The pandemic of the SARS-CoV2 (COVID-19) that was declared by the World Health Organization (WHO) on 11 March 2020 is still ongoing. One of the early recommendations from CDC and other international agencies is the seasonal influenza vaccination to decrease the effects and burden of COVID-19 pandemic. This review suggests that during COVID-19 pandemic vaccination against seasonal influenza should be conducted all over the year, even for young age groups, because of several reasons. First, the complications of seasonal influenza, especially pneumonia, could increase the burden on the saturated healthcare systems worldwide. Second, the resemblance of symptoms and signs of both seasonal influenza and COVID-19 will difficult diagnosing and isolation of COVID-19 patients. Third, it has been postulated that there is a cross immunity between seasonal influenza and COVID-19.

Background: Oncology nurse navigators (ONNs) are becoming even more vital as healthcare continues to develop into a more complicated, confusing maze for patients. When many specialists on the treatment team have divergent points of view due to the nature of their respective professions or other factors, the patient may experience feelings of confusion. In the end, this can cause delays in treatment, pose a threat to the established standard of care, and lead to a decrease in patient satisfaction. Aim: To enumerate various ways in which ONNs may help improve the quality of life of cancer patients. Design: An integrative review. Results: A total of 19 studies related to the topic are evaluated. Four main themes namely: provider of psychological support, facilitator of timely care, oncology nurse navigators perception of their role and patient’s perception of oncology nurse navigators and 3 sub themes which are: information giver, source of emotional support and coordinator, were identified to be the roles of the ONNs. The findings showed that oncology nurse navigators help reduce patients anxiety and distress, increase patient satisfaction, shorten the time from diagnosis to treatment, provide necessary information, support them emotionally and coordinate their care with the different members of the healthcare team and resources. Conclusion: The main function of the ONNs is to address any barrier that may hinder the patient’s cancer treatment, survivorship and even palliative care. ONNs make sure that each patient has individualized nursing care according to the patients and their families' needs. Implications for Practice: ONNs have the potential to significantly contribute not only to the quality of life of cancer patients but also to the process of achieving better service integration. The result of this integrative review contributes to the growth of the healthcare system by improving accessibility, fairness, efficiency, effectiveness, and the ability to maintain health services throughout time brought about by ONNs.

This review aimed to analyze some problems and challenges that emerged from the COVID-19 pandemic since it has affected all global business sectors. During the pandemic, remote work was increased in response to social distance requirements to decrease the transmission of disease. In addition, increased delegation, teamwork, supply chains, sales activities, and business operations have all been disrupted. Many challenges have emerged in the management of organizations due to the pandemic including the lack of direct contact as the lockdown made many people work from home and placed restrictions on movement and travel and uncertainty about the future. The healthcare system was also affected by the COVID-19 pandemic and faced several difficulties including increased demand for medical supplies and personal protective equipment, a greater need for nurses and other skilled healthcare professionals, and increased pressure on healthcare facilities, emergency services, and critical care departments. These challenges have created some opportunities in the management systems of healthcare organizations and other sectors. It is recommended for leaders prepare and continuously work proactively to be ready for unexpected future crises. Risk management and planning for any unexpected situation are among the very important aspects of organizational management.

Background: Menthol-flavored tobacco products are disproportionately used in low-income African American communities, a result of decades of targeted marketing and systemic inequities. Menthol use has been associated with lower quit rates, often compounded by factors such as lower trust in healthcare systems, reduced access to cessation programs, and other structural barriers. Despite this, few studies have systematically examined the explanatory mechanisms that might clarify why menthol-flavored tobacco is linked to poorer cessation outcomes among participants in tobacco cessation programs. Aims: This study aimed to investigate the potential mechanisms by which menthol tobacco use is associated with lower quit rates across three types of smoking cessation interventions. Methods: Participants were randomized into one of three smoking cessation interventions: in-person (CEASE), self-help, or online/hybrid programs. Smoking abstinence was assessed three months post-intervention as the primary outcome. Secondary analyses explored whether demographic, socioeconomic, or behavioral factors mediated the association between menthol use and quit rates across the intervention arms. Results: Menthol tobacco use was significantly associated with lower quit rates (p < 0.01). This association was not explained by demographic, socioeconomic, health, or addiction-related factors. While menthol use was associated with lower education and employment levels, demographic characteristics, physical or mental health, or addiction did not explain the effect of menthol on tobacco cessation. These findings suggest that the lower quit rates observed among menthol users cannot be attributed to any third factors assessed in this study. Conclusions: Menthol tobacco use independently predicts lower quit rates, and the mechanisms behind this disparity remain unclear. The consistent findings across different intervention types highlight the need for further research to uncover the underlying pathways and to design targeted strategies to improve cessation outcomes for menthol users.

