Dataset Information

Resiliency of healthcare expenditure to income shock: Evidence from dynamic heterogeneous panels

ABSTRACT: Using the World Bank data over the period of 1960–2019, this study aims at estimating the resiliency of health expenditures against gross domestic product (GDP). Long-run and short-run elasticities are calculated using the type of panel time series methods that are exclusively designed for dynamic heterogeneous panels: Mean Group, Pooled Mean Group, and Dynamic Fixed Effects estimators. These methods permit better estimations of elasticity with considerable heterogeneity across the 177 countries included in this study. Along with a standard elasticity estimation, this study estimates country-specific long-run and short-run elasticities along with error correction components. The study finds that the long-run elasticity of income is very close to unity, but short-run coefficients are insignificant for most nations. In addition, most countries revert to long-run equilibrium reasonably quickly if there is shock as the error correction coefficients are negative and, in many cases, very close to one. While for most developed countries, the short-run elasticities are lower in comparison with the short-run elasticities of developing countries indicating that many developing countries may face a larger decrease in health expenditure with the forecasted decline in income due to impending economic recession. Therefore, although this study is not directly intended to capture the post-COVID-19 effects, the study estimates may project the potential responses in health expenditure across countries due to potential income shocks.

SUBMITTER:

PROVIDER: S-EPMC10027743 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The exponential growth of China's digital economy has exerted a profound influence on economic advancement and income distribution. To effectively tackle income inequality, it is essential to incorporate the analysis of digital economy development within the framework of fiscal expenditure. This study utilizes a comprehensive panel dataset encompassing 276 cities in China during the period from 2011 to 2020. Employing the fixed-effect model and instrumental variable method, the research investigates the influence of fiscal expenditure on the income gap while investigating the moderating effect of the digital economy. The key findings of the study can be summarized as follows: (1) In general, fiscal expenditure demonstrates a propensity to reduce the income gap. (2) Different categories of fiscal expenditure exhibit distinct effects on the income gap. Social security and employment expenditures do not significantly alleviate the income gap. Conversely, education expenditures and health expenditures tend to exacerbate the income gap. On the other hand, expenditures in agriculture, forestry, and water resources, as well as urban and rural affairs, effectively narrow the income gap. (3) The development of the digital economy enhances the capacity of fiscal expenditure to adjust income distribution, showcasing non-linear effects. From a fiscal expenditure classification perspective, the digital economy primarily enhances the effectiveness of income distribution adjustment for expenditures in sectors such as agriculture, forestry, water resources, and others. Based on these findings, this study proposes a set of future measures aimed at facilitating China's efforts to reduce the income gap within the framework of the digital economy. These measures encompass expediting the integration of the digital economy with government governance and advocating for the widespread adoption of digital government affairs platforms. By implementing these measures, China can gain valuable insights into effectively addressing income inequality and promoting more equitable economic outcomes within the context of the digital economy.

Project description:ObjectivesThe number of modern healthcare providers in Bangladesh has increased and they are well equipped with modern medical instruments and infrastructures. Despite this development, patients seeking treatment from alternative healthcare providers are ongoing. Hence, this study aims to determine the underlying predictors of patients' choosing modern healthcare providers and health facilities for getting treatments.SettingData from the nationally representative Household Income and Expenditure Survey 2016-2017 conducted by the Bangladesh Bureau of Statistics were used.Participants34 512 respondents sought treatment for their illnesses from different types of available healthcare providers.Primary and secondary outcome measurePatients' choice of healthcare providers (primary) and predictors of patients' choice of modern healthcare providers (secondary).ResultsThe study found that 40% of the patients visit modern healthcare providers primarily on having symptoms of illness, and the remainder goes to alternative healthcare providers. Patients living in urban areas (adjusted OR (AOR)=1.11, 95% CI 1.05 to 1.17, p<0.01), and if the travel time was between 1 and 2 hours (AOR=1.11, 95% CI 1.00 to 1.22, p<0.05) compared with travel time less than 1 hour, were positively associated to utilisation of modern healthcare facilities for their first consultation. The statistical models show that the predisposing and need factors do not significantly impact patients' choice of modern healthcare providers.ConclusionsThe distribution of modern healthcare providers should be even across the country to eliminate the rural-urban divide in modern healthcare utilisation. Enhancing the digital provision of modern healthcare services could reduce travel time, omit transportation costs and save waiting time for treatment by the modern healthcare providers. Policymakers can think of introducing a national health insurance programme in Bangladesh as a potential policy instrument.

