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Objective @#To investigate equity of resource allocation in ophthalmology departments of medical institutions in Shenzhen City, so as to provide insights into the optimization of resource allocation in ophthalmology departments in Shenzhen City.@* Methods @#The numbers of beds and ophthalmologists in ophthalmology departments of medical institutions in Shenzhen City were collected through the Shenzhen Health Statistical Yearbook 2019. The distribution of resources and equity of resource allocation were evaluated in ophthalmology departments of Shenzhen City using Lorenz curve and Gini coefficient.@* Results @#There were 5.95 beds and 4.62 ophthalmologists in ophthalmology departments per 100 000 permanent residents in Shenzhen City in 2019. There were 13.35 beds and 9.51 ophthalmologists in ophthalmology departments per 100 000 permanent residents within the former special zone (Luohu, Futian, Nanshan and Yantian districts), and 2.17 beds and 2.13 ophthalmologists in ophthalmology departments per 100 000 permanent residents outside the former special zone (Guangming, Baoan, Longhua, Longgang, Pingshan districts and Dapeng New Area). The Gini coefficients of beds and ophthalmologists in ophthalmology departments were 0.348 and 0.243 by permanent residents in Shenzhen City, 0.386 and 0.386 within the former special zone and 0.086 and 0.012 outside the former special zone, respectively. The Lorenz curves of beds and ophthalmologists in ophthalmology departments were closer to the equity line outside the former special zone in relative to within the former special zone. @* Conclusion@#The gross number of beds and ophthalmologists remains to be increased in ophthalmology departments of medical institutions in Shenzhen City, and the equity of regional resource allocation is poor, which is mainly characterized by resource scarcity in ophthalmology departments outside the former special zone.
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Objective:To investigate the basic situation of clinical nuclear medicine resources and their application in medical institutions of Jiangsu province, in order to grasp their distribution characteristics and make an evaluation briefly on distribution eaquity of nuclear medicine resources and application.Methods:In the form of online questionnaire, the basic information in the medical institutions conducting clinical nuclear medicine diagnosis and treatment in the provice was collected, including the number and model of nuclear medicine equipment, the number of protection devices, the number of nuclear medicine employees and the application frequency of nuclear medicine.Results:In 2020 in Jiangsu province, there were 67 nuclear medicine institutions, 727 employees and 95 nuclear medicine tomography equipment including 38 positron emission tomography (PET) equipment and 54 single photon emission computed tomography (SPECT) equipment. The frequencies of imaging and treatment in the medical institutions were 259, 686 and 12 186, with average frequency of 3.21 expressed per 1 000 population. The Gini coefficients of nuclear medicine equipment, employees and application based on population distribution in Jangsu province were 0.25, 0.30 and 0.34, respectively. The related Theil indices were 0.044 9, 0.062 6 and 0.085 2, respectively.Conclusions:The nuclear medicine developed quickly in Jiangsu province in the past ten years. The distribution of all kinds of nuclear medicine resources and application on the basis of continuous increase showed a certain degree of imbalance, and correlation with the level of regional economic development.
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Objective To analyze the equity and efficiency of resource allocation for management and treatment of severe mental disorders in Shanghai in 2020, and to provide a foundation for making relevant policies. Methods Data on resource allocation for the management and treatment of severe mental disorders in 17 district-level mental health institutions in 2020 were collected. The Gini coefficient was used to evaluate the equity of resource allocation by population and geographic area, and data envelopment analysis was carried out to analyze the equity of resource allocation. Results The Gini coefficients of special funds, psychiatric medical staff and actual open beds according to population were 0.24, 0.25 and 0.27, respectively. The Gini coefficients according to area were 0.54, 0.62 and 0.64, respectively. The average efficiency of resource allocation was 0.865. There were 5 institutions where DEA was effective, accounting for 29.41%. There were 12 institutions where DEA was non-effective, accounting for 70.59%. Conclusion The equity of resources allocation for the management and treatment of severe mental disorders according to population is good, but the equity of allocation based on geographic area is not high. The efficiency of resource allocation needs to be further improved. It is suggested that the resource allocation should be optimized to promote the fairness and efficiency of resource allocation for the management and treatment of severe mental disorders.