The pharmaceutical supply chain has become increasingly complex and vulnerable to various risks, including counterfeit drugs, diversion, and fraud. As these challenges threaten patient safety and the integrity of global healthcare systems, serialization has emerged as a pivotal innovation in pharmaceutical logistics and regulatory compliance. Serialization involves assigning unique identifiers to individual drug packages, enabling precise tracking and authentication at every stage of the supply chain. This process provides unprecedented transparency, enhances product security, and facilitates real-time monitoring of pharmaceutical products as they move from manufacturers to end consumers. Despite its potential to revolutionize pharmaceutical traceability, the integration of serialization technologies faces numerous obstacles. These include high implementation costs, regulatory inconsistencies across regions, and the technological challenges of managing vast amounts of data. Moreover, the complex, multi-tiered nature of the global supply chain introduces additional risks related to data integrity, cybersecurity, and interoperability between systems. As pharmaceutical companies seek to navigate these challenges, innovations in serialization technology—such as blockchain, artificial intelligence (AI), the Internet of Things (IoT), and radio frequency identification (RFID)—are providing promising solutions to enhance efficiency, reduce fraud, and increase visibility. This manuscript explores both the innovative advancements and the key challenges associated with the integration of serialization in the pharmaceutical supply chain. It delves into the evolving regulatory landscape, highlighting the need for global harmonization of serialization standards, and examines the impact of serialization on securing pharmaceutical distribution networks. Additionally, the paper emphasizes the importance of collaboration among manufacturers, technology providers, and regulatory bodies in overcoming implementation barriers and realizing the full potential of serialization. As the pharmaceutical industry moves towards a more interconnected and data-driven future, serialization promises to play a central role in shaping the next generation of drug safety and supply chain management. By addressing the hurdles to adoption and leveraging emerging technologies, the pharmaceutical sector can create a more secure, transparent, and efficient supply chain that better serves public health and fosters greater trust among consumers and healthcare professionals alike.

Digital therapeutics (DTx) are emerging as a pivotal tool in promoting longevity by addressing non-communicable diseases (NCDs) such as diabetes, cardiovascular diseases, and mental health disorders. These software-driven interventions offer personalized, evidence-based treatments that can be accessed via digital devices, making healthcare more accessible and scalable. One of the key advancements in DTx is the integration of artificial intelligence (AI) and machine learning (ML) to tailor interventions based on individual health data. This personalization enhances the effectiveness of treatments and supports preventive care by identifying risk factors early. The need for digital therapeutics is underscored by the rising prevalence of NCDs, which are responsible for a significant portion of global mortality and healthcare costs. Traditional healthcare systems often struggle to provide timely and personalized care, especially in low-resource settings. DTx can bridge this gap by offering cost-effective solutions that are easily scalable. Moreover, digital therapeutics can address health inequities by providing low-cost interventions to underserved populations, thereby reducing the burden of NCDs and improving overall health outcomes. As technology continues to evolve, the potential for DTx to enhance longevity and quality of life becomes increasingly promising. Recent advancements in longevity medicine and technology have focused on extending both lifespan and healthspan, ensuring that people not only live longer but also maintain good health throughout their extended years. This review article highlights these advancements that are contributing to this compelling subject of Longevity.

Drug shortages represent a significant and growing challenge within the pharmaceutical supply chain, with profound implications for patient care, public health, and healthcare costs. This manuscript provides a comprehensive examination of the causes and impacts of drug shortages, highlighting the multifaceted nature of this issue. Key factors contributing to shortages include manufacturing complications, limited availability of active pharmaceutical ingredients (APIs), market dynamics that discourage the production of less profitable medications, and regulatory challenges that slow down the approval process for new manufacturing capacities. The consequences of these shortages are far-reaching. Patients often face treatment delays, which can lead to adverse health outcomes, increased hospitalization rates, and even mortality. Healthcare providers experience heightened operational costs as they seek alternative therapies and manage complications resulting from inadequate treatment. Furthermore, the frequent occurrence of drug shortages erodes public trust in both the healthcare system and the pharmaceutical industry, leading to decreased patient adherence to prescribed therapies. To mitigate the impacts of drug shortages, this manuscript proposes several strategic solutions, including enhanced communication among stakeholders, diversification of supply sources, increased regulatory flexibility, and collaborative approaches between public and private sectors. Additionally, raising awareness among healthcare providers and patients regarding the causes and potential alternatives can empower stakeholders to navigate shortages effectively. Ultimately, addressing drug shortages necessitates a proactive and coordinated effort from all participants in the pharmaceutical supply chain. By implementing these strategies, stakeholders can enhance the resilience of the supply chain, ensuring that essential medications remain accessible and that patient care is not compromised. The findings of this manuscript underscore the urgent need for ongoing vigilance and collaborative action to tackle the challenges posed by drug shortages, safeguarding public health and improving healthcare outcomes globally.