Project description:BackgroundGlobal health field assignments for medical and nursing professionals include a wide variety of opportunities. Many placements often involve individuals practicing in settings very different from their home environments, relying on their professional experience to help bridge cultural and clinical divides.ObjectivesThere is limited information about the individual factors that might lead to successful longer-term global health experiences in non-disaster settings. In this paper, we report on one cohort of health professionals' experiences of culture shock, stress, and resiliency as volunteers within the Global Health Service Partnership (GHSP), a public-private collaboration between Seed Global Health, the US Peace Corps, and the US Presidents Plan for Emergency Aids Relief (PEPFAR) that placed American medical and nursing educators in five African countries facing a shortage of health professionals.MethodsUsing the tools of Project PRIME (Psychosocial Response to International Medical Electives) as a basis, we created the GHSP Educator Support Survey to measure resiliency, stress, and culture shock levels in a cohort of GHSP volunteers during their year of service.FindingsIn our sample, participants were likely to experience lower levels of resiliency during initial quarters of global health placements compared to later timepoints. However, they were likely to experience similar stress and culture shock levels across quarters. Levels of preparedness and resources available, and medical needs in the community where the volunteer was placed played a role in the levels of resiliency, stress, and culture shock reported throughout the year.ConclusionThe GHSP Educator Support Survey represented a novel attempt to evaluate the longitudinal mental well-being of medical and nursing volunteers engaged in intense, long-term global health placements in high acuity, low resource clinical and teaching settings. Our findings highlight the need for additional research in this critical area of global health.

Project description:Introduction:The 2018 Astana Declaration reaffirmed global commitment to primary healthcare (PHC) as a core strategy to achieve universal health coverage. To meet this potential, PHC in low-income and middle-income countries (LMIC) needs to be strengthened, but research is lacking and fragmented. We conducted a scoping review of the recent literature to assess the state of research on PHC in LMIC and understand where future research is most needed. Methods:Guided by the Primary Healthcare Performance Initiative (PHCPI) conceptual framework, we conducted searches of the peer-reviewed literature on PHC in LMIC published between 2010 (the publication year of the last major review of PHC in LMIC) and 2017. We also conducted country-specific searches to understand performance trajectories in 14 high-performing countries identified in the previous review. Evidence highlights and gaps for each topic area of the PHCPI framework were extracted and summarised. Results:We retrieved 5219 articles, 207 of which met final inclusion criteria. Many PHC system inputs such as payment and workforce are well-studied. A number of emerging service delivery innovations have early evidence of success but lack evidence for how to scale more broadly. Community-based PHC systems with supportive governmental policies and financing structures (public and private) consistently promote better outcomes and equity. Among the 14 highlighted countries, most maintained or improved progress in the scope of services, quality, access and financial coverage of PHC during the review time period. Conclusion:Our findings revealed a heterogeneous focus of recent literature, with ample evidence for effective PHC policies, payment and other system inputs. More variability was seen in key areas of service delivery, underscoring a need for greater emphasis on implementation science and intervention testing. Future evaluations are needed on PHC system capacities and orientation toward social accountability, innovation, management and population health in order to achieve the promise of PHC.

Dataset Information

Resiliency of healthcare expenditure to income shock: Evidence from dynamic heterogeneous panels

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets