Detecting the priority areas for health workforce allocation with LISA functions: an empirical analysis for China

Process quality, diagnosis quality, and patient satisfaction of primary care in Rural Western China: A study using standardized patients

OBJECTIVES

Patient satisfaction is an essential indicator of the doctor-patient relationship. This study aimed to investigate the relationship between primary care quality and patient satisfaction for non-communicable diseases (NCDs) in rural western China.

METHODS

The study utilized the standardized patients (SPs) approach to present typical symptoms of unstable angina and diabetes to rural healthcare providers. After the consultations, the SPs completed a satisfaction survey. Ordinary least squares and quantile regression were used to examine the association between quality of primary care and patient satisfaction.

RESULTS

We examined 178 anonymous SPs visits. The results showed that higher process quality for angina SPs was correlated with stronger satisfaction for provider ability at a low quantile of ability satisfaction. For diabetes SPs, higher process quality increased overall satisfaction at a low quantile of overall satisfaction, whereas a correct diagnosis significantly contributed to communication satisfaction at a high quantile of communication satisfaction.

CONCLUSIONS

The study found positive associations between process and diagnosis quality and SPs satisfaction. Notably, the influence of process quality was most significant among patients with lower satisfaction levels.

PRACTICE IMPLICATIONS

Provider's process quality could be a key area of improving the satisfaction levels, especially for patients with lower levels of satisfaction.

Spatial distribution and influencing factors of CDC health resources in China: a study based on panel data from 2016-2021

Background

Measuring the development of Chinese centers for disease control and prevention only by analyzing human resources for health seems incomplete. Moreover, previous studies have focused more on the quantitative changes in healthcare resources and ignored its determinants. Therefore, this study aimed to analyze the allocation of healthcare resources in Chinese centers for disease control and prevention from the perspective of population and spatial distribution, and to further explore the characteristics and influencing factors of the spatial distribution of healthcare resources.

Methods

Disease control personnel density, disease control and prevention centers density, and health expenditures density were used to represent human, physical, and financial resources for health, respectively. First, health resources were analyzed descriptively. Then, spatial autocorrelation was used to analyze the spatial distribution characteristics of healthcare resources. Finally, we used spatial econometric modeling to explore the influencing factors of healthcare resources.

Results

The global Moran index for disease control and prevention centers density decreased from 1.3164 to 0.2662 (p < 0.01), while the global Moran index for disease control personnel density increased from 0.4782 to 0.5067 (p < 0.01), while the global Moran index for health expenditures density was statistically significant only in 2016 (p < 0.1). All three types of healthcare resources showed spatial aggregation. Population density and urbanization have a negative impact on the disease control and prevention centers density. There are direct and indirect effects of disease control personnel density and health expenditures density. Population density and urbanization had significant negative effects on local disease control personnel density. Urbanization has an indirect effect on health expenditures density.

Conclusion

There were obvious differences in the spatial distribution of healthcare resources in Chinese centers for disease control and prevention. Social, economic and policy factors can affect healthcare resources. The government should consider the rational allocation of healthcare resources at the macro level.

Spatial Accessibility Evaluation and Location Optimization of Primary Healthcare in China: A Case Study of Shenzhen

The unbalanced allocation of healthcare resources is a major challenge that hinders access to healthcare. Taking Shenzhen as an example, this study aimed to enhance equity in obtaining healthcare services, through measuring and visualizing the spatial accessibility of community healthcare centers (CHC), and optimizing CHC geospatial allocation. We used the number of health technicians per 10,000 to represent the CHC's service capacity, combined with resident points and census data to calculate the population the CHC needs to carry, and then analyzed the accessibility based on the Gaussian two-step floating catchment area method. In 2020, five regions in Shenzhen had better spatial accessibility scores: Nanshan (0.250), Luohu (0.246), Futian (0.244), Dapeng (0.226), and Yantian (0.196). The spatial accessibility of CHCs shows a gradual decrease from the city center to the edge, which is affected by economic and topographic factors. With the support of the maximal covering location problem model, we selected up to 567 candidate locations for the new CHC, which could improve Shenzhen's accessibility score from 0.189 to 0.361 and increase the coverage population by 63.46% within a 15-min impedance. By introducing spatial techniques and maps, this study provides (a) new evidence for promoting equitable access to primary healthcare services in Shenzhen and (b) a foundation for improving the accessibility of public service facilities in other areas.

Measuring the inequalities in healthcare resource in facility and workforce: A longitudinal study in China

Objective

The study aimed to measure time trends of inequalities of the geographical distribution of health facilities and workforce in Shanghai from 2010 to 2016 and used a spatial autocorrelation analysis method to precisely detect the priority areas for optimizing health resource reallocation in metropolises like Shanghai in developing countries.