The role of enterprise applications in pharmaceutical industries is driving the digital transformation of various critical processes, and one process benefiting from this innovation is pharmaceutical drug traceability. This industry grapples with challenges like a lack of transparency, difficulties in tracking products, a deficit of trust, and issues related to shipping expired products. To address these concerns, blockchain technology as an enterprise application has been harnessed as a solution. Notably, counterfeit drug prevention emerged as the most prevalent category, aligning with the pharmaceutical industry's primary objective. Blockchain technology is an emerging innovation that is finding enterprise applications in various industries, including healthcare. In the healthcare sector, Blockchain networks are being utilized to securely store and exchange patient data across hospitals, diagnostic laboratories, pharmacies, and medical practitioners. These enterprise applications can effectively identify and mitigate critical errors, including potentially hazardous ones within the realm of healthcare. Consequently, this enterprise technology holds the promise of enhancing the efficiency, security, and transparency of medical data sharing within the healthcare system. Moreover, it offers valuable tools for medical institutions to gain insights and improve the analysis of medical records. It visually represents the diverse capabilities, enablers, and the unified workflow process of Blockchain technology in supporting healthcare on a global scale. Additionally, the paper presents a thorough discussion of fourteen significant applications of Blockchain in healthcare, underscoring its pivotal role in addressing issues like deception in clinical trials.

Health professionals are the base of the healthcare systems in all societies. Their daily contact with the patient in a context of demanding and difficult working conditions affect their general health. This research was carried out to describe the levels of general health among health professionals and their perceived levels of fatigue and social support. Additionally, the purpose of this study was to examine the above three variables in relation to demographic (education, gender) and employment factors (working hours, department). The research was conducted in 165 health professionals working in hospitals in the region of Eastern Macedonia-Thrace and in the urban centers of Athens and Thessaloniki. The General Health Questionnaire (GHQ-28), the Fatigue Assessment Scale (FAS) as well as the Multidimensional Scale of Perceived Social Support (MSPSS) were used to measure the research variables. The processing and statistical analysis of the data was done using IBM SPSS. The majority of health professionals presented a high score in GHQ-28 subscales indicating low general health (avg 8.59≥5). One hundred thirty nine out of 165 health professionals (84%) were tired and 15 out of 165 (9%) were too tired. The perceived social support was at high levels (avg 5.57). Health professionals exhibit high fatigue and low levels of general health and quality of life. Instead, they receive high social support. Existence of circular hours and work in heavy part worsens the levels of fatigue and quality of life. Measures are needed to increase the number of health professionals and organizational and structural measures to improve their working conditions and strengthen their social work.

Digital therapeutics (DTx) is an evidence-based treatment that makes use of high-quality software. As many healthcare systems confront increasing expectations for quality results, the need for digital medications is steadily growing in the clinical arena. To ensure that patients are supported during chemotherapy and that needless hospital visits are avoided, digital therapeutics must be integrated into the cancer care pathway. Oncology patients are usually immunocompromised die to their disease and treatment, rendering them more susceptible to infection than the general population. As a result, visiting to a hospital might endanger their health. In addition, when cancer patients and survivors return home after treatment, digital health interventions provide them with the tools they need to manage their illness and its side effects in the privacy of their own homes. Considering the increasing prevalence of cancer patients and the solution that digital therapeutics has to offer in oncology, its future looks promising. This review article aims to summarize the existing companies in this domain, while evaluating the prospects as well.

Over the past few decades, cardiovascular disease and related complications have surpassed all others as the important causes of death on a universal scale. At the moment, they are the important cause of mortality universal, including in India. It is important to know how to find cardiovascular problems early so that patients get better care and prices go down. This project utilizes the UCI Heart Disease Dataset to develop ML and DL models capable of detecting cardiac diseases. Heart illness was categorized using Convolutional Neural Network (CNN) models, which are able to detect intricate patterns in supplied data. A confusion matrix rating, an F1-score, a ROC curve, accuracy, precision, and recall were some of the measures used to grade the model. It did much better than the Neural Network, Deep Neural Network (DNN), and Gradient Boosted Trees (GBT) models, with 91.71% accuracy, 88.88% precision, 82.75% memory, and 85.70% F1-score. Comparative study showed that CNN was the most accurate model. Other models had different balances between accuracy and recall. The experiment results show that the optional CNN model is a decent way to identify cardiovascular disease. This means that it could be used in healthcare systems to find diseases earlier and treat patients better.