Robotic systems are increasingly being used in healthcare to improve patient care and support healthcare professionals. These robots are especially effective at performing repetitive tasks. In complex cancer cases, robots can enhance surgical precision and efficiency, resulting in reduced pain for patients and a lower risk of complications. Robot-assisted surgery offers high-quality 3D imaging, improved clarity, and increased efficiency. This review paper examines the application of Artificial Intelligence (AI) and robotic systems in the healthcare domain, specifically focusing on the interaction among operators, patients, and robots. The goal is to promote collaboration and improve healthcare provision through human-robot interaction. We considered already published articles by relevance, to identify the primary safety issues that need addressing for the integration of AI and robots in hospitals. Concluding with insights into understanding the focal points of social errors in Human-Robot Interaction (HRI) is crucial for mitigating these errors. While current technologies have reached a certain level of maturity, there are still numerous challenges in utilizing robot-assisted clinical practice, including technological, safety, clinical, financial, insurance, psychological, social, ethical, and legal issues. In addition, there is an urgent issue that needs to be addressed: the alignment of values in artificial intelligence, ensuring that AI systems reflect ethical principles and human values is crucial to avoid negative consequences such as bias, discrimination, and prejudicial decisions. Resolving this complex issue requires collaboration among clinical staff, researchers, programmers, and political decision-makers from various fields.

The role of Physician Assistant emerged in 1960s America and their number has increased to become a significant component of the health care workforce in that country. On the eve of a new policy regulating Physician Associates in the United Kingdom, the role of key actors in shaping the development of regulatory policies in the two countries is critically compared against a backdrop of very different political contexts and health care systems, to reveal the factors that might help or hinder the deployment of Physician Associates/Assistants and ameliorate workforce shortages.

Objectives: To analyse and detail surgical process improvement activities that achieve the highest economic impact. Methods: Over 4 years, a team of technicians and healthcare professionals implemented a set of Lean surgical process improvement projects at Vall d’Hebron University Hospital (VHUH), Barcelona, Spain. These projects now form part of the daily routine in the surgical process. The economic impact on the hospital's surgical activity budget was analysed. Results: Process improvements have led to annual operational savings of over € 8.5 million. These improvements include better patient flow, better management of information between healthcare professionals, and improved logistic circuits. Conclusions: The current cultural shift towards process management in large hospitals implies shifting towards results-based healthcare, patient-perceived value (VBHC) and value-added payment. A Lean project implementation process requires long-term stability. The reason a considerable number of projects fail to complete process improvement projects is the difficulty involved in establishing the project and improving management routines. Few studies in the literature have investigated the economic impact of implementing Lean management a posteriori, and even fewer have examined actual cases. In this real case study, changes to surgical block management were initiated from zero. After being carefully thought through and designed, changes were carried out and subsequently analysed.

Solid waste management is challenging in many countries, especially developing economies. The impacts of the pandemic continue to be felt and have indicated secondary impacts on waste management. This work draws on data on household solid waste (HSW), healthcare waste (HCW), and recyclables collected in the Rio de Janeiro municipality, analyzed from January 2018 to December 2022. As expected, the collection of HCW in Rio de Janeiro municipality experienced a noticeable increase in 2020 and 2021, with an average of 46.9 tons and 54.3 tons collected, respectively. Notably, 2021 saw a significant 30% increase compared to 2019 (p-value<0.001). No significant difference was observed in recyclables collected from 2018 to 2021. The average recyclable amount was 3,638 and 3,747 tons per month in 2020 and 2021. In contrast, the monthly amount was equal to 4,819.5 tons in 2022, representing an increase higher than 32% compared to previous years (p-value<0.05). Our findings can be used to adapt and improve waste systems to cope with similar emergency scenarios in the future, serving as a template for municipalities with similar challenges.

