Funding the National Health Service is the biggest single thing the government does, so it is not surprising that it is at the forefront of the election campaign. In this report, we look at how health spending has changed over the last 70 years and place funding increases since 2010 in the context of the pressures associated with an ageing population. We then compare existing spending plans for the NHS to those implied by the political parties' manifestos at the 2017 general election and examine capital spending on the health service. Finally, we consider the longer term outlook for health spending.
Health spending has risen rapidly in Japan. We find two-thirds of the spending increase over 1990–2011 resulted from ageing, and the rest from excess cost growth. The spending level will rise further: ageing alone will raise it by 3½ percentage points of GDP over 2010–30, and excess cost growth at the rate observed over 1990–2011 will lead to an additional increase of 2–3 percentage points of GDP. This will require a sizable increase in government transfers. Japan can introduce micro- and macro-reforms to contain health spending, and financing options should be designed to enhance equ
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Using a panel dataset of 320 Indonesian districts we examine the impact of district budgets on public health spending, utilization patters in the public and private sector, and private health spending in the four years after decentralization. We exploit the panel structure of the data and the fact that district budgets are largely driven by central government transfers to determine causal patterns. We find that the elasticity of public health spending with respect to district budgets is around 0.9 with a higher elasticity for development spending than for routine spending. District splits reduce public health spending. We find a positive effect of public district health spending on public sector utilization, with the strongest effects in the poorest two quintiles. We find no significant effects on private sector utilization and out of pocket health expenditures.
Gesundheitsausgaben steigen weiterhin exorbitant an und wachsen weitaus mehr als die Wirtschaft in den meisten OECD-Ländern. Nach der Wirtschaftskrise suchen die Länder nach Möglichkeiten, die Kosten zu senken und die Effizienz der Gesundheitsversorgung zu erhöhen. Die Studie zeigt aktuelle Ansätze: Maßnahmen wie Vorkasse, Koordination der Versorgung und klinische Leitlinien werden dabei genauer unter die Lupe genommen.
What factors determine a country's spending on health? And what factors determine the share of spending financed by the public sector? Taking these factors into account, is post‐communist health spending unusual? For the OECD economies, we find that per capita health spending is strongly related to per capita income, with an elasticity of about 1.5. The elasticity for developing economies is close to one. Spending is also positively related to the elderly dependency rate, but the relationship is weaker than a static comparison of spending by the elderly and non‐elderly would suggest. Even though health spending as a share of GDP in the post‐communist countries of eastern and central Europe is below the OECD average, there is evidence of above normal health spending in most countries when we control for income and demographics. For Hungary, the 'excess' spending reached over three percentage points of GDP in 1994. For the OECD sample, four development indicators account for half the variation in the public sector share of total health spending. Political variables help explain the remainder. If the post‐communist countries converge to the market economy pattern, the share of public financing will fall, yet still remain well above half.
Health is important for sustainable economic performance of a country. This study seeks to investigate the effectiveness of public health spending on health outcomes. This is obtained by estimating a health production function for Kenya. In the study, infant mortality rate is used to measure health outcomes. The study uses time series data running from 1984 to 2015. The data is obtained from World Bank database and Kenya National Bureau of Statistics Economic Surveys. Error Correction Model (ECM) is adopted due to presence of cointegration. The results show that public expenditure on average influence health outcomes in Kenya. These results therefore provide evidence to support that increase in public expenditure improves health outcomes. The other factor that is found to be important determinant of health outcomes in Kenya is child immunization. The major policy implication of this study is that Kenyan government should increase budgetary allocation to health sector. In addition, government of Kenya should allocate more resources to child immunization.
This research evaluates government education and health spending in China and explores the underlying determinants of its spatial pattern. A framework defining local needs at three levels is proposed to analyze whether the expenditure has been reasonably allocated. Results show that both government education and health spending closely respond to local needs at the general level. The illiteracy rate is positively correlated with government education spending while the life expectancy is negatively correlated with government health spending. On the demand and supply sides, while government education spending is more responsive to local demand measured by student number, the needs from the supply side represented by the number of medical personnel appear to be more relevant when governments distribute resources into the health sector. One particular area that needs more effort is the responsiveness to the needs arising from the lack of teaching staff. The student-teaching ratio is now largely ignored when governments make decisions of education outlays. Given that the adequacy of teaching staff is a must to ensure the quality of teaching, governments are thus suggested to put more weights to this aspect in its decision-making process. As for the determinants of government education and health spending, this study takes a close look at three groups of key potential explaining factors identified in the existing literature – economic development, openness and decentralization. The findings pose challenges to the existing mainstream theories developed in the western context. Only per capita gross regional product is found to have significant explanatory power for budgetary expenditure on education and a significant negative relationship is revealed. On the other hand, both economic development and the degree of fiscal dependency are significant in explaining the spatial pattern of government health spending; and their relationships are both non-linear. The fixed-effects panel data regression model predicts that, ceteris paribus, a province with a per capita gross regional product of 20,265 yuan would have the most government health outlays while a province with a fiscal dependency ratio of 63.6% would have the lowest public health expenditure. Provinces with either higher or lower per capita GRP (fiscal dependency ratio) than the threshold value allocate fewer (more) resources into government health outlays. The most important recommendation derived from the findings of this dissertation is that the central government should keep an eye on those provinces that are neither fully financially dependent nor fully financially independent, because their government health spending tends to be particularly inadequate. ; published_or_final_version ; China Development Studies ; Master ; Master of Arts in China Development Studies
Governments have been thrust to the forefront of health care reform efforts as growth in government health care costs was faster than growth in all other sponsor sectors in 1991. In the business sector, real health care costs per worker have risen 65 times faster than real wages and salaries per worker during the past 26 years. Households continue to devote 5 percent of income after taxes to health care, the same percentage for the last 8 years. This article presents data supporting these findings, and an analysis of health care spending by each sponsor sector.
