Projections of health expenditure

2019 ◽  
Keyword(s):  
Health Expenditure

Empirical analysis of factors influencing the public health expenditure in Malaysia

2018 ◽  
Vol 6 (3) ◽  
pp. 1
Author(s):  
Kok Wooi Yap ◽  
Doris Padmini Selvaratnam
Keyword(s):  
Public Health ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Health Expenditure ◽  
Price Index ◽  
Infant Mortality Rate ◽  
Public Health Expenditure ◽  
The Public ◽  
Empirical Results ◽  
Per Capita

This study aims to investigate the determinants of public health expenditure in Malaysia. An Autoregressive Distributed Lag (ARDL) approach proposed by Pesaran & Shin (1999) and Pesaran et al. (2001) is applied to analyse annual time series data during the period from 1970 to 2017. The study focused on four explanatory variables, namely per capita gross domestic product (GDP), healthcare price index, population aged 65 years and above, as well as infant mortality rate. The bounds test results showed that the public health expenditure and its determinants are cointegrated. The empirical results revealed that the elasticity of government health expenditure with respect to national income is less than unity, indicating that public health expenditure in Malaysia is a necessity good and thus the Wagner’s law does not exist to explain the relationship between public health expenditure and economic growth in Malaysia. In the long run, per capita GDP, healthcare price index, population aged more than 65 years, and infant mortality rate are the important variables in explaining the behaviour of public health expenditure in Malaysia. The empirical results also prove that infant mortality rate is significant in influencing public health spending in the short run. It is noted that macroeconomic and health status factors assume an important role in determining the public health expenditure in Malaysia and thus government policies and strategies should be made by taking into account of these aspects.

The monetary value of disability-adjusted-life-years lost in Kenya in 2017.pdf

2019 ◽  
Author(s):  
Joses Kirigia ◽  
Rose Nabi Deborah Karimi Muthuri
Keyword(s):  
New York ◽  
International Monetary Fund ◽  
Health Expenditure ◽  
Analytical Framework ◽  
World Health ◽  
Gdp Per Capita ◽  
Current Health ◽  
Monetary Value ◽  
Life Years ◽  
Per Capita

<div>A variant of human capital (or net output) analytical framework was applied to monetarily value DALYs lost from 166 diseases and injuries. The monetary value of each of the 166 diseases (or injuries) was obtained through multiplication of the net 2019 GDP per capita for Kenya by the number of DALYs lost from each specific cause. Where net GDP per capita was calculated by subtracting current health expenditure from the GDP per capita. </div><div> </div><p>The DALYs data for the 166 causes were from IHME (Global Burden of Disease Collaborative Network, 2018), GDP per capita data from the International Monetary Fund world economic outlook database (International Monetary Fund, 2019), and the current health expenditure per person data from the WHO Global Health Expenditure Database (World Health Organization, 2019b). A model consisting of fourteen equations was calculated with Excel Software developed by Microsoft (New York).</p><p> </p>

scholarly journals Case study of the beneficiary group distribution of curative care expenditure based on SHA 2011 in Xinjiang autonomous region, China

BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e043155
Author(s):  
Honghong Feng ◽  
Kai Pan ◽  
Xiaoju Li ◽  
Liwen Zhang ◽  
Lu Mao ◽  
...  
Keyword(s):  
Health Expenditure ◽  
Age Groups ◽  
Family Health ◽  
Curative Care ◽  
Medical Institutions ◽  
Health Policy Analysis ◽  
Health Accounts ◽  
System Of Health Accounts ◽  
Xinjiang Autonomous Region

BackgroundThe System of Health Accounts 2011 (SHA 2011) assists in health policy analysis and health expenditure comparison at the international level. Based on SHA 2011, this study analysed the distribution of beneficiary groups of curative care expenditure (CCE) in Xinjiang, to present suggestions for developing health policies.MethodsA total of 160 health institutions were selected using the multistage stratified random sampling method. An analysis of the agewise CCE distribution, institutional flow, and disease distribution was then performed based on the SHA 2011 accounting framework.ResultsIn 2016, the CCE in Xinjiang was ¥50.05 billion, accounting for 70.18% of current health expenditure and 6.66% of the gross domestic product. The per capita CCE was ¥2366.56. The CCE was distributed differently across age groups, with the highest spending on people over the age of 65 years. The CCE was highest for diseases of the circulatory, respiratory and digestive systems. Most of the expenditure was incurred in hospitals and, to a lesser extent, in primary healthcare institutions. Family health expenditure, especially on children aged 14 years and below, accounted for a relatively high proportion of the CCE.ConclusionSHA 2011 was used to capture data, which was then analysed according to the newly added beneficiary dimension. The findings revealed that the use of medical resources is low, the scale of primary medical institutions needs to be significantly expanded and there is a need to optimise the CCE financing scheme. Therefore, the health policymaking department should optimise the relevant policies and improve the efficiency of health services.

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