Background Healthcare workers (HCWs) have suffered considerable morbidity and mortality during the COVID-19 pandemic. Few data on COVID-19 vaccine effectiveness (VE) are available from middle-income countries in Europe. We evaluated primary series COVID-19 VE against laboratory-confirmed COVID-19 among HCWs in Georgia. Methods HCWs in six hospitals in Georgia were invited to enroll in a prospective cohort study conducted during March 19–December 5, 2021. Participants completed weekly symptom questionnaires. Symptomatic HCWs were tested by RT-PCR and/or rapid antigen test (RAT), and participants were routinely tested for SARS-CoV-2 by RT-PCR or RAT, regardless of symptoms. Serology was collected at enrolment, and quarterly thereafter, and tested by electrochemiluminescence immunoassay for SARS-CoV-2 antibodies. We defined primary series vaccination as two doses of COVID-19 vaccine received ≥14 days before symptom onset. We estimated VE as (1-hazard ratio)*100 using a Cox proportional hazards model with vaccination status as a time-varying covariate. Estimates were adjusted by potential confounders that changed the VE estimate by more than 5%, according to the change-in-estimate approach. Results Overall, 1561/3849 (41%) eligible HCWs enrolled and were included in the analysis. The median age was 40 (IQR: 30-53), 1318 (84%) were female, and 1003 (64%) had laboratory evidence of prior SARS-Cov-2 infection. At enrolment, 1300 (83%) were unvaccinated; By study end, 1082 (62%) had completed a primary vaccine series (69% BNT162b2 (Pfizer-BioNTech); 22% BBIBP-CorV (Sinopharm); 9% other). During the study period, 191(12%) participants had a new PCR- or RAT-confirmed symptomatic SARS-CoV-2 infection. VEa gainst PCR- or RAT- confirmed symptomatic SARS-CoV-2 infection was 58 (95%CI: 41; 70) for all primary series vaccinations, 68% (95%CI: 51; 79) for BNT162b2, and 40% (95%CI: 1; 64) for BBIBP-CorV vaccines. Among previously infected HCWs, VE was 58% (95%CI: 11; 80). VE against medically attended COVID-19 was 52% (95%CI: 28; 68), and VE against hospitalization was 69% (95% CI: 36; 85). During the period of predominant Delta variant circulation (July-December 2021), VE against symptomatic COVID-19 was 52% (95%CI: 30; 66). Conclusions Primary series vaccination with BNT162b2 and BBIBP-CorV was effective at preventing COVID-19 among HCWs, most of whom had previous infection, during a period of mainly Delta circulation. Our results support the utility of COVID-19 primary vaccine series, and the importance of increasing coverage, even among previously infected individuals.

Telemedicine has been increasingly considered an effective strategy to support patients with several diagnosis and therapies, avoiding the on-site visit and drastically reducing the risks to share infections. In the recent years, a number of different technologies have been developed and applied to clinical studies, with the aim to investigate new ways for increase the early diagnoses and monitor the clinical evolution of the most predictable diseases directly from the patients’ home. Telemedicine refers to all those technological interfaces used to remotely perform clinical procedures. Telemedicine applications could be useful in several medical fields, such as preventive medicine, home patient care, education for healthcare professionals and patients, research, public health, and health management. On the other hand, the synergy of these different technologies has a significant impact on the clinical risks analysis, particularly useful in frail patients. Although Telemedicine shows to have important advantages, undoubtedly important issues still remain. The present work aims to shed light on the main advantages and disadvantages related to of each application’s features, which may serve as a useful tool for researchers.

Healthcare workers have atypical working schedule and are exposed to experienced stress that led to poor sleep health and frequent mental complaints, particularly since the Covid-19 crisis. We conducted a cross-sectional study to determine the prevalence of poor sleep hygiene and mental complaints and their associations among healthcare workers. Usual sleep-wake timings were ex-plored during workdays and free days and used to compute sleep duration, sleep efficiency and social jetlag. Insomnia, sleepiness, anxiety and depressive symptoms, and fatigue were calculated using validated scales. A total of 1,562 participants were included (80.5% of women and mean age of 40.0). Among them, 25.9% slept less than 6 hours, 24.3% had a poor sleep efficiency, and 11.5% reported a social jetlag. A total of 33.9% of participants reported insomnia, 45.1% reported EDS, 13.1% reported fatigue, 16.5% reported depression and 35.7% reported anxiety. After ad-justment, sleep duration and sleep efficiency were associated with mental complaints. Social jetlag was associated with significant insomnia but not with anxiety or depression symptoms. Healthcare workers have a high prevalence of poor sleep hygiene and mental complaints. The promotion of sleep health through behavioral sleep strategies should be encouraged to ensure good health for these professionals.

This comprehensive review examines the critical issue of antimicrobial resistance (AMR), a growing global concern with profound societal implications. This article presents an overview of the causes of AMR, including the misuse and overuse of antibiotics in healthcare, agriculture, and veterinary practices. Various conventional and advanced detection methodologies have been explored, highlighting the importance of the accurate and timely identification of resistant strains. The challenges associated with tackling AMR, encompassing scientific, economic, and regulatory aspects have been discussed in depth. In addition, this article sheds light on the far-reaching societal implications of AMR, including increased healthcare costs, treatment complexities, and potential disruptions to healthcare systems. This emphasizes the urgency of adopting proactive strategies to combat AMR and underscores the need for global cooperation, policy interventions and public awareness campaigns. By unraveling the multifaceted dimensions of AMR, this review aims to enhance our understanding, stimulate further research, and promote concerted efforts to mitigate the threat of antimicrobial resistance.