Methods

The study used secondary data from the Shanghai Health Statistical Yearbook and the Shanghai Statistical Yearbook from 2011 to 2017. Five indicators on health resources, namely, health institutions, beds, technicians, doctors, and nurses, were employed to quantitatively measure the healthcare resource in Shanghai. The Theil index and the Gini coefficient were applied to assess the global inequalities in the geographic distribution of these resources in Shanghai. Global and local spatial autocorrelation was performed using global Moran's index and local Moran's index to illustrate the spatial changing patterns and identify the priority areas for two types of healthcare resource allocation.

Results

Shanghai's healthcare resources showed decreasing trends of inequalities at large from 2010 to 2016. However, there still existed an unchanged over-concentration distribution in healthcare facilities and workforce density among districts in Shanghai, especially for doctors at the municipal level and facility allocation at the rural level. Through spatial autocorrelation analysis, it was found that there exhibited a significant spatial autocorrelation in the density distribution of all resources, and some identified priority areas were detected for resource re-allocation policy planning.

Conclusion

The study identified the existence of inequality in some healthcare resource allocations in Shanghai from 2010 to 2016. Hence, more detailed area-specific healthcare resource planning and distribution policies are required to balance the health workforce distribution at the municipal level and institution distribution at the rural level, and particular geographical areas (low–low and low–high cluster areas) should be focused on and fully considered across all the policies and regional cooperation to ensure health equality for municipal cities like Shanghai in developing countries.

Finding flaws in the spatial distribution of health workforce and its influential factors: An empirical analysis based on Chinese provincial panel data, 2010-2019

Background

The maldistributions of the health workforce showed great inconsistency when singly measured by population quantity or geographic area in China. Meanwhile, earlier studies mainly employed traditional econometric approaches to investigate determinants for the health workforce, which ignored spillover effects of influential factors on neighboring regions. Therefore, we aimed to analyze health workforce allocation in China from demographic and geographic perspectives simultaneously and then explore the spatial pattern and determinants for health workforce allocation taking account of the spillover effect.

Methods

The health resource density index (HRDI) equals the geometric mean of health resources per 1,000 persons and per square kilometer. First, the HRDI of licensed physicians (HRDI_P) and registered nurses (HRDI_N) was calculated for descriptive analysis. Then, global and local Moran's I indices were employed to explore the spatial features and aggregation clusters of the health workforce. Finally, four types of independent variables were selected: supportive resources (bed density and government health expenditure), healthcare need (proportion of the elderly population), socioeconomic factors (urbanization rate and GDP per capita), and sociocultural factors (education expenditure per pupil and park green area per capita), and then the spatial panel econometric model was used to assess direct associations and intra-region spillover effects between independent variables and HRDI_P and HRDI_N.

Results

Global Moran's I index of HRDI_P and HRDI_N increased from 0.2136 (P = 0.0070) to 0.2316 (P = 0.0050), and from 0.1645 (P = 0.0120) to 0.2022 (P = 0.0080), respectively. Local Moran's I suggested spatial aggregation clusters of HRDI_P and HRDI_N. For HRDI_P, bed density, government health expenditure, and GDP had significantly positive associations with local HRDI_P, while the proportion of the elderly population and education expenditure showed opposite spillover effects. More precisely, a 1% increase in the proportion of the elderly population would lead to a 0.4098% increase in HRDI_P of neighboring provinces, while a 1% increase in education expenditure leads to a 0.2688% decline in neighboring HRDI_P. For HRDI_N, the urbanization rate, bed density, and government health expenditure exerted significantly positive impacted local HRDI_N. In addition, the spillover effect was more evident in the urbanization rate, with a 1% increase in the urbanization rate relating to 0.9080% growth of HRDI_N of surrounding provinces. Negative spillover effects of education expenditure, government health expenditure, and elderly proportion were observed in neighboring HRDI_N.

Conclusion

There were substantial spatial disparities in health workforce distribution in China; moreover, the health workforce showed positive spatial agglomeration with a strengthening tendency in the last decade. In addition, supportive resources, healthcare needs, and socioeconomic and sociocultural factors would affect the health labor configuration not only in a given province but also in its nearby provinces.

