Health Care Science最新文献

This study examines the UK's May 2023 judgment in an international organ trafficking and organ tourism case. Human trafficking for organ removal is one of the least understood but growing forms of trafficking worldwide. Countries in the Middle East, Asia, and the Americas are often widely criticized by the international transplant community as sites for organ trafficking. However, we believe that when discussing this issue, it is not just these areas that need to be addressed. What is particularly special is that this case not only involves transnational human trafficking, organ trafficking, and illegal organ transplantation interest chains but also involves the participation of national political officials and complex social and humanistic factors. This article focuses on the current ethical and policy issues involved in organ transplant tourism and organ trafficking and analyzes the implications of this case for our country's donation and transplantation work.

Noncommunicable diseases (NCDs) are a significant public concern, greatly impacting the economic and social development in China. In 2019, NCDs accounted for a staggering 88.5% of total deaths in China, with cardiovascular diseases, cancer, chronic respiratory diseases, and diabetes—the four major chronic diseases—contributing to a premature mortality rate of 16.5% [1]. The complexity of NCDs arises from the involvement of multiple genetic and environmental factors that interact in intricate ways. The complexity is characterized by a multitude of interactions among genes, proteins, and metabolic pathways throughout the various stages of life. Furthermore, these interactions demonstrate time-dependent specificity during the different phases of the life course. Prior research on the etiology of NCDs tended to focus on “specificity,” which overlooked the concept of “universality.” Studies are often conducted from one risk factor, one disease, or one dimension, leading to an insufficient understanding of NCD etiology and less than satisfactory outcomes in prevention and control efforts. Therefore, the aim of this review is to highlight and propose a new trend in NCD etiology research, considering the research focus and research methodology.

The relationships among NCDs are intricate, and patients often show distinct patterns of multiple diseases, reflecting population heterogeneity in comorbidity. The study of comorbidity patterns among populations affected by NCDs can offer valuable insights for developing effective prevention and management strategies. In a retrospective study by Jansana et al. [2] using electronic health records, five multimorbidity clusters were identified among breast cancer survivors in Spain; notably, the “musculoskeletal and cardiovascular disease” pattern showed a significantly higher risk of mortality than other NCDs. Advancements in computational science contribute to the emergence of network analysis based on graph theory as a powerful tool for understanding the complexity of comorbidity from a holistic and systemic perspective. Graph theory in network analysis facilitates the construction of comorbidity networks in which disease status is represented as nodes and risk associations are shown as edges, thereby visualizing the co-occurrence of diseases in a concise and intuitive manner. Such topological approaches enable the prioritization of disease severity and identification of the core disease within a comorbidity network. Furthermore, network clustering techniques have been applied to identify specific comorbidity patterns in NCDs. However, cautiousness in interpreting the identified patterns is essential because some network topology indexes may lack practical significance. The challenge in interpreting the identified patterns can be addressed by considering association rules. Typically, association rule mining is used to identify comorbidity patterns, and network analysis is used to

The purpose of the National Digital Health Mission (or more precisely, the Ayushman Bharat Digital Mission) is to promote and facilitate the evolution of the National Digital Health Ecosystem in India. The Health Facility Registry, the Healthcare Professionals Registry, and the Unified Health Interface are the major components of the proposed system—which is intended to be a co-operative federated architecture with optimal interoperability provision coupled with authorized access.

China's rapid population aging and remarkable family-level changes have raised concerns about the weakening of its family-based elderly care. The last decade indeed has seen a clear departure from multigenerational living to alternative living arrangements such as living with spouse only and solo living. However, ample evidence suggests that Chinese families have demonstrated considerable resilience amidst profound sociodemographic changes. This review article highlights the importance of government–society cooperation in meeting the social challenges of population aging. A key factor is the persistient filial piety norms, which enable children living far or close, migrant or nonmigrant, to rearrange financial, instrumental, and emotional support to aging parents. Equally important is the step-in of the government to share elderly care responsibilities, provide support through deepening pension and healthcare reforms, and implement the active and healthy aging agenda. How the two factors play out over the next decade and beyond will have profound implications on the living arrangement, intergenerational support, and wellbeing of older adults in China.

Data science is an interdisciplinary discipline that employs big data, machine learning algorithms, data mining techniques, and scientific methodologies to extract insights and information from massive amounts of structured and unstructured data. The healthcare industry constantly creates large, important databases on patient demographics, treatment plans, results of medical exams, insurance coverage, and more. The data that IoT (Internet of Things) devices collect is of interest to data scientists. Data science can help with the healthcare industry's massive amounts of disparate, structured, and unstructured data by processing, managing, analyzing, and integrating it. To get reliable findings from this data, proper management and analysis are essential. This article provides a comprehensive study and discussion of process data analysis as it pertains to healthcare applications. The article discusses the advantages and disadvantages of using big data analytics (BDA) in the medical industry. The insights offered by BDA, which can also aid in making strategic decisions, can assist the healthcare system.

The coronavirus disease (COVID-19), which the World Health Organization classified as the Sixth Public Health Emergency Of International Concern (PHEIC) on January 30, 2020, is no longer a PHEIC. Millions were affected due to unawareness. The increase in fatalities and shortage of medicine was the first outrage of COVID-19. As per the Johns Hopkins COVID-19 resource center database, it was observed that the disease has spread dynamically across 200+ nations worldwide affecting more than 600 million people from 2019 to 2023, and over thousands of people were victimized regularly at a 2% mortality rate (approx.). In the midway, the mutant variants of concern like omicron, and delta have also created havoc and caused significant impact on public health, global economy, and lifestyle. Since 2019, 3 years now passed and the dynamic disease statistics seem decelerated; moreover, the prevalence of COVID-19 is also fading. The Johns Hopkins resource center has also stopped recording the data of the global pandemic recently from March 10, 2023. Hence, based on the facts, we are presenting a concise report on the pandemic from 2019 to 2023, which includes a brief discussion of the global pandemic. We have highlighted global epidemiology, emphasizing the Indian COVID scenario, vaccination across the globe, and the psychosocial and geopolitical consequences of COVID-19 with a brief background to pathology, clinical management, and the worldwide response against triage. A lot has changed and still needs to change after three tough years of COVID-19. Even though science has progressed and advanced research in medicine is pointing toward future generations, there is no standard care supplied for COVID-19-like calamities. COVID-19 cases might have declined but its influence on the society is still stagnant. This COVID experience has taught us that, despite our bleak beginnings, there is always hope for the future and that we must act with foresight to improve things for future generations.