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OBJECTIVE@#To analyze the long-term trends of the changes in the equity of China's health workforce allocation to provide a reference for the more balanced and orderly development of China's health system.@*METHODS@#The Gini coefficient was used to evaluate the degree of equity in the allocation of health workforce between regions, and the Gini coefficients for the allocation of doctors and nurses based on population and regional gross domestic product (GDP) distribution were calculated respectively.@*RESULTS@#In 2019, the number of licensed (assistant) physicians per 1 000 population in China was 2.77, and the number of registered nurses per 1 000 population was 3.18. The Gini coefficient for the distribution of licensed (assistant) physicians by population was 0.141 in 2002, decreasing to 0.081 by 2014 and then remained stable. The Gini coefficient for the distribution of registered nurses by population was 0.164 in 2002 and decreased to 0.066 in 2018. The Gini coefficient for the distribution of licensed (assistant) physicians by GDP was 0.236 in 2002, decreased to 0.169 in 2013, then increased to 0.183 and remained stable. The Gini coefficient for the distribution of registered nurses by GDP was 0.206 in 2002, decreased to 0.150 in 2013, and then increased each year to 0.180 in 2019. The equity of the allocation of registered nurses by population was worse than the equity of the allocation of licensed (assistant) physicians in 2002, and in 2016, for the first time, exceeded that of licensed (assistant) physicians.@*CONCLUSION@#Equity in the allocation of health workforce across China has improved, but the improvement in equity between regions has hit a bottleneck, with health workforce allocation in the western regions still relatively scarce. Although nursing workforce allocation equity caught up with licensed (assistant) physicians, the number of licensed (assistant) physicians is close to that of developed western countries, while there is a large gap in registered nurses. It is recommended that the relevant authorities make good long-term planning for health workforce, further increase the policy for the introduction of health workforce in the western region, and increase the supply of healthcare services in the western region with the help of digital transformation of healthcare and internet healthcare. At the same time, they should further increase investment in resources for higher nursing education and actively plan to cope with the ageing population.
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Humans , China , Health Equity , Health Services , Health Workforce , WorkforceABSTRACT
Introducción. La adecuada dotación y distribución con equidad de recursos humanos son fundamentales para el desempeño del sistema de salud, especialmente en el primer nivel de atención. El Programa Servicio Rural y Urbano Marginal (SERUMS) es la principal estrategia desarrollada por el Estado peruano para este fin. Objetivo. Describir el efecto de la dotación de médicos, enfermeros y obstetras del Programa SERUMS en la equidad de la distribución de recursos humanos en el primer nivel de atención. Métodos. Estudio observacional, descriptivo y transversal, de carácter censal con base en el Registro Nacional de Personal de Salud - INFORHUS, agosto 2019. Se aplicó indicadores de dotación, se verificó si existe diferencia entre la distribución porcentual de profesionales SERUMS y no SERUMS, se calculó la densidad (profesionales/10 000 hab. a nivel departamental, quintil de pobreza y ruralidad) y coeficientes de Gini (departamental). Resultados. La población estuvo constituida por 6037 profesionales SERUMS y 27 495 no SERUMS. El Programa SERUMS incrementó de manera importante la dotación y densidad de profesionales en casi todas las regiones del país. En 5 regiones los profesionales SERUMS representaron más del 50% de la dotación. Incrementos importantes se encontraron en el análisis por quintil de pobreza y en el ámbito rural, especialmente en la dotación de médicos. El programa SERUMS evidenció una mayor desigualdad en su distribución, según los coeficientes de Gini, a favor de las poblaciones más vulnerables. Conclusiones. El Programa SERUMS incrementa de manera importante la dotación y densidad de profesionales, especialmente en los distritos más pobres del Perú.
