BackgroundHospital electronic information management systems (HEIMS) are widely used in Ghana, and hence its performance must be carefully assessed. Nurses as clinical health personnel are the largest cluster of hospital staff and are the pillar of healthcare delivery. Therefore, they play a crucial role in the adoption and assessment of HEIMSs in Ghana. This report sought to assess the “Social Influence” (SI) and “Facilitating Conditions” (FC) that support Nurses’ Acceptance of HEIMS in Ghana using the “Unified Theory of Acceptance and Use of Technology” (UTAUT) model.MethodsThis study applied a non-experimental survey design. An electronic platform questionnaire on smartphones was used to collect data on 660 nurses. Statistically, AMOS Structural Equation Modelling (SEM) version 22.0 was employed to examine the research model.Results“Behavioral Intention” (BI) to HEIMS use was significantly predicted by SI and FC (p < 0.001). Notably, both SI and FC had an influence on nurses’ use behavior (UB) with behavioral intention (BI) as the mediator, which explains a total of 42.1% variance in the intention of nurses to use HEIMS. Likewise, UB of HEIMS was also significantly predicted by SI (R2 = 43.2) and BI (R2 = 0.39.6) with both constructs explaining a total of 51.7% of the variance in nurses’ acceptance to use HEIMS.ConclusionNurses’ adoption of HEIMS in terms of the UB was influenced by SI and BI, whiles SI and FC had the strongest influence on BI (serving as mediator) of UB to adopt and use HEIMS among the nurses in Ghanaian hospitals.

BackgroundWhile the demand for the health service keeps escalating at the grass root or rural areas of China, a substantial portion of healthcare resources remains stagnant in the more developed cities and this has entrenched health inequity in many parts of China. At its conception, the Deepening Health Care Reform in 2012 China was intended to flush out these discrepancies and promote a more equitable and efficient distribution of health resources. Nearly half a decade of this reform, there are uncertainties as to whether the attainment of the objectives of the reform is in sight.MethodsWe divided Jiangsu Province into 3 zones according to the level of economic and social development i.e. developed, developing, and undeveloped areas. Using a hybrid of Panel data analysis and an augmented Data Envelopment Analysis (DEA), we model human resources, capital inputs of Community Health Centers to comprehensively determine the technical and scale efficiency of community health resources in 3 zones in Jiangsu Province.ResultsWe sampled data and analysed efficiency and productivity growth of 75 Community Health Centers in 13 cities of Jiangsu Province from 2011 to 2015, which shows that a significant productive growth among Community Health Centers between 2011 and 2015. Mirroring the behavior of Community Health Centers, technological progress was the underlying force for the growth and the deterioration in efficiency change was found. This can be credited partly to the Deepening Health Care Reform measures aimed at improving technology availability in health centers in sub-urban areas. The regional summary of the DEA result shows that the stage of economic development and the efficiency performance of hospital did not necessarily go hand in hand among the 3 zones of Jiangsu.ConclusionsThe government of China in general and Jiangsu province in particular could improve the efficiency of health resources allocation by improving the community health service system, rationalizing the allocation of health personnel, optimizing the allocation of material resources and enhancing the level of health of financial resources allocation.

Background Emerging countries continue to suffer gravely from insufficient healthcare funding, which adversely affects access to quality healthcare and ultimately the health status of citizens. By using panel data from the World Development Indicators, the study examined the determinants of health care expenditure among twenty-two (22) emerging countries from the year 2000 to 2018. Methods The study employed cross-section dependence and homogeneity tests to confirm cross-sectional dependence and to deal with homogeneity issues. The Quantile regression technique is employed to test for the relationship between private and public health care expenses and its determinants. The Pooled mean group causality test is used to examine the causal connections among the variables. Results The outcome of the quantile regression test revealed that economic growth and aging population could induce healthcare costs in emerging countries. However, the impact of industrialization, agricultural activities, and technological advancement on health expenses are found to be noticeably heterogeneous at the various quantile levels. Unidirectional causality was found between industrialization and public health expenses; whereas two-way causal influence was reveled amongst public health expenditure and GDP per capita; public health expenditure and agricultural activities. Conclusion It is therefore suggested that effective and integrated strategies should be considered by industries and agricultural sectors to help reduce preventable diseases that will ultimately reduce healthcare costs among the emerging countries.

BackgroundWhile the demand for health services keep escalating at the grass roots or rural areas of China, a substantial portion of healthcare resources remain stagnant in the more developed cities and this has entrenched health inequity in many parts of China. At its conception, China’s Deepen Medical Reform started in 2012 was intended to flush out possible disparities and promote a more equitable and efficient distribution of healthcare resources. Nearly half a decade of this reform, there are uncertainties as to whether the attainment of the objectives of the reform is in sight.MethodsUsing a hybrid of panel data analysis and an augmented data envelopment analysis (DEA), we model human resources, material, finance to determine their technical and scale efficiency to comprehensively evaluate the transverse and longitudinal allocation efficiency of community health resources in Jiangsu Province.ResultsWe observed that the Deepen Medical Reform in China has led to an increase concern to ensure efficient allocation of community health resources by health policy makers in the province. This has led to greater efficiency in health resource allocation in Jiangsu in general but serious regional or municipal disparities still exist. Using the DEA model, we note that the output from the Community Health Centers does not commensurate with the substantial resources (human resources, materials, and financial) invested in them. We further observe that the case is worst in less-developed Northern parts of Jiangsu Province.ConclusionsThe government of Jiangsu Province could improve the efficiency of health resource allocation by improving the community health service system, rationalizing the allocation of health personnel, optimizing the allocation of material resources, and enhancing the level of health of financial resource allocation.

BackgroundChina has become the world‘s second largest healthcare market based on a recent report by the World Health Organization. Eventhough China achieved universal health insurance coverage in 2011, representing the largest expansion of insurance coverage in human history achieved; health inequality remains endemic in China. Lessons from the effect of market crisis on health equity in Europe and other places has reignited interest in exploring the potential healthcare market aberrations that can trigger distributive injustice in healthcare resource allocation among China’s provinces. Recently, many healthcare investors in China have become more concerned about capital preservation, and are responding by abandoning long term investments strategies in healthcare. This investment withdrawal en mass is perceived to be influenced by herding tendencies and can trigger or consolidate endemic health inequality.MethodsOur study simultaneously employs four testing models (two state spaced models and two return dispersion models) to establish the existence of procyclical (herding) behavior among the stocks and its health equity implications. These are applied to a large set of data to compare and contrast results of herd formation among investors in fourteen healthcare sectors in China.ResultsThe study reveals that apart from the cross sectional standard deviation (CSSD) model, the remaining two models and our augmented state space model yields significant evidence of herding in all subsectors of the healthcare market. We also find that the herding effect is more prominent during down movements of the market.ConclusionHerding behavior may lead to contemporaneous loss of investor confidence and capital withdrawal and thereby deprive the healthcare sector of the much needed capital for expansion. Thus there may be obvious delay in efforts to bridge the gap in access to healthcare facilities, medical support services, medical supplies, pharmaceuticals, biotechnology, diagnostic substances, medical laboratory and advanced medical equipment across China. Moreover, a potential crash in the healthcare market is possible in the healthcare sector as a result of persistent herding tendencies among investors and that may have more damaging consequences for health inequality in China.