scholarly journals Equity and efficiency of health care resource allocation in Jiangsu Province, China

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Qian Li ◽  
Jianjun Wei ◽  
Fengchang Jiang ◽  
Guixiang Zhou ◽  
Rilei Jiang ◽  
...  
Keyword(s):  
Health Care ◽  
Resource Allocation ◽  
Geographical Area ◽  
Health Care Resource ◽  
Jiangsu Province ◽  
Financial Resources ◽  
Health Resource ◽  
Statistical Yearbook ◽  
Efficiency And Productivity ◽  
Better Than

Abstract Background Jiangsu was one of the first four pilot provinces to engage in comprehensive health care reform in China, which has been on-going for the past 5 years. This study aims to evaluate the equity, efficiency and productivity of health care resource allocation in Jiangsu Province using the most recent data, analyse the causes of deficiencies, and discuss measures to solve these problems. Methods Data were extracted from the Jiangsu Health/Family Planning Statistical Yearbook (2015–2019) and Jiangsu Statistical Yearbook (2015–2019). The Gini coefficient (G), Theil index (T) and health resource density index (HRDI) were chosen to study the fairness of health resource allocation in Jiangsu Province. Data envelopment analysis (DEA) and the Malmquist productivity index (MPI) were used to analyse the efficiency and productivity of this allocation. Results From 2014 to 2018, the total amount of health resources in Jiangsu Province increased. The G of primary resource allocation by population remained below 0.15, and that by geographical area was between 0.14 and 0.28; additionally, the G of health financial resources was below 0.26, and that by geographical area was above 0.39. T was consistent with the results for G and Lorenz curves. The HRDI shows that the allocated amounts of health care resources were the highest in southern Jiangsu, except for the number of health institutions. The average value of TE was above 0.93, and the DEA results were invalid for only two cities. From 2014 to 2018, the mean TFPC in Jiangsu was less than 1, and the values exceeded 1 for only five cities. Conclusion The equity of basic medical resources was better than that of financial resources, and the equity of geographical allocation was better than that of population allocation. The overall efficiency of health care resource allocation was high; however, the total factor productivity of the whole province has declined due to technological regression. Jiangsu Province needs to further optimize the allocation and increase the utilization efficiency of health care resources.

scholarly journals Equity and efficiency of health resource allocation of Chinese Medicine in mainland China: 2013 to 2017

2020 ◽  
Author(s):  
Zhengjun Li ◽  
Lili Yang ◽  
Yaoyao Bian
Keyword(s):  
Resource Allocation ◽  
Chinese Medicine ◽  
Mainland China ◽  
Health Resource ◽  
Middle Region ◽  
Health Resource Allocation ◽  
Equity And Efficiency ◽  
Statistical Yearbook ◽  
Efficiency And Productivity ◽  
Better Than

Abstract Background: In this study, we aimed to measure the equity, efficiency and productivity of traditional Chinese medicine (TCM) health resource allocation and utilization in mainland China trend from 2013 to 2017. Methods: The data were download from the China Health Statistical Yearbook (2018) and the China Statistical Yearbook (2018). The equity and efficiency of TCM health resource allocation was evaluated by Lorenz curve, Gini coefficient (G) and Theil index (T) were applied to evaluate. The efficiency and productivity of TCM health resource utilization were assessed by Data Envelopment Analysis (DEA)-based Malmquist productivity index (MPI). Results: The TCM health resource had an increasing trend every year. The equity allocated by population (Gs range from 0.1 to 0.3) was better than that by geographic region (Gs more than 0.5). Ts in the intra-groups were higher than that in the inter-groups. Most provinces (29 out of 31) had negative productivity changes, which suggested a deterioration in productivity. However, the middle region with higher scale sizes had more redundant inputs. Moreover, the low technological development (all technical values lower than 1.00) might obstacle the productive progress. Conclusion: The equity of TCM health allocated by population was better than that by the geography region. The intra-regional difference was the main reasons of the sources of inequity. The equity of TCM resource allocation was middle region ＞ eastern region ＞ western region. The productivity in more than 97% provinces are inefficient. The frequency distribution of Sech ( score ＞ 1) increased since 2015. However, the frequency distribution of Techch (score ＞ 1) decreased year by year. The slow technological progress and low scale size might the major reason for the low productivity. Keywords: TCM health resource, Equity, Efficiency, Productivity

scholarly journals Equity and efficiency of health resource allocation of Chinese Medicine in mainland China: 2013 to 2017