Introduction. The adequate allocation and equitable distribution of human resources are essential for the health system›s performance, especially at the first level of care. The Rural and Urban Marginal Service Program (SERUMS) is the primary strategy developed by the Peruvian State for this purpose. Objective. To describe the effect of the number of doctors, nurses, and midwives of the SERUMS Program on the equity of the distribution of human resources at the primary care level. Methods. Observational, descriptive, and cross-sectional study of a census nature based on the National Registry of Health Personnel - INFORHUS, August 2019. Staffing indicators were applied, it was verified if there is a difference between the percentage distribution of SERUMS and non-SERUMS professionals, density (professionals per 10 000 inhabitants at the departmental level, poverty quintile, and rurality), and Gini coefficients (departmental) were calculated. Results. The population consisted of 6037 SERUMS professionals and 27 495 non-SERUMS professionals. The SERUMS Program significantly increased the number and density of professionals in almost all departments. In 5 regions, SERUMS professionals represented more than 50% of the workforce. Significant increases in the number of doctors were found in the poverty quintile and rural areas analysis. According to the Gini coefficients, the SERUMS program showed greater inequality in its distribution in favor of the most vulnerable populations. Conclusions. The SERUMS Program significantly increases the number and density of healthcare professionals, especially in the poorest districts of Peru.
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Objective:To analyze the equity of community health resource allocation available to the elderly in Shanghai to provide a reference for the optimization of their allocation and to ensure the basic medical needs of the elderly.Methods:116 community health service centers were selected as research objects. Based on the human resources and financial inputs for community health, the Gini coefficient and Theil index were used to analyze the equity of community health resource allocation in Shanghai from the service population and across geographical dimensions.Results:The Gini coefficients of in-service health technicians and total financial compensation, as based upon the dimension of serving the elderly population, were 0.116 and 0.251, respectively, while the Gini coefficients based on the geographical dimension were 0.483 and 0.329 (respectively). The results of the Theil index analysis are relatively consistent with the Gini coefficient. The equity of health human resource allocation is slightly better than that of financial investment, and the equity of health resource allocation population is better than that concerning geography. Regional differences are the main factors regarding the equity of health resource allocation of the elderly community based on geographical factors (71.47%-86.71%), intra-regional differences were the main source of equity differences in community health resources allocation based on the elderly population (52.52%-89.44%).Conclusion:The allocation structure of community health resources for the elderly in Shanghai is, on the whole, fair; but, the differences between population equity and geographical equity, and between and within regional plates, cannot be ignored.
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Objectives To analyze the allocation of major health resources in each district of Shenzhen from 2015 to 2019, to evaluate the equity of allocation, and to provide a reference for further optimizing the allocation of health resources. Methods Based on the statistics and analysis of the distribution of major health resources in Shenzhen from 2015 to 2019, the Gini coefficient was used to evaluate the equity of health resources allocation in Shenzhen from two dimensions of population and geography, and to analyze the trend of change. Results From 2015 to 2019, the total amount of health resources in Shenzhen maintained a rapid average annual increase of about 7.21%. The number of beds, doctors and nurses per every thousand people reached 3.81, 2.86 and 3.29, respectively. The Gini coefficients of each indicator decreased year by year. The Gini coefficient of population distribution was less than 0.3, and the Gini coefficient of geographical distribution was close to 0.5, exceeding the warning line. Conclusion The total amount of health resources in Shenzhen is insufficient and the distribution is uneven. The government should increase investment in health resources while taking into account the regional balance to improve the fairness of allocation.
