116 research outputs found

    A Comparative Study on Outcome of Government and Co-Operative Community-Based Health Insurance in Nepal

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    BackgroundThere are different models for community-based health insurance (CBHI), and in Nepal, among them, the government and the local communities (co-ops) are responsible for operating the CBHI models that are in practice.AimsThe aim of this study is to compare the outcomes in relation to benefit packages, population coverage, inclusiveness, healthcare utilization, and promptness of treatment for the two types of CBHI models in Nepal.MethodsThis study was an observational and interactive descriptive study using the concurrent mixed approach of data collection, framing, and compilation. Quantitative data were collected from records, and qualitative data were collected from key informants in all 12 CBHI groups. Unstructured questionnaires, observation checklists, and memo notepads were used for data collection. Descriptive statistics and the Mann–Whitney U test were used when appropriate. Ethically, written informed consent was obtained from the respondents who participated in the study, and they were told that they could withdraw from the study anytime.ResultsThe study revealed the following: new enrolment did not increase in either group; however, the healthcare utilization rate did (Government 107% and co-ops 137%), while the benefit packages remained almost same for both groups. Overall, inclusiveness was higher for the government group. For the CBHI co-ops, enrollment among the religious minority and the discount negotiated with the hospitals for treatment were significantly higher, and the promptness in reaching a hospital was significantly faster (p < 0.05) than that in the government-operated CBHI.ConclusionFindings indicate that CBHI through co-ops would be a better model because of its lower costs and ability to enhance self-responsiveness and the overall health system. Health insurance coverage is the most important component to achieve universal health coverage

    Universal health coverage: the long road ahead for low- and middle-income regions

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    Universal health coverage (UHC) is one of the core Millennium Development Goals adopted in the United Nations and the World Health Organization’s (WHO) strategic agenda. Surprisingly, even as we approach the year 2021, achieving UHC to a reasonable extent and protecting the most vulnerable segments of native populations remains a challenge even for the richest of nations (1). In recent years, traditional world health sector establishments have assumed that most of the market demand for drugs, medical technologies, and services took place in rich Western societies, including Japan (2). Most of the market supply in terms of innovation and technology production led by multinational businesses, such as Big Pharma companies, also took place in these nations (3, 4). Back in 2000, WHO estimates on national health systems worldwide ranked the top ten systems, seven of which were European and only three of which were Asian (Japan, Oman, and Singapore) (5). Due to urbanization on a mega scale, however, growth in living standards and affordability of medical care and medicines can be seen throughout rapidly developing regions (primarily the BRIC nations (Brazil, Russia, India, China) and Southern and Eastern Asia) (6). In November 2018, a public announcement by the Chancellor of Germany, the largest EU economy, emphasized that most of the essential innovation in this area is now taking place either in North America or Far East Asia, far surpassing the European Union. All of these changes reflect heavily on the market demand for drugs, medicinal devices, services, and long-term care worldwide (7). Until the early 2000s, the global pharmaceutical market was still heavily dominated by the USA, representing approximately a 4% share of the global population and almost 50% consumption of brand-name medicines expressed in value-based turn over. Japan was ranked second in the same terms, preserving this position for a very long time. The contemporary pace of pharmaceutical innovation remains to be dominated by Western, Japanese, and Israeli-based multinationals (8). On the other hand, demand is exploding among emerging economies and all major investors are aware that the lion’s share of growth opportunities as we approach 2050 will take place in these emerging economies, outside of mature high-income Organization for Economic Co-operation and Development (OECD) member nations (10). Emerging markets, such as the BRIC nations or EM7 (BRIC + Indonesia, Mexico, and Turkey), remain the core focus of foreign capital investment in long-term strategies and forecasts (9).info:eu-repo/semantics/publishedVersio

    Real GDP growth rates and healthcare spending – comparison between the G7 and the EM7 countries

