| 1. |
- Dieleman, J., et al.
(författare)
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Evolution and patterns of global health financing 1995-2014 : Development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries
- 2017
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Ingår i: The Lancet. - : Lancet Publishing Group. - 0140-6736 .- 1474-547X. ; 389:10083, s. 1981-2004
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Tidskriftsartikel (refereegranskat)abstract
- Background: An adequate amount of prepaid resources for health is important to ensure access to health services and for the pursuit of universal health coverage. Previous studies on global health financing have described the relationship between economic development and health financing. In this study, we further explore global health financing trends and examine how the sources of funds used, types of services purchased, and development assistance for health disbursed change with economic development. We also identify countries that deviate from the trends. Methods: We estimated national health spending by type of care and by source, including development assistance for health, based on a diverse set of data including programme reports, budget data, national estimates, and 964 National Health Accounts. These data represent health spending for 184 countries from 1995 through 2014. We converted these data into a common inflation-adjusted and purchasing power-adjusted currency, and used non-linear regression methods to model the relationship between health financing, time, and economic development. Findings: Between 1995 and 2014, economic development was positively associated with total health spending and a shift away from a reliance on development assistance and out-of-pocket (OOP) towards government spending. The largest absolute increase in spending was in high-income countries, which increased to purchasing power-adjusted $5221 per capita based on an annual growth rate of 3.0%. The largest health spending growth rates were in upper-middle-income (5.9) and lower-middle-income groups (5.0), which both increased spending at more than 5% per year, and spent $914 and $267 per capita in 2014, respectively. Spending in low-income countries grew nearly as fast, at 4.6%, and health spending increased from $51 to $120 per capita. In 2014, 59.2% of all health spending was financed by the government, although in low-income and lower-middle-income countries, 29.1% and 58.0% of spending was OOP spending and 35.7% and 3.0% of spending was development assistance. Recent growth in development assistance for health has been tepid; between 2010 and 2016, it grew annually at 1.8%, and reached US$37.6 billion in 2016. Nonetheless, there is a great deal of variation revolving around these averages. 29 countries spend at least 50% more than expected per capita, based on their level of economic development alone, whereas 11 countries spend less than 50% their expected amount. Interpretation: Health spending remains disparate, with low-income and lower-middle-income countries increasing spending in absolute terms the least, and relying heavily on OOP spending and development assistance. Moreover, tremendous variation shows that neither time nor economic development guarantee adequate prepaid health resources, which are vital for the pursuit of universal health coverage. © The Author(s). Published by Elsevier Ltd.
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| 2. |
- Dieleman, J. L., et al.
(författare)
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Future and potential spending on health 2015-40 : Development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries
- 2017
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Ingår i: The Lancet. - : Lancet Publishing Group. - 0140-6736 .- 1474-547X. ; 389:10083, s. 2005-2030
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Tidskriftsartikel (refereegranskat)abstract
- Background: The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods: We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings: We estimated that global spending on health will increase from US$9.21 trillion in 2014 to $24.24 trillion (uncertainty interval [UI] 20.47-29.72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5.3% (UI 4.1-6.8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4.2% (3.8-4.9). High-income countries are expected to grow at 2.1% (UI 1.8-2.4) and low-income countries are expected to grow at 1.8% (1.0-2.8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133-181) per capita in 2030 and $195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries. Interpretation: Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential. © The Author(s).
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| 3. |
- Wong, Winnie S., et al.
(författare)
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A pixel detector asic for dosimetry using time-over-threshold energy measurements
- 2011
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Ingår i: Radiation Measurements. - : Elsevier BV. - 1350-4487 .- 1879-0925. ; 46:12, s. 1619-1623
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Tidskriftsartikel (refereegranskat)abstract
- In this work we present the design of a chip which provides the readout of a highly segmented diode array, in which signals induced by individual X-ray photons are processed discretely. There are several benefits to this approach, including the ability to achieve a high signal to noise ratio due to the inherently low sensor capacitance, and the suppression of background noise (e.g. dark current) using an analogue threshold. The segmentation also ensures a linear behaviour even at very high dose rates. A time over threshold (ToT1) energy measurement technique provides an immediate digital value corresponding to the energy deposited onto the diode by each individual photon. Deadtime-free operation is achieved by reading out a subset of the detector segments at a time while the rest of the detector continues to process signals. This paper describes the application-specific integrated circuit (ASIC) chip which was designed to provide pre-processing of photo-induced signals in the detector and readout of the processed digital data.
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| 4. |
- Wong, Winnie S, et al.
(författare)
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Electrical measurements of a multi-mode hybrid pixel detector ASIC for radiation detection
- 2012
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Ingår i: Journal of Instrumentation. - 1748-0221. ; 7:1, s. Art. no. C01056-
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Tidskriftsartikel (refereegranskat)abstract
- We present the first electrical measurements of an application-specific integrated circuit (ASIC) to be used in a hybrid pixel detector intended for dosimetry and radiation detection. The dosimeter has three programmable modes of operation: photon counting mode, energy integration mode, and dosimetry mode. The ASIC comprises a matrix of 16 by 16 (256 total) square pixels of 220 ÎŒm pitch, providing 12.4 mm 2 of segmented active area. Each pixel can be configured to operate in one of the three radiation measurement modes, with programmable-depth counters and shift registers to tailor the data word size and optimise the readout frame-rate in a given mode. The individual energies of impinging photons are determined through programmable analogue energy threshold discrimination, time over threshold measurement, or a combination thereof. Furthermore, the dosimetry mode contains 16 digital energy thresholds and automatically sorts data into 16 corresponding energy bin registers. The chip's output is therefore pre-processed charge spectra of the radiation field. This paper discusses results from measurements taken using programmable test-pulses to inject controlled stimuli into the pixel circuits.
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