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To analyze the global burden of periodontal disease and its relation with socioeconomic development. Data of global disability-adjusted life year (DALY) due to periodontal disease and human development index (HDI) from 1990 to 2019 were obtained from Global Health Data Exchange (GHDx) and human development reports. The trend of the global burden of periodontal disease from 1990 to 2019 was described. The correlation between age-standardized DALY rates and HDI were examined in 2019, and between-country periodontal disease burden inequality from 1990 to 2019 was measured using health-related Gini coefficients and concentration indexes. From 1990 to 2019, the global DALY rate due to periodontal disease increased from 78.63 to 85.48, and the epidemiological burden did not increase significantly. Statistical differences were found across different HDI categories for age-standardized DALY rates of periodontal disease ( 44.315, <0.01) in 2019. Linear regression analysis also revealed a negative correlation between age-standardized DALY rate of periodontal disease and HDI ( = -0.417, <0.01) . Gini coefficients decreased from 0.361 to 0.281 and concentration indexes fell from 0.0339 to -0.0538 between 1990 and 2019. The global burden of periodontal disease did not increase between 1990 and 2019, though the socioeconomic-associated inequality still existed. The burden of periodontal disease was more concentrated in less developed countries, and the socioeconomic-associated inequality has increased since 2000.
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Humans , Disability-Adjusted Life Years , Global Health , Periodontal Diseases/epidemiology , Quality-Adjusted Life Years , Socioeconomic FactorsABSTRACT
【Objective】 To study the fairness of blood bank resources allocation in China, aimed at providing references for reasonable allocation of blood bank resources. 【Methods】 A questionnaire survey was conducted among 32 provincial blood centers and 321 regional central blood banks across China in August 1~25, 2018. Resource allocation of blood banks in China was analyzed using descriptive methods, and the fairness of resource allocation were analyzed using Lorenz curve, Gini coefficient and Theil index. 【Results】 Blood bank resources and services showed an overall upward trend from 2013 to 2017. The fairness of institutional coverage was optimal in 2017 according to the Lorenz curve and Gini coefficient, suggesting the allocation of blood bank resources according to the population was better than geographic area. The fairness of health technicians staffing was the worst from the perspective of geographic area. The total Theil index was 0.448 5~0.526 7, and the differences was contributed more by intra group comparison than that of inter group. 【Conclusion】 The unbalanced development underlying in the provincial and regional blood centers has been observed, and the service capacity needs to be further improved. The resource allocation varies greatly among regions, and it is recommended to optimize the regional planning of blood bank resources.
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RESUMO: Objetivo: Avaliar, por meio de análise espaçotemporal, se a desigualdade econômica das Unidades Federativas (UF) do Brasil pode estar associada com o risco de infecção e morte por COVID-19. Métodos: Trata-se de um estudo ecológico, baseado em dados secundários das taxas de incidência e mortalidade para COVID-19. Os dados foram analisados em nível estadual, tendo como principal variável independente o coeficiente de Gini. Foram utilizados os registros de 12 dias, espaçados em uma semana cada, entre 21 de abril e 7 de julho de 2020. A variação semanal das taxas foi calculada pela regressão de Prais-Winsten, com o objetivo de medir a evolução da pandemia em cada UF. O teste de correlação de Spearman foi empregado para avaliar a correlação entre as taxas e suas evoluções semanais e as variáveis independentes. Por fim, realizou-se diagnóstico de dependência espacial dos dados e usou-se o modelo de defasagem da regressão espacial, quando aplicável. Resultados: As taxas de incidência e mortalidade por COVID-19 foram crescentes em todas as UF brasileiras, tendo sido mais acentuada entre aquelas com maior desigualdade econômica. A associação entre coeficiente de Gini e incidência e mortalidade por COVID-19 manteve-se mesmo quando levados em consideração aspectos demográficos e espaciais. Conclusão: A desigualdade econômica pode exercer papel importante no impacto da COVID-19 em território brasileiro, por meio de efeitos absolutos e contextuais. Políticas estruturais para a redução da desigualdade são fundamentais para o enfrentamento dessa e de futuras crises sanitárias no Brasil.
