Hospitalization, mortality and public healthcare expenditure in Brazil during the COVID-19 crisis: vulnerabilities in the spotlight

In China, upper-level healthcare (ULHC) and lower-level healthcare (LLHC) provide different public medical and health services. Only when these two levels of healthcare resources are distributed equally and synergistically can the public’s demands for healthcare be met fairly. Despite a number of previous studies having analysed the spatial distribution of healthcare and its determinants, few have evaluated the differences in spatial equity between ULHC and LLHC and investigated their institutional, geographical and socioeconomic influences and spillover effects. This study aims to bridge this gap by analysing panel data on the two levels of healthcare resources in 31 Chinese provinces covering the period 2003–2015 using Moran’s I models and dynamic spatial Durbin panel models (DSDMs). The results indicate that, over the study period, although both levels of healthcare resources improved considerably in all regions, spatial disparities were large. The spatio-temporal characteristics of ULHC and LLHC differed, although both levels were relatively low to the north-west of the Hu Huanyong Line. DSDM analysis revealed direct and indirect effects at both short-and long-term scales for both levels of healthcare resources. Meanwhile, the influencing factors had different impacts on the different levels of healthcare resources. In general, long-term effects were greater for ULHC and short-term effects were greater for LLHC. The spillover effects of ULHC were more significant than those of LLHC. More specifically, industrial structure, traffic accessibility, government expenditure and family healthcare expenditure were the main determinants of ULHC, while industrial structure, urbanisation, topography, traffic accessibility, government expenditure and family healthcare expenditure were the main determinants of LLHC. These findings have important implications for policymakers seeking to optimize the availability of the two levels of healthcare resources.

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Public Healthcare: Expenditure in PHCs and CHCs in Maharashtra

FIIB Business Review ◽

10.1177/2455265820160107s ◽

2016 ◽

Vol 5 (5) ◽

pp. 42-49

Author(s):

Veena Iyer

Keyword(s):

Healthcare Expenditure ◽

Public Healthcare

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MARKET SEGMENTATION IN HEALTHCARE

Marketing and Management of Innovations ◽

10.21272/mmi.2019.3-12 ◽

2019 ◽

pp. 151-166

Author(s):

Irena Antosova ◽

Naďa Hazuchova ◽

Jana Stavkova

Keyword(s):

Prescription Drugs ◽

Low Income ◽

Healthcare Expenditure ◽

Relative Number ◽

Primary Data ◽

Living Standard ◽

Public Healthcare ◽

Development Expenditure ◽

Income Decile ◽

Low Income Households

The share of healthcare expenditure in the first income decile in their income is higher in comparison with other deciles, however, their expenditure is the lowest. The main purpose of the research is to show the availability of healthcare in different income groups of households. Literature sources indicate that some specific household social classes face problems with access to healthcare because of low income. Firstly, public healthcare expenditure is evaluated. The low share of research and development expenditure in healthcare is alarming. Investigation continues in the accessibility of healthcare and medicines in households. The paper reveals segments of endangered low-income households with insufficient healthcare that decrease their living standard. The main data source for conducted analyses of household situations is primary data from Household Budget Survey and primary data from EU-Statistics on Income and Living Conditions survey in four years 2007, 2010, 2014 and 2016 in the Czech Republic. The paper presents the results of an analysis of households which showed that first low-income decile has the lowest healthcare payments in absolute expression but the relative number of healthcare expenditure confirms that low-income households spend the most of their income on healthcare in the comparison with other households. The first income decile is mainly composed of old-age pensioners and unemployed consumers. The structure of household healthcare expenditure according to expenditure categories shows that all consumers pay the most for non-prescription drugs followed by prescription drugs, orthopaedic and therapeutic aids, ambulatory dental care and ambulatory medical care. The research confirms that specific groups of households cannot afford appropriate healthcare. The constructed Health Poverty Index expresses that low-income households would need their income to be higher by at least 4.36 % to be able to afford average healthcare expenditure and appropriate healthcare.

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Causal impact of social care, public health and healthcare expenditure on mortality in England: cross-sectional evidence for 2013/2014

BMJ Open ◽

10.1136/bmjopen-2020-046417 ◽

2021 ◽

Vol 11 (10) ◽

pp. e046417

Author(s):

Stephen Martin ◽

Francesco Longo ◽

James Lomas ◽

Karl Claxton

Keyword(s):