2020 ◽  
Author(s):  
Zhengjun Li ◽  
Lili Yang ◽  
Yaoyao Bian
Keyword(s):  
Resource Allocation ◽  
Chinese Medicine ◽  
Mainland China ◽  
Health Resource ◽  
Middle Region ◽  
Health Resource Allocation ◽  
Equity And Efficiency ◽  
Statistical Yearbook ◽  
Efficiency And Productivity ◽  
Better Than

Abstract Background: In this study, we aimed to measure the equity, efficiency and productivity of traditional Chinese medicine (TCM) health resource allocation and utilization in mainland China trend from 2013 to 2017. Methods: The data were download from the China Health Statistical Yearbook (2018) and the China Statistical Yearbook (2018). The equity and efficiency of TCM health resource allocation was evaluated by Lorenz curve, Gini coefficient (G) and Theil index (T) were applied to evaluate. The efficiency and productivity of TCM health resource utilization were assessed by Data Envelopment Analysis (DEA)-based Malmquist productivity index (MPI). Results: The TCM health resource had an increasing trend every year. The equity allocated by population (Gs range from 0.1 to 0.3) was better than that by geographic region (Gs more than 0.5). Ts in the intra-groups were higher than that in the inter-groups. Most provinces (29 out of 31) had negative productivity changes, which suggested a deterioration in productivity. However, the middle region with higher scale sizes had more redundant inputs. Moreover, the low technological development (all technical values lower than 1.00) might obstacle the productive progress. Conclusion: The equity of TCM health allocated by population was better than that by the geography region. The intra-regional difference was the main reasons of the sources of inequity. The equity of TCM resource allocation was middle region ＞ eastern region ＞ western region. The productivity in more than 97% provinces are inefficient. The frequency distribution of Sech ( score ＞ 1) increased since 2015. However, the frequency distribution of Techch (score ＞ 1) decreased year by year. The slow technological progress and low scale size might the major reason for the low productivity. Keywords: TCM health resource, Equity, Efficiency, Productivity

scholarly journals Differences in regional distribution and inequality in health-resource allocation on institutions, beds, and workforce: a longitudinal study in China

2021 ◽  
Vol 79 (1) ◽  
Author(s):  
Enhong Dong ◽  
Jie Xu ◽  
Xiaoting Sun ◽  
Ting Xu ◽  
Lufa Zhang ◽  
...  
Keyword(s):  
Health Care ◽  
Resource Allocation ◽  
Time Trends ◽  
Regional Distribution ◽  
Health Care Resource ◽  
Theil Index ◽  
Health Resource ◽  
Health Care Resources ◽  
Health Resource Allocation ◽  
Inequality In Health

Abstract Background The distribution of health-care resources is foundational to achieving fairness and having access to health service. China and its local Shanghai’s government have implemented measures to allocate health-care resources with the equity as one of the major goals since 2009-health-care reform. The aim of this study was to analyze differences in regional distribution and inequality in health-resource allocation on institutions, beds, and workforce in Shanghai over 7 years. Methods The study was conducted using 2010–2016 data to analyze health-resource allocation on institutions, beds, and workforce in Shanghai, China. The annual growth rate (AGR) was used to evaluate the time trends of health-care resource from 2010 to 2016, and Theil index was calculated to measure inequality of five indicators of health-care resource allocation during this study period. Results All quantities of health-care resources per 1000 people increased across Shanghai districts from 2010 to 2016. Compared with suburban districts, the central districts had higher ratios on five health-care resource indicators, and faster average growth in the bed and nurse indicator. The Theil of the indicators, except for doctors in hospitals, all exhibited downward time trends. Conclusions Regional difference between urban and rural areas and inequality between institution and workforce, especially for doctors, still existed. Some targeted measures including but not limited to income raising, facilitation of transportation conditions, investment of more fiscal funds, enhancement of health-care service provision for rural residents should be fully considered to narrow resource distribution gap between urban and rural districts and mitigate the inequality of health-care resource allocation.

scholarly journals Equity and Efficiency of Health Resource Allocation of Chinese Medicine in Mainland China: 2013–2017