ABSTRACT: Objective: To assess, through space-time analyses, whether the income inequality of the Federative Units (FUs) in Brazil can be associated with the risk of infection and death by COVID-19. Methods: This was an ecological study, based on secondary data on incidence and mortality rates for COVID-19. Data were analyzed at the state level, having the Gini coefficient as the main independent variable. Records of twelve days were used, spaced one week each, between April 21th and June 7th, 2020. The weekly variation in the rates was calculated through Prais-Winsten regression, aiming at measuring the evolution of the pandemic in each FU. Spearman's correlation test was used to assess correlation between the rates and their weekly evolution and the independent variables. Lastly, a spatial dependence diagnosis was conducted, and a Spatial Regression lag model was used when applicable. Results: Incidence and mortality rates of COVID-19 increased in all Brazilian FUs, being more pronounced among those with greater economic inequality. Association between Gini coefficient and COVID-19 incidence and mortality rates remained even when demographic and spatial aspects were taken into account. Conclusion: Income inequality can play an important role in the impact of COVID-19 on the Brazilian territory, through absolute and contextual effects. Structural policies to reduce inequality are essential to face this and future health crises in Brazil.
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Humans , Pneumonia, Viral/epidemiology , Coronavirus Infections/epidemiology , Health Status Disparities , Pandemics , Pneumonia, Viral/mortality , Socioeconomic Factors , Brazil/epidemiology , Coronavirus Infections/mortality , Risk Assessment , COVID-19ABSTRACT
ABSTRACT: We used the data of the China Labor-force Dynamics Survey 2014 to examine the effects of livelihood capitals which include natural, material, human, financial, and social capitals on total household income, per capita income, agricultural income, wage income, operational income, and property income inequality among rural households in China. Results showed that different kinds of livelihood capitals have different effects on different types of rural households' income. Specifically; (1) although, the area of cultivated land reduces agricultural income inequality, it increases per capita income inequality. (2) Forest land area enlarges per capita income inequality and total household income inequality. (3) Tractor variable reduces inequality in agricultural income and total household income. (4) While reducing the property income inequality, education variable enlarges the wage income inequality, the per capita income inequality and the total household income inequality. (5) Book variable reduces property income inequality. (6) Loan variable increases inequality in agricultural incomes. (7) Party variable reduces the agricultural income inequality. (8) Although, the internet variable increases agricultural income inequality, and property income inequality, it reduces wage income inequality, operational income inequality, per capita income, and total household income inequality.
RESUMO: Utilizamos os dados da Pesquisa de Dinâmica da Força de Trabalho da China de 2014 para examinar os efeitos dos capitais de subsistência, que incluem capitais natural, material, humano, financeiro e social sobre a renda total da família, renda per capita, renda agrícola, renda salarial, renda operacional e desigualdade de renda da propriedade entre as famílias rurais da China. Os resultados mostraram que diferentes tipos de capitais de subsistência têm efeitos diferentes sobre os diferentes tipos de renda das famílias rurais. Especificamente, (1) embora a área de terra cultivada reduza a desigualdade de renda agrícola, aumenta a desigualdade de renda per capita. (2) A área florestal aumenta a desigualdade de renda per capita e a desigualdade total de renda familiar. (3) A variável trator reduz a desigualdade na renda agrícola e na renda familiar total. (4) Embora reduza a desigualdade de renda da propriedade, a variável educação aumenta a desigualdade de renda salarial, a desigualdade de renda per capita e a desigualdade total de renda familiar. (5) A variável contábil reduz a desigualdade de renda da propriedade. (6) A variável empréstimo aumenta a desigualdade na renda agrícola. (7) A variável partidária reduz a desigualdade de renda agrícola. (8) Embora a variável internet aumente a desigualdade de renda agrícola e a desigualdade de renda da propriedade, reduz a desigualdade de renda salarial, a desigualdade de renda operacional, a renda per capita e a desigualdade total de renda familiar.