Precipitation and urban expansion caused jointly the spatiotemporal dislocation between supply and demand of water provision service

A clear quantification and spatial mapping between supply and demand of water provision service in relation to climate change and urban expansion can provide some guidance to water resources management. Nevertheless, so far, most researches ignored the dynamic changes and influences of supply-demand coupling correlations. In this study, water yield and water demand were quantified and mapped in the Xiangjiang River Basin (XRB) from 2000 to 2018 by using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) and water-demand models, then the spatial distribution characteristics and their matching relationship were identified by using the univariate local autocorrelation analysis and the common logarithm of water supply-demand ratio (WSDR). With that, the contributions of climate and socio-economic factors to the above-mentioned changes were explored by using geographic detector. Results showed that the annual water yield increased by 20.20% in 2000-2015 and decreased by 33.92% in 2015-2018 affected by precipitation and land use changes; Changsha-Zhuzhou- Xiangtan urban agglomeration (CZX) and Southwest of Yongzhou were the high value areas of water yield (>338 m³/hm²). Due to the urban expansion, the water demand increased by 40.50% from 2000 to 2005 and decreased by 36.39% after 2005; From 2000 to 2018, high value areas of water demand (>53566 m³/hm²) mainly appeared in midstream and downstream with high urbanization level, dense population and developed industry. Under the joint action of precipitation (prep) and urban expansion, the overall state of supply and demand in the upper reaches was surplus, and more than 90% of the regions in midstream and downstream were at the middle and high level of supply shortage, especially in Hengyang and Chenzhou. Consequently, the increasing needs of human beings should be emphasized from the overall perspective of the basin, the growth rate of construction land and the necessary green infrastructure should be controlled reasonably and configured for achieving win-win goals of coordinating environmental protection and urban development.

Growth and challenges of China's nursing workforce from 1998 to 2018: A retrospective data analysis

BACKGROUND

Nurses play a vitally important role in promoting equitable and essential care. China undertook bold reforms in its education and healthcare systems since 1990s. The effect of these reforms on the nursing workforce has not been assessed systematically.

OBJECTIVE

This study aims to assess the changing trends and the underlying challenges of the nursing workforce in Mainland China in the period of 1998-2018.

DESIGN

Retrospective data analysis.

METHODS

Data were acquired from the National Health Statistics Yearbook from 1999 to 2019. Descriptive statistics were used to analyze the nature of the nursing workforce in terms of quantity, quality, and structure. Non-parametric tests were used to compare doctors and nurses in terms of number and work experiences. Global Moran's I index and hotspot analysis were applied to compare the equity in distribution of nurses at national and provincial levels.

RESULTS

From 1998 to 2018, the number of nurses increased from 1.22 to 4.10 million with an average rate of increase of 6.3% per annum. The ratio of doctors to nurses changed from 1: 0.61 to 1: 1.14, reaching 1: 1 in 2013. The main educational level of registered nurses elevated to associated degree (48.9%), and nurses with advanced titles increased at the most rapid rate. In 2018, 60.3% of nurses were younger than 35 years old. The Global Moran's I index ranged from 0.211 to 0.198 (Z > 1.96, P < 0.05). Hotspot analysis showed the distribution of nurses was unequally concentrated in the northern region and with the highest distribution in Beijing.

CONCLUSIONS

Great improvement on the scale and the quality of nursing workforce over the past 20 years has been witnessed in China. However, the shortage of nurses, outflow of younger nurses and the imbalance distribution of nursing workforce among the country are emerging challenges. Plans should not be ignored on continuously cultivating more qualified nurses, retaining younger nurses, attracting nurses to work in rural areas and the northeast region. Tweetable abstract: Numbers of Chinese nurses finally outstrip the number of doctors but do limited educational opportunities limits their contribution to the nation's health? New article in @ijnsjournal.

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

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13690-021-00597-1.

Visualizing the drivers of an effective health workforce: a detailed, interactive logic model

BACKGROUND

A strong health workforce is a key building block of a well-functioning health system. To achieve health systems goals, policymakers need information on what works to improve and sustain health workforce performance. Most frameworks on health workforce planning and policymaking are high-level and conceptual, and do not provide a structure for synthesizing the growing body of empirical literature on the effectiveness of strategies to strengthen human resources for health (HRH). Our aim is to create a detailed, interactive logic model to map HRH evidence and inform policy development and decision-making.

METHODS

We reviewed existing conceptual frameworks and models on health workforce planning and policymaking. We included frameworks that were: (1) visual, (2) comprehensive (not concentrated on specific outcomes or strategies), and (3) designed to support decision-making. We compared and synthesized the frameworks to develop a detailed logic model and interactive evidence visualization tool.

RESULTS

Ten frameworks met our inclusion criteria. The resulting logic model, available at hrhvisualizer.org , allows for visualization of high-level linkages as well as a detailed understanding of the factors that affect health workforce outcomes. HRH data and governance systems interact with the context to affect how human resource policies are formulated and implemented. These policies affect HRH processes and strategies that influence health workforce outcomes and contribute to the overarching health systems goals of clinical quality, responsiveness, efficiency, and coverage. Unlike existing conceptual frameworks, this logic model has been operationalized in a highly visual, interactive platform that can be used to map the research informing policies and illuminating their underlying mechanisms.

CONCLUSIONS

The interactive logic model presented in this paper will allow for comprehensive mapping of literature around effective strategies to strengthen HRH. It can aid researchers in communicating with policymakers about the evidence behind policy questions, thus supporting the translation of evidence to policy.