Public Health ◽

Social Care ◽

Healthcare Expenditure ◽

Least Squares Method ◽

Total Mortality ◽

Public Healthcare ◽

Cross Sectional ◽

Local Public Health ◽

Spending Growth ◽

The Impact

ObjectivesThe first objective is to estimate the joint impact of social care, public health and healthcare expenditure on mortality in England. The second objective is to use these results to estimate the impact of spending constraints in 2010/2011–2014/2015 on total mortality.MethodsThe impact of social care, healthcare and public health expenditure on mortality is analysed by applying the two-stage least squares method to local authority data for 2013/2014. Next, we compare the growth in healthcare and social care expenditure pre-2010 and post-2010. We use the difference between these growth rates and the responsiveness of mortality to changes in expenditure taken from the 2013/2014 cross-sectional analysis to estimate the additional mortality generated by post-2010 spending constraints.ResultsOur most conservative results suggest that (1) a 1% increase in healthcare expenditure reduces mortality by 0.532%; (2) a 1% increase in social care expenditure reduces mortality by 0.336%; and (3) a 1% increase in local public health spending reduces mortality by 0.019%. Using the first two of these elasticities and data on the change in spending growth between 2001/2002–2009/2010 and 2010/2011–2014/2015, we find that there were 57 550 (CI 3075 to 111 955) more deaths in the latter period than would have been observed had spending growth during this period matched that in 2001/2002–2009/2010.ConclusionsAll three forms of public healthcare-related expenditure save lives and there is evidence that additional social care expenditure is more than twice as productive as additional healthcare expenditure. Our results are consistent with the hypothesis that the slowdown in the rate of improvement in life expectancy in England and Wales since 2010 is attributable to spending constraints in the healthcare and social care sectors.

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Public healthcare expenditure and COVID-19 mortality in Spain and in Europe. Response to the Letter from the Editor by Velasco et al

Revista Clínica Española (English Edition) ◽

10.1016/j.rceng.2021.09.002 ◽

2021 ◽

Author(s):

F.J. Elola-Somoza ◽

M.C. Bas-Villalobos ◽

J. Pérez-Villacastín ◽

C. Macaya-Miguel

Keyword(s):

Healthcare Expenditure ◽

Public Healthcare

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Drivers of Public Health Expenditure in Kenya: Do Structural Breaks Matter?

European Scientific Journal ESJ ◽

10.19044/esj.2021.v17n23p143 ◽

2021 ◽

Vol 17 (23) ◽

pp. 143

Author(s):

Cyprian Amutabi

Keyword(s):

Public Health ◽

Health Expenditure ◽

Structural Breaks ◽

Healthcare Expenditure ◽

Human Life ◽

Structural Break ◽

Public Healthcare ◽

Health Coverage ◽

Public Health Expenditure ◽

Long Run

Health forms the basic foundation of the quality of human life, which is an ultimate ingredient towards the productivity and efficiency of an economy. The rapid growth of health expenditure has emerged as an enormous concern for many households and governments globally. This study used timeseries data for the period 1985–2018 in unearthing the drivers of healthcare expenditure in Kenya, with a central focus on the role of health shocks. The study also sought to assess whether structural breaks mattered in a healthcare expenditure model. A public healthcare expenditure model was estimated using the Autoregressive Distributed Lag (ARDL) model. The findings revealed the presence of a long-run relationship between public health expenditure and its determinants in Kenya. Population growth rate and CO2 emissions (proxy to respiratory illnesses) were found to significantly and positively determine public health expenditure in the short run. This impact was insignificant in the long run. Similarly, GDP per capita and the number of HIV/AIDs infections positively and significantly determined public health expenditure in the long run. A key finding of this study highlighted the importance of testing for structural breaks in analyzing a time-series healthcare expenditure model. Previously, this is something that has been largely omitted in the Kenyan healthcare context. The structural break dummy variables significantly determined public health expenditure and, therefore, their incorporation in the model yielded a more accurate forecast with better econometric estimates. The findings will be useful in informing the government’s health budgetary allocation as well as the design of appropriate shock mitigation policies. This is paramount for the country in achieving not only Universal Health Coverage but also high-quality medical care to its citizens as envisioned in the ‘Big Four Agenda’ government priorities.

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Anatomy and Significance of Public Healthcare Expenditure and Economic Growth Nexus in India

Social, Health, and Environmental Infrastructures for Economic Growth - Advances in Finance, Accounting, and Economics ◽

10.4018/978-1-5225-2364-2.ch007 ◽

2017 ◽

pp. 120-144 ◽

Cited By ~ 1

Author(s):

Sovik Mukherjee

Keyword(s):

Economic Growth ◽

Healthcare Expenditure ◽

Panel Cointegration ◽

Policy Implications ◽

Future Research ◽

Public Healthcare ◽

Infrastructure Development ◽

Vector Error Correction ◽

Health Infrastructure ◽

Set Up

The objective of this chapter is to take a closer look at the liaison between the two focus variables viz. growth and public healthcare expenditure, and the associated implications for public health infrastructure development. Initially, a theoretical model has been proposed which brings out the link between the focus variables. Panel cointegration and causality are the techniques applied in a Vector Error Correction Mechanism (VECM) set-up using panel data from 1980-2015. Next, a health infrastructure index has been constructed using the Euclidean distance function approach for India for two time points i.e. 2005-06 and 2014-15, to evaluate the interstate performance in public healthcare infrastructure. The findings validate the existence of a cointegrated relationship between health expenditure and economic growth coupled with a bidirectional causality linking the focus variables in this model. It comes to a close by highlighting the policy implications and the future research possibilities in this regard.

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