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Objective@#Allocation of human resources to address inequalities in the public health system has increasingly attracted societal and political attention. Using the Centers for Disease Control and Prevention (CDCs) system of China as an example, we evaluated inequality in the public health workforce distribution across different regions in China between 2008 and 2017, with the aim of providing information for policymakers to support resource allocation and address growing health inequities.@*Methods@#We used three standard public health workforce inequality indices - Gini coefficient, Theil L, and Theil T - and spatial autocorrelation analysis to explore spatial clusters of the workforce in different provinces, visualized with geographical tools.@*Results@#The aggregate workforce-to-population ratio decreased from 1.47 to 1.42 per 10,000 population from 2008 to 2017, and was consistently lower than the National Health Commission's (NHC) recommended critical shortage threshold of 1.75. The workforce distribution inequality indices varied by regional socioeconomic and health system development. Geographic clustering of CDCs workforce distribution was evident, with H-H and L-L clusters in western China and the Guangdong-Fujian region, respectively.@*Conclusions@#Our study addressed key issues for government and policymakers in allocation of public health human resources. There is an urgent need for careful identification of analytic questions that will help carry out public health functions in the new era, alongside policy implications for an equitable distribution of the public health workforce focusing on the western region and low-low cluster areas.
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China , Health Workforce , Public Health , Socioeconomic FactorsABSTRACT
Abstract Background: The Gini coefficient is a statistical tool generally used by economists to quantify income inequality. However, it can be applied to any kind of data with unequal distribution, including heart rate variability (HRV). Objectives: To assess the application of the Gini coefficient to measure inequality in power spectral density of RR intervals, and to use this application as a psychophysiological indicator of mental stress. Methods: Thirteen healthy subjects (19 ± 1.5 years) participated in this study, and their RR intervals were obtained by electrocardiogram during rest (five minutes) and during mental stress (arithmetic challenge; five minutes). These RR intervals were used to obtain the estimates of power spectral densities (PSD). The limits for the PSD bands were defined from 0.15 to 0.40 Hz for high frequency band (HF), from 0.04 to 0.15 Hz for low frequency band (LF), from 0.04 to 0.085 Hz for first low frequency sub-band (LF1) and from 0.085 to 0.15 Hz for second low frequency sub-band (LF2). The spectral Gini coefficient (SpG) was proposed to measure the inequality in the power distribution of the RR intervals in each of above-mentioned HRV bands. SpG from each band was compared with its respective traditional index of HRV during the conditions of rest and mental stress. All the differences were considered statistically significant for p < 0.05. Results: There was a significant decrease in HF power (p = 0.046), as well as significant increases in heart rate (p = 0.004), LF power (p = 0.033), LF2 power (p = 0.019) and LF/HF (p = 0.002) during mental stress. There was also a significant increase in SpG(LF) (p = 0.009) and SpG(LF2) (p = 0.033) during mental stress. Coefficient of variation showed SpG has more homogeneity compared to the traditional index of HRV during mental stress. Conclusions: This pilot study suggested that spectral inequality of Heart Rate Variability analyzed using the Gini coefficient seems to be an independent and homogeneous psychophysiological indicator of mental stress. Also, HR, LF/HF, SpG(LF) of HRV are possibly important, reliable and valid indicators of mental stress.
Resumo Fundamento: O coeficiente de Gini é um instrumento estatístico geralmente usado por economistas para quantificar a desigualdade de renda. No entanto, ele pode ser aplicado a qualquer tipo de dados com distribuição desigual, incluindo a variabilidade da frequência cardíaca (VFC). Objetivos: Avaliar a aplicação do coeficiente de Gini para medir a desigualdade na densidade espectral de potência de intervalos RR, e usar esta aplicação como um indicador psicofisiológico do estresse mental. Métodos: Treze indivíduos saudáveis (19 ± 1,5 anos) participaram deste estudo, e seus intervalos RR foram obtidos por eletrocardiograma durante repouso (cinco minutos) e durante estresse mental (desafio aritmético; cinco minutos). Esses intervalos RR foram utilizados para obter as estimativas de densidades espectrais de potência (PSD). Os limites para as bandas PSD foram definidos de 0,15 a 0,40 Hz para banda de alta frequência (HF), de 0,04 a 0,15 Hz para banda de baixa frequência (LF), de 0,04 a 0,085 Hz para a primeira sub-banda de baixa frequência (LF1) e de 0,085 a 0,15 Hz para a segunda sub-banda de baixa frequência (LF2). O coeficiente de Gini espectral (SpG) foi proposto para medir a desigualdade na distribuição de potência dos intervalos RR em cada uma das bandas de VFC mencionadas acima. O SpG de cada banda foi comparado com seu respectivo índice tradicional de VFC durante as condições de repouso e de estresse mental. Todas as diferenças foram consideradas estatisticamente significativas para p < 0,05. Resultados: Houve uma diminuição significativa no poder de FC (p=0,046), bem como aumentos significativos na frequência cardíaca (p = 0,004), potência da LF (p = 0,033), potência da LF2 (p = 0,019) e LF/HF (p = 0,002) durante estresse mental. Houve também um aumento significativo de SpG(LF) (p = 0,009) e SpG(LF2) (p = 0,033) durante estresse mental. O coeficiente de variação mostrou que o SpG tem mais homogeneidade em comparação com o índice tradicional de VFC durante o estresse mental. Conclusões: Este estudo piloto sugeriu que a desigualdade espectral da VFC analisada pelo coeficiente de Gini parece ser um indicador psicofisiológico independente e homogêneo de estresse mental. Além disso, FC, LF/HF, SpG(LF) da VFC são possivelmente indicadores importantes, confiáveis e válidos de estresse mental.