Current situation and distribution equality of public health resource in China

Background

The public health system has been developed in China for several years while no research explores its distribution. This research aims to describe the variation and equality of public health allocation from 2013 to 2018 and explore the source of inequality.

Methods

Data in this research was obtained from the China Health Statistics Yearbook 2014 to 2019 and the China Statistical Yearbook 2019. Four indicators were chosen in describing the development and current situation of the public health system. Three of them were used to evaluate allocation equality. 31 provinces were categorized into western, middle, and eastern groups based on geographical and economic conditions. Total allocation equality, inter- and intra-difference were all measured by the Theil index.

Results

All indicators showed a stably upwards trend except for the number of public health institutions. The allocation gap of the public health institution per km² was larger than that per 10,000 capita. Theil index of three indicators continually rose from 2013 to 2018 and the inequality of public health institutions allocation was the highest one. The western region had the highest Theil index in technical personnel and beds allocation. Among the three regions, the western region contributed most to inequality.

Conclusions

The public health workforces and institutions are still under the requirement of the National Medical and Health Service System Plan. From 2013 to 2018, the equality of public health resources stably decreases, which is mainly contributed by the internal difference within the western region. Further research should be done to explore the possible cause of the results. Problems founded in this research should be solved by multisectoral cooperation.

Factors associated with the utilization of community-based diabetes management care: A cross-sectional study in Shandong Province, China

Background

Community-based diabetes management is known to be an important strategy for global diabetes control. In China, community-based diabetes management care, including regular blood glucose tests and guidance on medicine use, dietary control, and physical exercise provided by primary health institutions (PHIs), as one of the key contents of the national essential public health services (EPHS), was implemented since 2009 when the new round of health system reform was initiated. This study aimed to investigate the utilization of community-based diabetes management care services, and explore the factors influencing utilization from both patients’ and providers’ points of view.

Methods

In total, 2520 type-2 diabetes mellitus (DM) patients registered for EPHS were selected from 63 PHIs in eight counties of Shandong province, China, using multi-stage stratified sampling. Of those, 2166 patients (response rate: 85.4%) completed face-to-face structured questionnaires on their utilization of community-based diabetes management care services. Further, 63 PHIs were surveyed on diabetes care delivery, and 444 primary healthcare providers were purposively sampled from those PHIs to measure their knowledge of diabetes management care delivery, using a self-developed questionnaire. Descriptive statistics were used to analyze the delivery and utilization of diabetes management care services. Multilevel logistic regression models were used to analyze the factors associated with patients’ utilization of diabetes management services.

Results

All 63 PHIs reported that all the required four diabetes management services were provided through EPHS. However, only 49.6% of the patients reported they fully used these services, with no statistically significant difference between urban and rural patients. Patients who had higher knowledge of diabetes and better self-efficacy in controlling the condition, were more likely to fully utilize diabetes management care. A larger number of PHI health staff per 1000 population was associated with better utilization of care.

Conclusion

Although community-based diabetes management services are well available to Chinese DM patients under the framework of EPHS, the actual utilization of diabetes management services among the patients was poor. The size of the PHI workforce, patients’ knowledge and self-efficacy in controlling diabetes, were important predictors of utilization, and could be enhanced to improve control of diabetes.

Addressing the Licensed Doctor Maldistribution in China: A Demand-And-Supply Perspective

Background: The maldistribution of licensed doctors is one of the major challenges faced by the Chinese health sector. However, this subject remains underexplored, as the underlying causes of licensed doctor distribution have not been fully mapped out. To fill the research void, this study theoretically modeled and empirically measured various determinants of licensed doctor distribution from both the supply and demand sides while taking the spillover effect between the adjacent geographical units into consideration. Methods: The theory of demand and supply is adopted to construct a research framework so as to explain the imbalance in the licensed doctor distribution. Both direct effects and spillover effects of the supply-side factors and demand-side factors are empirically measured with the spatial panel econometric models. Results: The health service demand was found, as expected, to be the major driving force of the licensed doctor distribution across the nation. That is, the increase in health services demands in a province could significantly help one unit attract licensed doctors from adjacent units. Unexpectedly but intriguingly, the medical education capacity showed a relatively limited effect on increasing the licensed doctor density in local units compared with its spillover effect on neighboring units. In addition, government and social health expenditures played different roles in the health labor market, the former being more effective in increasing the stock of clinicians and public health doctors, the latter doing better in attracting dentists and general practitioners. Conclusions: The results provide directions for Chinese policy makers to formulate more effective policies, including a series of measures to boost the licensed doctor stock in disadvantaged areas, such as the increase of government or social health expenditures, more quotas for medical universities, and the prevention of a brain drain of licensed doctors.