insufficient quality measurement and improvement system, and poor performance in the control of risk factors (such as hypertension and diabetes). As China deepens its health-care reform, it has the opportunity to build an integrated, cooperative primary health-care system, generating knowledge from practice that can support improvements, and bolstered by evidence-based performance indicators and incentives.
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                Author and article information

                Contributors
                Journal
                Front Public Health
                Front Public Health
                Front. Public Health
                Frontiers in Public Health
                Frontiers Media S.A.
                2296-2565
                02 February 2023
                2023
                : 11
                : 1073552
                Affiliations
                [1] 1School of Public Policy and Management, Guangxi University , Nanning, China
                [2] 2Health Policy Research Center, Guangxi Medical University , Nanning, China
                [3] 3School of Public Policy and Administration, Chongqing University , Chongqing, China
                Author notes

                Edited by: Victoria Seewaldt, Beckman Research Institute, United States

                Reviewed by: Ahmed Mohamed Habib, Independent Researcher, Zagazig, Egypt; Wasi Ul Hassan Shah, Zhejiang Shuren University, China

                *Correspondence: Xianjing Qin ✉ qinxianjing@ 123456gxmu.edu.cn

                This article was submitted to Family Medicine and Primary Care, a section of the journal Frontiers in Public Health

                Article
                10.3389/fpubh.2023.1073552
                9931751
                36817900
                740cc36e-649e-4003-9c02-021adaabe1e3
                Copyright © 2023 Zhou, Peng, Chang, Liu, Gao, Zhao, Li, Feng and Qin.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 18 October 2022
                : 16 January 2023
                Page count
                Figures: 1, Tables: 9, Equations: 3, References: 61, Pages: 13, Words: 10622
                Funding
                Funded by: National Social Science Fund of China, doi 10.13039/501100012456;
                Award ID: 17AGL023
                This research was supported by the National Social Science Foundation of China (No. 17AGL023).
                Categories
                Public Health
                Original Research

                primary healthcare institutions,relative efficiency,data envelopment analysis,malmquist index,urban-rural areas,china

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