We identify health sector reforms implemented in Bangladesh over the past 30 years and examine their impact on health system outcomes. Studies were included if they identified health sector reforms implemented in Bangladesh, focused on reforms affecting health system outcomes, were published between 1991 and 2023 in English or French, and were full-text peer-reviewed articles, literature reviews, book chapters, grey literature or reports. Twenty-four studies were included. Over the past three decades, Bangladesh’s health system has been transformed to improve outcomes, with crucial funding from development partners. Sector-wide approaches and subsequent reforms have improved services, tackling issues such as shortages of professionals, financial constraints and barriers to access. Improvements were made in staffing levels, but disparities between rural and urban areas persisted. Although financial reforms stimulated funding, achieving universal health coverage through direct payments proved challenging. Monitoring and evaluation capabilities have improved, but issues such as inadequate drug supply and high out-of-pocket expenditure require ongoing attention to enhance Bangladesh’s health system. Reforms such as sector-wide approaches have improved health system performance, but persistent problems underline the need for sustained attention and comprehensive reforms to achieve a sustainable improvement.
Global health expenditures, which have increased over the past 20 years, and especially reimbursement of health expenditures in developed and developing countries, mainly by government budgets, have further increased the importance of effective and efficient use of resources used in funding these expenditures. In this study, absolute productivity of healthcare services provided between 2009 and 2020 in Türkiye was measured using EATWIOS, which has not been used in the field of health so far, as integrated with CRITIC. Findings showed that productivity of healthcare services in Türkiye in the period of 2009–2022 was close to the productivity threshold but still low. This was particularly attributed to the low rates of satisfaction from services provided by university and private sector hospitals and the excessiveness of both current and investment expenditures for health. Findings of sensitivity analysis, on the other hand, showed that rather than input weights, satisficing levels determined for outcomes were effective on the productivity scores. Thus, it was concluded that in order to raise the productivity of healthcare services in Türkiye, it would be beneficial to increase the rates of satisfaction from the healthcare services provided by university and private sector hospitals and to reduce health expenditures made by state hospitals.
Health expenditures, which are one of the main areas of health economics, are among the topics that have been discussed recently. The increase in health expenditures puts pressure on the public budget of many countries. In addition, health expenditures increase the health level of society and accelerate development with their contributions to human capital. In this study, Turkey’s current health expenditure (% of gross domestic product (GDP)) was estimated using multiple linear regression, artificial neural networks, random forest (RF) and support vector regression (SVR) methods. In the study, the ratio of current health expenditure to GDP is the dependent variable, life expectancy at birth, the population aged 65 and over (% of the total population), the number of physicians per 1,000 people, the infant mortality rate and the number of hospital beds per 1,000 people were considered as independent variables. 75% of the data set was reserved for training and 25% for test data. The performance of the regression models obtained was compared by calculating the coefficient of determination, mean squared error, root mean square error, mean absolute error and mean absolute percent error, which are goodness-of-fit criteria. Results show that the radial-based SVR and RF models had better prediction results for the entire data set.
Child malnutrition poses a significant challenge in India, impacting both the physical and mental development of children and giving rise to socio-economic difficulties. This study seeks to investigate the prevalence of malnutrition, disparities across regions and social strata, trends of state-wise allocation of resources under nutritional schemes and their impact on malnutrition among children under the age of five. The study utilises secondary data from state budget documents and the National Family Health Survey for various rounds spanning from 1997–1998 to 2021–2022. The study employs scatterplots and multiple linear regression models within a cross-sectional framework for analysing data. The findings reveal that there are improvements in nutritional status among children in Indian states over the period of time. However, malnutrition rates among children in Bihar, Gujarat, Chhattisgarh, Jharkhand, Madhya Pradesh and Karnataka are still higher, and they need immediate attention. Rural areas, in particular, register higher proportions of stunting, wasting and underweight among children. The expenditure on nutrition-related schemes is rising over the period. Though the share of state expenditure on nutrition as a percentage of gross state domestic product in low-income states (LIS) is higher than the same in high-income states (HIS) in recent years, state-level per capita expenditure on nutrition is higher in HIS than in LIS throughout the period. State-level per capita allocation for Integrated Child Development Services (ICDS) and the Poshan Abhiyan scheme are found to play an important role in reducing stunting, wasting and underweight. Specifically, a 1% rise in per capita ICDS allocation to a state significantly reduces underweight prevalence by 0.04% among children under five. Similarly, an increase in per capita Poshan Abhiyan expenditure by 1% is associated with declines in stunting by 0.02% and underweight by 0.04%. There is a need to increase government spending on nutrition-related schemes, make the schemes well-targeted and prioritise integrated health and nutrition strategies in social welfare schemes for the reduction of child malnutrition in India. Measures on effective utilisation of schemes, creating awareness on various schemes for nutrition and improving women’s education are required to sustainably reduce child malnutrition in India.
This study aims to classify the Organisation for Economic Co-operation and Development (OECD) countries through cluster analysis according to the Global Health Security Index (GHSI) 2019 and 2021 data. Within the scope of the research, the dimensions of the GHSI were determined as variables. First, the appropriate number of clusters was determined using Ward’s method, which is one of the hierarchical cluster analyses, and then the countries were divided into clusters using the K-means method, which is a non-hierarchical cluster analyses methods. Differences between variables according to clusters were determined with the analysis of variance (ANOVA) test. As a result of the cluster analysis of the GHSI 2019 data, it was determined that there were 14 countries in the 1st cluster, 11 countries in the 2nd cluster and 13 countries in the 3rd cluster. As a result of the cluster analysis of the GHSI 2021 data, it was determined that there were 9 countries in the 1st cluster, 14 countries in the 2nd cluster, 4 countries in the 3rd cluster and 11 countries in the 4th cluster. According to both data sets, it was observed that there was a statistically significant difference between the countries in terms of all variables. In the cluster analysis results of the GHSI 2019 and 2021 statistics, it was seen that similar countries were in the same cluster. It was observed that countries that were prepared for health emergencies according to the 2019 data were not prepared due to the COVID-19 pandemic in the 2021 data.