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Humans , Male , Female , Adolescent , Young Adult , Stress, Psychological/physiopathology , Heart Rate/physiology , Reference Values , Case-Control Studies , Pilot Projects , Reproducibility of Results , ROC Curve , Statistics, Nonparametric , Cross-Over Studies , ElectroencephalographyABSTRACT
Objective To analyze the allocation and equity of Class-A and Class-B large medical equipment in Shanghai, and to compare them with those in other parts of China and in other OECD countries. Methods The data of large medical equipments were collected from the Health and Family Planning Commission of Shanghai, government websites, relevant research reports and the database of OECD. Gene-coefficients were adopted to evaluate the equity of large equipment allocation. Results In terms of Class-A and Class B large equipments like CTs, MRIs and DSAs per million population, the number for Shanghai by the end of 2015, was 1.325, 5.30, 2.13 and 3.81 units respectively. Except for CTs, this figure was higher than national average, yet lower than average of other OECD countries. In addition, the equity in allocation of Class-B large medical equipment was better than that of Class-A large medical equipment in Shanghai. Conclusions The overall deployment level of large medical equipments in Shanghai remains to be increased, and the equity in allocation of Class-A large medical equipment deserves more attention.
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Objective To analyze family clustering of outpatient service utilization in rural areas of China.Method Outpatient service information of all families in rural area of sample county was obtained on the basis of new cooperative medical system (NCMS) outpatient database,and family outpatient service utilization database was cleared out with the help of functions like IF,LOOKUP and so on in Excel 2010.Lorentz curve was drawn by area graph and scatter diagram with Excel 2010,so was Gini coefficient.Descriptive statistic,variance analysis and so on were carried by IBM SPSS Statistic 20.0.Result 20％ family takes up 53％ of outpatient service,and rural family's Gini coefficient of outpatient service utilization is 0.516.Members of high outpatient service utilization family (HOUF) used (17.7) more outpatient service than other families (10.4,4.2).HOUF were mainly distributed in towns with high capability of township hospital and low capability of township hospital.Conclusion Great family clustering of outpatient service utilization exists in rural areas.Family homogenization is distinct,in which irrationality exists.The capability of primary medical institutions influences the outpatient service utilization of residents in rural area.
