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

ABSTRACT: BACKGROUND:Health workforce misdistribution leads to severe inequity and low-efficiency in health services in the developing countries. Targeting at China, this research aims to reveal, visualize and compare the geographical distribution patterns of different subtypes of urban and rural health workforce and identify the priority regions for health workforce planning and allocation policies designing. METHODS:The health workforce density (workforce-to-population ratio) is adopted to represent the accessibility to health workforce in each geographical unit. Besides a descriptive geography of health workforce as a whole, the local indicators of spatial association (LISA) are used to explore the spatial clusters of different subtypes of health workforce, which are visualized by geographical tools. RESULTS:Results reveal that regional disparities and spatial clusters exist in China's health workforce distribution, with different types of workforce exhibiting relatively different spatial distribution characteristics. Besides, huge urban-rural disparities are found in the distribution of health workforce in China. Unexpectedly but intriguingly, most of the high-high and high-low cluster area of urban health workforce are concentrated in the western China (Xinjiang, Xizang etc.), indicating the relative abundant stock of urban health workforce in these units, while the low-low and low-high cluster area of different types of urban health workforce are mainly distributed in middle China. Regarding the rural health workforce, there is an obvious and similar low-low and low-high clustering pattern in western provinces (Sichuan, Yunnan) for the licensed doctors, pharmacists, technologists, which play a critical role in health services delivery. CONCLUSIONS:Different types of health workforce displayed distinct spatial distribution patterns, while the misdistribution of rural health workforce imposed more challenges to the Chinese health sector due to its poorer stock and more disadvantaged positions of backward regions (i.e., low-low and low-high cluster area). Subtype-specific and region-oriented health workforce planning and allocation policies are suggested to be made, aiming at the urban and rural health workforce respectively, by prioritizing the identified low-low and low-high cluster areas.

SUBMITTER: Zhu B

PROVIDER: S-EPMC6292090 | biostudies-other | 2018 Dec

REPOSITORIES: biostudies-other

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

Zhu Bin B Fu Yang Y Liu Jinlin J He Rongxin R Zhang Ning N Mao Ying Y

BMC health services research 20181212 1

<h4>Background</h4>Health workforce misdistribution leads to severe inequity and low-efficiency in health services in the developing countries. Targeting at China, this research aims to reveal, visualize and compare the geographical distribution patterns of different subtypes of urban and rural health workforce and identify the priority regions for health workforce planning and allocation policies designing.<h4>Methods</h4>The health workforce density (workforce-to-population ratio) is adopted t ...[more]

PMID: 30541543

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Project description:BackgroundIn Vietnam, a lower-middle income country, while the overall skill- and knowledge-based quality of health workforce is improving, health workers are disproportionately distributed across different economic regions. A similar trend appears to be in relation to health outcomes between those regions. It is unclear, however, whether there is any relationship between the distribution of health workers and the achievement of health outcomes in the context of Vietnam. This study examines the statistical relationship between the availability of health workers and health outcomes across the different economic regions in Vietnam.MethodsWe constructed a panel data of six economic regions covering 8 years (2006-2013) and used principal components analysis regressions to estimate the impact of health workforce on health outcomes. The dependent variables representing the outcomes included life expectancy at birth, infant mortality, and under-five mortality rates. Besides the health workforce as our target explanatory variable, we also controlled for key demographic factors including regional income per capita, poverty rate, illiteracy rate, and population density.ResultsThe numbers of doctors, nurses, midwives, and pharmacists have been rising in the country over the last decade. However, there are notable differences across the different categories. For example, while the numbers of nurses increased considerably between 2006 and 2013, the number of pharmacists slightly decreased between 2011 and 2013. We found statistically significant evidence of the impact of density of doctors, nurses, midwives, and pharmacists on improvement to life expectancy and reduction of infant and under-five mortality rates.ConclusionsAvailability of different categories of health workforce can positively contribute to improvements in health outcomes and ultimately extend the life expectancy of populations. Therefore, increasing investment into more equitable distribution of four main categories of health workforce (doctors, nurses, midwives, and pharmacists) can be an important strategy for improving health outcomes in Vietnam and other similar contexts. Future interventions will also need to consider an integrated approach, building on the link between the health and the development.

Project description:BackgroundAttracting and retaining sufficient health workers to provide adequate services for residents of rural and remote areas has global significance. High income countries (HICs) face challenges in staffing rural areas, which are often perceived by health workers as less attractive workplaces. The objective of this review was to examine the quantifiable associations between interventions to retain health workers in rural and remote areas of HICs, and workforce retention.MethodsThe review considers studies of rural or remote health workers in HICs where participants have experienced interventions, support measures or incentive programs intended to increase retention. Experimental, quasi-experimental and observational study designs including cohort, case-control, cross-sectional and case series studies published since 2010 were eligible for inclusion. The Joanna Briggs Institute methodology for reviews of risk and aetiology was used. Databases searched included MEDLINE (OVID), CINAHL (EBSCO), Embase, Web of Science and Informit.ResultsOf 2649 identified articles, 34 were included, with a total of 58,188 participants. All study designs were observational, limiting certainty of findings. Evidence relating to the retention of non-medical health professionals was scant. There is growing evidence that preferential selection of students who grew up in a rural area is associated with increased rural retention. Undertaking substantial lengths of rural training during basic university training or during post-graduate training were each associated with higher rural retention, as was supporting existing rural health professionals to extend their skills or upgrade their qualifications. Regulatory interventions requiring return-of-service (ROS) in a rural area in exchange for visa waivers, access to professional licenses or provider numbers were associated with comparatively low rural retention, especially once the ROS period was complete. Rural retention was higher if ROS was in exchange for loan repayments.ConclusionEducational interventions such as preferential selection of rural students and distributed training in rural areas are associated with increased rural retention of health professionals. Strongly coercive interventions are associated with comparatively lower rural retention than interventions that involve less coercion. Policy makers seeking rural retention in the medium and longer term would be prudent to strengthen rural training pathways and limit the use of strongly coercive interventions.

Project description:BACKGROUND:Equity is one of the major goals of China's new medical reforms launched in 2009. This study aimed to analyze the disequilibrium in primary health care (PHC) workforce among various economic zones in China and to compare the fairness between urban and rural areas since the implementation of the new medical reforms. METHOD:According to China's 11th Five-Year Plan, China is divided into eight economic regions. The data of this study were obtained from China Statistical Yearbook 2009-2016. The Atkinson index was used to depict the trend of PHC workforce fairness; the Gini coefficient was used to compare the fairness of workforce distribution between urban and rural areas; the health resource agglomeration degree was used to analyze the distributional equity of the workforce in the eight regions; and the Theil Index was used to compare the fairness of urban and rural workforce distribution across eight regions. RESULT:The Atkinson index indicated that the equity of the entire PHC workforce allocation had generally improved during the new medical reforms; the Gini coefficient indicated that the fairness of the entire workforce allocation had improved in cities, but only the nurse allocation became fairer in rural areas. The agglomeration degree and the Theil index indicated that the fairness gaps across the eight regions were still large. These analyses differed from previous studies where China was divided into western, central and eastern regions. In what was previously defined as eastern region, the northeast was under-resourced, while the eastern coastal areas were observing a resource surplus. In western region, we found that the fairness in the northwest was significantly worse than southwest. CONCLUSION:In China, the distribution of healthcare workforce has been improved with continuous effort. The gaps in the distribution of PHC workforce across different economic regions and between urban and rural areas are still large, with different regions facing different problems. The government should consider the population and geographical factors in allocation of PHC workforce, especially nurses.

Dataset Information

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

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

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