2020 ◽  
Vol 8 ◽  
Author(s):  
Zhengjun Li ◽  
Lili Yang ◽  
Shaoliang Tang ◽  
Yaoyao Bian
Keyword(s):  
Resource Allocation ◽  
Chinese Medicine ◽  
Mainland China ◽  
Geographic Region ◽  
Health Resource ◽  
Middle Region ◽  
Health Resource Allocation ◽  
Equity And Efficiency ◽  
Statistical Yearbook ◽  
Better Than

Background: In this study, we aimed to estimate the equity and efficiency of traditional Chinese medicine (TCM) health resource allocation, utilization, and trend in mainland China from 2013 to 2017.Methods: The data were downloaded from the China Health Statistical Yearbook (2014–2018) and the China Statistical Yearbook (2018). The equity of TCM health resource allocation was evaluated through the Lorenz curve, Gini coefficient (G), and Theil index (T) based on population size and geographical area. The efficiency and productivity of TCM health resource utilization were assessed using the data envelopment analysis-based Malmquist productivity index.Results: TCM health resource had an increasing trend every year. The equity allocated by population (G ranging from 0.1 to 0.3) was better than that by geographic region (G > 0.5). T in the intra-groups was higher than those in the inter-groups. The equity of TCM resource allocation was the middle region > eastern region > western region. Most provinces (29 out of 31) had negative productivity changes, suggesting deterioration in productivity. Moreover, the middle region with higher scale sizes had more redundant inputs than the other two regions. However, the low technological development (all technical values <1) might hinder productive progress.Conclusion: The equity of TCM health allocated by the population was better than that by the geographic region. The intra-regional difference was the main reason for inequity sources. Productivities in more than 97% of provinces are inefficient. The frequency distribution of scale efficiency (score > 1) had increased since 2015. However, the frequency distribution of technical change (score > 1) decreased every year. The slow technological progress and low scale size might be the main reasons for low productivity.

Social values and cancer funding priorities: Empirical evidence for cancer policy.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e18352-e18352
Author(s):  
Avram Denburg
Keyword(s):  
Health Care ◽  
Resource Allocation ◽  
Moral Reasoning ◽  
Cancer Care ◽  
Stated Preference ◽  
Population Based ◽  
Health Care Resource ◽  
Ethical Principles ◽  
Public Values ◽  
Stated Preference Survey

e18352 Background: Achieving value in health care requires knowledge of public values and priorities. To better understand public values for resource allocation on cancer care, we conducted a population-based stated preference survey with a nested randomized controlled moral reasoning intervention. Our objective was to generate evidence to inform economic evaluation and policymaking on cancer care priority-setting and payment reform in developed health systems. Methods: We conducted a population-based stated preference survey of societal views on the prioritization of health resources between children and adults, administered to a nationally representative sample (n = 1,556) of Canadian adults. Allocative preferences were elicited across a range of hypothetical treatment scenarios and scored on a visual analogue scale. Participants were randomized to a moral reasoning intervention (n = 773) or a control group (n = 783). Those randomized to the intervention group were exposed to a moral reasoning exercise prior to each choice task. The exercise presented participants with a list of ethical principles relevant to health care resource allocation and tasked them to select the top principles guiding their choice. The main outcomes were the difference in mean preference scores by group, scenario, and participant demographics. Results: Multiple regression analyses demonstrated a consistent aggregate preference by participants to allocate scarce health system resources to children. Exposure to the moral reasoning exercise weakened but did not eliminate allocative preference for children, as compared to control (difference 0.72, SE 0.14, p < 0.0001). Younger respondent age (-0.71, SE 0.14, p < 0.0001) and parenthood (-0.40, SE 0.11, p < 0.0002) were associated with greater preference for children. The top three principles guiding participants’ allocative decisions were treat equally (54.3-63.9%), relieve suffering (39.6-66.1%), and rescue those at risk of dying (37-40.8%). Conclusions: Our results demonstrate a significant preference by participants to allocate health care resources to children, but one attenuated by exposure to a range of ethical principles to guide decision-making. It also evinced strong support for humanitarian principles to guide health care resource allocation. Definitions of value in health care based primarily on the magnitude of clinical benefit and cost-effectiveness may exclude moral considerations that the public values.

Sign in / Sign up

Export Citation Format

Share Document