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Objective To learn the status and equity of human resource allocation for health so as to provide evidence for health administrative department. Methods Descriptive analysis and annual percent changes (APC) were used to analyze the numbers and trends of human resource allocation for health from 2011 to 2015, and Gini coefficients were used for equity evaluation. Results In 2015, Hangzhou had the largest number (12.62) of medical personnel per 1000 persons while Jiaxing had the least amount (7.43) . Hangzhou had the largest number (10.32) of medical technical personnel per 1000 persons while Wenzhou had the least amount (6.23) . Hangzhou had the largest number (3.86) of licensed (assistant) doctors per 1000 persons while Jiaxing had the least amount (2.15) . Hangzhou had the largest number (4.23) of registered nurses per 1000 persons while Wenzhou had the least amount (2.42) . Jiaxing had 8.06 medical personnel, 7.03 medical technical personnel, 2.33 licensed (assistant) doctors and 2.86 registered nurses per square kilometer which were all the largest number while Lishui had 1.21 medical personnel, 1.00 medical technical personnel, 0.39 licensed (assistant) doctors and 0.38 registered nurses per square kilometer which were all the least. The doctor-to-nurse ratio was only 1:1.01 in 2015. Both numbers of human resources for health per 1000 persons and per square kilometer increased year by year from 2011 to 2015, and Gini coefficients of each index expressed by per 1000 persons were all under 0.2, while it ranged from 0.2 to 0.3 when they were expressed by per square kilometer. Conclusion Numbers of human resource allocation for health had an increasing trend and the allocation was fair, but the equity evaluated by service population was better than by service areas, and the research about accessibility of regional human resource allocation for health needs to be concerned.
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Objective: To analyze the trends of development and equity of health institutions in China during the period from 2002 to 2013 , and put forward references to optimize the decision-making on health resources alloca-tion. Methods:Statistical map, Gini coefficient and other methods were used to analyze the distribution and equity of health institutions in China for 12 years, during the period from 2002 to 2013. Results:(1) The overall development of health institutions is on the rise in China, and the distribution density of health resources with the population ad-justment is opposite to the adjustment of both population and geographic area at the same time. (2) In the past 12 years, the number of tertiary hospitals showed an increasing trend, and growth in the eastern region was the most sig-nificant. (3) From 2002 to 2013, the Gini coefficient of the number of health institutions and beds per 1,000 per-sons per square kilometer was maintained at 0. 40, and decreased from 0. 70 to 0. 60 in the eastern region of China, respectively. This same number was maintained at 0. 40 and 0. 20 in the central and western region. Conclusion: In China, the fairness trend of health resources allocation has improved during the period from 2002 to 2013, but the imbalance is more serious in the eastern region than in the central and western regions. It should be paid more atten-tion to optimizing the health resources allocation according to the local conditions of different regions, especially the influence of geographical distribution.
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Objective:To evaluate the equity of the secondary performance allocation in target hospital.Methods:Through the comparison on the Gini coefficient calculation,the calculation method of Gini coefficient developed by Jianhua Zhang was applied to estimate the secondary allocation result of performance salary in the target hospital from 2014 to 2015.Results:From 2014 to 2015,the Gini coefficient remained at 0.22 or so,the overall allocation was average.Conclusion:Estimating the Gini coefficient was beneficial for the hospital managers control the structure and level of the second performance distribution and modulate the program of the sencond performance distribution in time,so that the distribution of performance salary would be accordant to the designed program and acts as the direction of motivation.
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Objective To explore regional variations of basic public health services implementation in Zhejiang Province at prefectural,county and township level,respectively.To find key problems which obstacle the equalization of basic public health services in Zhejiang Province.Methods Descriptive analysis was made on surveillance data of basic public health services in Zhejiang Province,2014.Gini coefficient of key indicators was calculated at prefectural,county and township level,respectively.To the key indicator with higher Gini coefficient,Lorenz curve was plotted and Gini coefficient of each prefectural-level city was calculated.Results An increasing tendency from prefectural to township level was showed in Gini coefficient of all twenty-five analyzed indicators.The Gini coefficient at township level was 0.497 for the average financial fund per migrant person,and the highest prefectural -level cities were Taizhou (0.709 ),Lishui (0.838 ), Quzhou(0.918).The Gini coefficient at township level of other indicators were 0.314 and 0.235 for the children and elderly health management of traditional Chinese medicine,and lower than 0.05 for maternal &children health care, immunization,and coverage rate of electronic health record,and between 0.066 to 0.179 for health management of chronic disease and severe mental illness patients.Conclusion Average financial fund per migrant person and health management of traditional Chinese medicine are current major problems which obstacle the equalization of basic public health services in Zhejiang Province.