The need for systemic healthcare policies to systematically eliminate NTDs globally and in India has been stressed for more than two decades. Yet, the present policies and the research on them do not meet the need. We present an ontological framework, a research roadmap, and a policy brief to address the gap. The ontology clearly, concisely, and comprehensively represents the combinations of diseases, the objectives regarding the diseases, the entities to address them, the outcomes sought, and the potential policy instruments to invoke. The paper explicates the state-of-the-policies and state-of-the-research on policies to eliminate NTDs in India. It highlights the significant gaps in both. Last, it presents a set of systemic policies congruent with the ontology to systematically address the gaps. The recommendations are aligned with the present research, policies, practices, and recommendations in India and of WHO, UN agencies, and other similar bodies. The approach can be generalized to provide roadmaps for other countries facing a similar challenge and for other diseases of similar complexity. The roadmaps, with continuous feedback and learning, can help navigate the challenge efficiently and effectively.

Introduction Prostate Cancer (PCa) exhibits one of the widest racial and socioeconomic disparities. PCa disparities have also been widely linked to location as living in more deprived regions was associated with lower healthcare access and worse outcomes. This study aims to examine PCa survival across various US counties in function of different socioeconomic profiles and discuss the role of potential intermediary factors. Methods The SEER database linked to county-level SES was utilized. Five-year PCa-specific survival using the Kaplan Meier method was performed for 5 racial/ethnic categories in function of SES quintiles. Multilevel Cox proportional hazards regression was performed to assess the relationship between county-level SES and PCa survival. Multivariate regression analysis was performed to examine the role of healthcare utilization and severity. Results 279,000 PCa records were extracted, 5-year PCa-specific survival was 94%. Overall, living in counties with worst poverty/income quintile and highest proportions of foreign-born/language-isolated increased PCa mortality by 23% each. No association was observed with county-level High-School education, while Bachelor’s-level education decreased mortality risk by 23%. Associations varied considerably upon racial/ethnic stratification. Multilevel analyses showed varying contributions of individual and area-level factors to survival within minorities. The relationship between SES and PCa survival appeared to be influenced by healthcare utilization and disease stage/grade. Discussion Racial/ethnic categories responded differently under similar county-level SES and individual-level factors to the point where disparities reversed in Hispanics. The inclusion of Healthcare utilization and severity factors may provide partial early support for their role as intermediaries. Healthcare access (insurance) might not necessarily be associated with better PCa survival, through performing biopsy and or/surgery. County-level education plays an important role in PCa decision-making as it might elucidate discussions of other non-invasive management options. Conclusion Findings of this study demonstrate that interventions need to be tailored according to each group's needs. This potentially informs the focus of public health efforts in terms of planning and prioritizing. This study could also direct further research delving into pathways between area-level characteristics with PCa survival.

Innovation development in healthcare has paved the path towards the improvement in system efficiency, patient care and cost-effective healthcare services, increasing the overall efficiency of the healthcare system in a significant manner. Electronic medical record system has fostered interoperability and collaboration in healthcare departments by enabling different systems to exchange and use patient data. This trend has been accelerated dominantly by the pandemic, leading to increased use of telemedicine, referring specifically to the use of electronic communication to provide healthcare services remotely. Moreover, an increased prevalence towards the use of artificial intelligence and machine learning in healthcare has contributed effectively towards the rigorous and informed analysis of large amounts of data as well as to identify patterns or trends that may be useful for improving care delivery or identifying potential issues. A unified electronic medical record System that will generate competitive opportunities and success prospects with reference to enhanced interoperability in US healthcare departments, can contribute towards the improvement in the quality and efficiency of care by making it easier for healthcare providers to access and share patient information as well as reducing the risk of errors in effective patient care.