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    Background: Accelerated globalisation has substantially contributed to the rise of emerging markets worldwide. The G7 and Emerging Markets Seven (EM7) behaved in significantly different macroeconomic ways before, during, and after the 2008 Global Crisis. Average real GDP growth rates remained substantially higher among the EM7, while unemployment rates changed their patterns after the crisis. Since 2017, however, approximately one half of the worldwide economic growth is attributable to the EM7, and only a quarter to the G7. This paper aims to analyse the association between the health spending and real GDP growth in the G7 and the EM7 countries. Results: In terms of GDP growth, the EM7 exhibited a higher degree of resilience during the 2008 crisis, compared to the G7. Unemployment in the G7 nations was rising significantly, compared to pre-recession levels, but, in the EM7, it remained traditionally high. In the G7, the austerity (measured as a percentage of GDP) significantly decreased the public health expenditure, even more so than in the EM7. Out-of-pocket health expenditure grew at a far more concerning pace in the EM7 compared to the G7 during the crisis, exposing the vulnerability of households living close to the poverty line. Regression analysis demonstrated that, in the G7, real GDP growth had a positive impact on out-of-pocket expenditure, measured as a percentage of current health expenditure, expressed as a percentage of GDP (CHE). In the EM7, it negatively affected CHE, CHE per capita, and out-of-pocket expenditure per capita. Conclusion: The EM7 countries demonstrated stronger endurance, withstanding the consequences of the crisis as compared to the G7 economies. Evidence of this was most visible in real growth and unemployment rates, before, during and after the crisis. It influenced health spending patterns in both groups, although they tended to diverge instead of converge in several important areas.info:eu-repo/semantics/publishedVersio

    Editorial : emerging markets' health and pharmaceutical sectors at the dawn of a potential global financial crisis of early 2020s

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    Essential pharmaceutical innovation in terms of market placement of new chemical entities featuring medicines with novel mechanisms continue to be dominated by Pharmaceutical multinational companies (Sadat Russel et al, 2014). This is gradually changing with the growth of emerging biopharma companies launching their new products rather than being bought over by major Pharma Companies (IQVIA Report 2022)

    Feasibility of implementing public-private mix approach for tuberculosis case management in Pokhara Metropolitan City of western Nepal: a qualitative study

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    BackgroundThe Public-Private Mix (PPM) approach is a strategic initiative that involves engaging all private and public health care providers in the fight against tuberculosis using international health care standards. For tuberculosis control in Nepal, the PPM approach could be a milestone. This study aimed to explore the barriers to a public-private mix approach in the management of tuberculosis cases in Nepal.MethodsWe conducted key informant interviews with 20 participants, 14 of whom were from private clinics, polyclinics, and hospitals where the PPM approach was used, two from government hospitals, and four from policymakers. All data were audio-recorded, transcribed, and translated into English. The transcripts of the interviews were manually organized, and themes were generated and categorized into 1. TB case detection, 2. patient-related barriers, and 3. health-system-related barriers.ResultsA total of 20 respondents participated in the study. Barriers to PPM were identified into following three themes: (1) Obstacles related to TB case detection, (2) Obstacles related to patients, and (3) Obstacles related to health-care system. PPM implementation was challenged by following sub-themes that included staff turnover, low private sector participation in workshops, a lack of trainings, poor recording and reporting, insufficient joint monitoring and supervision, poor financial benefit, lack of coordination and collaboration, and non-supportive TB-related policies and strategies.ConclusionGovernment stakeholders can significantly benefit by applying a proactive role working with the private in monitoring and supervision. The joint efforts with private sector can then enable all stakeholders to follow the government policy, practice and protocols in case finding, holding and other preventive approaches. Future research are essential in exploring how PPM could be optimized

    Burden of injuries in Nepal, 1990–2017: Findings from the Global Burden of Disease Study 2017