An artificial intelligence (AI)-based conversational large language model (LLM) was launched in November 2022 namely, “ChatGPT”. Despite the wide array of potential applications of LLMs in healthcare education, research and practice, several valid concerns were raised. The current systematic review aimed to investigate the possible utility of ChatGPT and to highlight its limitations in healthcare education, research and practice. Using the PRIMSA guidelines, a systematic search was conducted to retrieve English records in PubMed/MEDLINE and Google Scholar under the term “ChatGPT”. Eligibility criteria included the published research or preprints of any type that discussed ChatGPT in the context of healthcare education, research and practice. A total of 280 records were identified, and following full screening, a total of 60 records were eligible for inclusion. Benefits/applications of ChatGPT were cited in 51/60 (85.0%) records with the most common being the utility in scientific writing followed by benefits in healthcare research (efficient analysis of massive datasets, code generation and rapid concise literature reviews besides utility in drug discovery and development). Benefits in healthcare practice included cost saving, documentation, personalized medicine and improved health literacy. Concerns/possible risks of ChatGPT use were expressed in 58/60 (96.7%) records with the most common being the ethical issues including the risk of bias, plagiarism, copyright issues, transparency issues, legal issues, lack of originality, incorrect responses, limited knowledge, and inaccurate citations. Despite the promising applications of ChatGPT which can result in paradigm shifts in healthcare education, research and practice, the embrace of this application should be done with extreme caution. Specific applications of ChatGPT in health education include the promising utility in personalized learning tools and shift towards more focus on critical thinking and problem-based learning. In healthcare practice, ChatGPT can be valuable for streamlining the workflow and refining personalized medicine. Saving time for the focus on experimental design and enhancing research equity and versatility are the benefits in scientific research. Regarding authorship in scientific articles, as it currently stands, ChatGPT does not qualify to be listed as an author unless the ICJME/COPE guidelines are revised and amended. An initiative involving all stakeholders involved in healthcare education, research and practice is urgently needed to set a code of ethics and conduct on the responsible practices involving ChatGPT among other LLMs.

Over the years, researchers have been developing different ventilation strategies as a potential solution for controlling infectious airborne transmissions in healthcare facilities. The effects of ventilation systems on airflow characteristics have been extensively discussed among researchers since SARS-CoV-2 outbreak in 2019. Based on a bibliometric study of 154 publications from 1970 to 2021 retrieved from the Web of Science (WoS) database, this paper examines the research landscape on the effects of ventilation strategies on airflow analysis in healthcare facilities. Results show that China is the most productive country due to its significant contributions to the top prolific authors and funding agencies, which have promoted the research development of the topic. Several research hotspots were identified through keyword co-occurrence analysis. Cluster 1 highlights the ventilation studies involving ventilation layouts and ventilation rates in healthcare facilities. Cluster 2 underlines the computational analysis of ventilation performance for reducing the exposure risk of occupants, which promotes the development of infection control measures. Cluster 3 strengthens the knowledge of the emission and dispersion characteristics of respiratory droplets in healthcare facilities. Overall, this paper highlights the future direction of the current research field other than identifying strategic collaborators and suitable publication outlets for interested researchers.

Patients satisfaction with fast and high-quality services is the most important in the healthcare settings and specially in outpatient departments and private clinics. High quality services on health sector are indicated by continuous quality improvement (CQI). CQI is a progressive incremental process focused on safety of all participants, outcomes, systematic process, regulated and improved working environment at the later than earlier stages. Among the various suggested strategies, we adopted the patents feedback to improve the quality of services our clinic. All of the patient visited hospital were sent a massage on mobile and requested to provide their feedback on our services. Roughly around 5% of all visitors responded and filled up questionnaire. Majority of them were satisfied with the services in various department. However, they provided us some suggestions to identify the further gaps and improve the services in improving patients experience at our clinic. We considered their feedback, identified problems, redesigned the policies and implemented. After implementation of new strategies, we preliminary again evaluated the patients’ feedback on our services. Patients feedback explores that optimized methods of services for the has considerably increased the patients’ satisfaction. Taken together, our this shows that patients’ feedback is very important factor to improve patients’ experience at outpatient clinics using continuous quality improvement tools. For that reason, this study would serve as reference for public health stack holders, administrators and researchers.

Background: Fluoride toothpaste (FT) has recently been included in the World Health Organization’s (WHO) Model List of Essential Medicines. Whereas it is essential for preventing dental caries, its current affordability around the globe remains unclear. This study aimed to analyse the affordability of FT in as many as possible countries worldwide. Methods: A standardized protocol was developed to collect country-specific information about the characteristics of the cheapest FT at a common point of purchase. 82 members of the WHO Global Oral Health Network of Chief Dental Officers (CDOs), directors of WHO Collaborative Centres and other oral health experts collected data using mobile phone technology. The Fluoride Toothpaste Affordability Ratio (FTAR) was calculated as the price associated with the recommended annual consumption of FT, relative to the daily wage of the lowest-paid unskilled government worker (FTAR >1 = unaffordable spending on fluoride toothpaste). The daily expenditure per capita of the poorest 15% of the income distrubition was used as the main proxy of the daily wage, using World Bank data. Alternatively, we used the daily minimum wage as a proxy of the daily wage. Stratified descriptive statistics were undertaken with respect to different World Bank Income Groups and WHO Regions. Results: There are significant discrepancies in the affordability of FT across 78 countries. FT was strongly affordable in high-income countries, relatively affordable in upper middle-income countries, and strongly unaffordable in lower middle-income and low-income countries. The affordability of FT across WHO Regions was dependent upon the economic mix of WHO Regions’ member states. Conclusion: FT is still unaffordable for many people, particularly in low-resource settings. Health policy members should develop better strategies to address and improve the universal affordability of FTs, for the incidence of dental caries to be reduced at a global level.