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    Background: Nepal is a low-income country undergoing rapid political, economic and social development. To date, there has been little evidence published on the burden of injuries during this period of transition.Methods: The Global Burden of Disease Study (GBD) is a comprehensive measurement of population health outcomes in terms of morbidity and mortality. We analysed the GBD 2017 estimates for deaths, years of life lost, years lived with disability, incidence and disability-adjusted life years (DALYs) from injuries to ascertain the burden of injuries in Nepal from 1990 to 2017.Results: There were 16 831 (95% uncertainty interval 13 323 to 20 579) deaths caused by injuries (9.21% of all-cause deaths (7.45% to 11.25%)) in 2017 while the proportion of deaths from injuries was 6.31% in 1990. Overall, the injury-specific age-standardised mortality rate declined from 88.91 (71.54 to 105.31) per 100 000 in 1990 to 70.25 (56.75 to 85.11) per 100 000 in 2017. In 2017, 4.11% (2.47% to 6.10%) of all deaths in Nepal were attributed to transport injuries, 3.54% (2.86% to 4.08%) were attributed to unintentional injuries and 1.55% (1.16% to 1.85%) were attributed to self-harm and interpersonal violence. From 1990 to 2017, road injuries, falls and self-harm all rose in rank for all causes of death.Conclusions: The increase in injury-related deaths and DALYs in Nepal between 1990 and 2017 indicates the need for further research and prevention interventions. Injuries remain an important public health burden in Nepal with the magnitude and trend of burden varying over time by cause-specific, sex and age group. Findings from this study may be used by the federal, provincial and local governments in Nepal to prioritise injury prevention as a public health agenda and as evidence for country-specific interventions

    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

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    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 US9.21trillionin2014to9.21 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(UI133−181)percapitain2030and154 (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.Peer reviewe

    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

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    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 US9.21trillionin2014to9.21 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(UI133−181)percapitain2030and154 (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

    Trends in future health financing and coverage: future health spending and universal health coverage in 188 countries, 2016–40

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    Background: Achieving universal health coverage (UHC) requires health financing systems that provide prepaid pooled resources for key health services without placing undue financial stress on households. Understanding current and future trajectories of health financing is vital for progress towards UHC. We used historical health financing data for 188 countries from 1995 to 2015 to estimate future scenarios of health spending and pooled health spending through to 2040. Methods: We extracted historical data on gross domestic product (GDP) and health spending for 188 countries from 1995 to 2015, and projected annual GDP, development assistance for health, and government, out-of-pocket, and prepaid private health spending from 2015 through to 2040 as a reference scenario. These estimates were generated using an ensemble of models that varied key demographic and socioeconomic determinants. We generated better and worse alternative future scenarios based on the global distribution of historic health spending growth rates. Last, we used stochastic frontier analysis to investigate the association between pooled health resources and UHC index, a measure of a country's UHC service coverage. Finally, we estimated future UHC performance and the number of people covered under the three future scenarios. Findings: In the reference scenario, global health spending was projected to increase from US10trillion(9510 trillion (95% uncertainty interval 10 trillion to 10 trillion) in 2015 to 20 trillion (18 trillion to 22 trillion) in 2040. Per capita health spending was projected to increase fastest in upper-middle-income countries, at 4·2% (3·4–5·1) per year, followed by lower-middle-income countries (4·0%, 3·6–4·5) and low-income countries (2·2%, 1·7–2·8). Despite global growth, per capita health spending was projected to range from only 40(24–65)to40 (24–65) to 413 (263–668) in 2040 in low-income countries, and from 140(90–200)to140 (90–200) to 1699 (711–3423) in lower-middle-income countries. Globally, the share of health spending covered by pooled resources would range widely, from 19·8% (10·3–38·6) in Nigeria to 97·9% (96·4–98·5) in Seychelles. Historical performance on the UHC index was significantly associated with pooled resources per capita. Across the alternative scenarios, we estimate UHC reaching between 5·1 billion (4·9 billion to 5·3 billion) and 5·6 billion (5·3 billion to 5·8 billion) lives in 2030. Interpretation: We chart future scenarios for health spending and its relationship with UHC. Ensuring that all countries have sustainable pooled health resources is crucial to the achievement of UHC. Funding: The Bill & Melinda Gates Foundation

    Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM2.5 air pollution, 1990-2019 : An analysis of data from the Global Burden of Disease Study 2019

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    Background Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution. Methods We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2·5. Interpretation Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2·5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes
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