The need for miniaturized shear force sensors is expanding, particularly for biomedical applications. Examples include measuring interfacial shear stresses between a human and an external device (e.g., footwear or a prosthesis). However, there are considerable challenges in designing a shear sensor for these applications due to the need for a small package, low power requirements, and resistance to interference from motion artifact and electromagnetic fields. This paper presents the design, fabrication, and characterization sensor that measures two-axis shear force by detecting displacement between a color panel and a red, green, and blue light-sensing photodiode. The sensor response to applied displacements and forces was characterized under benchtop testing conditions. We also present the design of a prototype wireless version of the sensor for integration into footwear. The sensor exhibited strong agreement with gold standard measurements for two axis shear displacements (R2>0.99, RMSE≤5.0 µm) and forces (R2>0.99, RMSE≤0.94 N). This performance, along with the sensor’s scalability, miniaturized form, and low power requirements make it well-suited a variety of biomedical applications.

Pneumonia is the leading cause of hospitalization in pediatric patients. Disease severity greatly influences pneumonia progression and adverse health outcomes such as hospital readmission. Hospital readmissions have become a measure of healthcare quality to reduce excess expenditures. The aim of this study was to examine 30-day all-cause readmission rates and evaluate the association between pneumonia severity and readmission among pediatric pneumonia hospitalizations. Using 2018 Nationwide Readmissions Database (NRD), we conducted a cross-sectional study of pediatric hospitalizations for pneumonia. Pneumonia severity was defined by the presence of respiratory failure, sepsis, mechanical ventilation, dependence on long-term supplemental oxygen, and/or respiratory intubation. Outcomes of interest were 30-day all-cause readmission, length of stay, and cost. The rate of 30-day readmission for the total sample was 5.9%, 4.7% for non-severe pneumonia, and 8.7% for severe pneumonia (p&lt;0.01). Among those who were readmitted, hospitalizations for severe pneumonia had a longer length of stay (6.5 vs. 5.4 days, p&lt;0.01) and higher daily cost ($3,246 vs. $2,679, p&lt;0.01) than admissions for non-severe pneumonia. Factors associated with 30-day readmission were pneumonia severity, immunosuppressive conditions, length of stay, and hospital case volume. To reduce potentially preventable readmissions, clinical interventions to improve the disease course and hospital system interventions are necessary.

In personalized healthcare, an ecosystem for the manipulation of reliable and safe private data should be orchestrated. This paper describes a first approach for the generation of fake electrocardiograms (ECGs) based on Generative Adversarial Networks (GANs) with the objective of anonymizing users’ information for privacy issues. This is intended to create valuable data that can be used both, in educational and research areas, while avoiding the risk of a sensitive data leakage. As GANs are mainly exploited on images and video frames, we are proposing general raw data processing after transformation into an image, so it can be managed through a GAN, then decoded back to the original data domain. The feasibility of our transformation and processing hypothesis is primarily demonstrated. Next, from the proposed procedure, main drawbacks for each step in the procedure are addressed for the particular case of ECGs. Hence, a novel research pathway on health data anonymization using GANs is opened and further straightforward developments are expected.

COVID-19 has been a major issue in most countries throughout the world with 213 countries being affected till date due to the disease. The pandemic has raised concerns over the healthcare facilities available in various countries and question the government decisions made during this period of outbreak. Despite having the best healthcare facilities several countries across Europe and America have found it difficult to contain the disease outbreak questioning the available solutions to contain an area. This paper focuses on presenting information on solutions available to control outbreaks in order to prevent another pandemic occurring in the future. The paper also highlights the strategies and plans implemented by various governments who have been successful in combatting the disease with minimum damage. By using available resources such as technology, scientific innovation and digitalized healthcare this paper focuses on providing solutions which are already available to be utilized in the right manner.

This paper deals with the service performance analysis and improvement using discrete event simulation has been used. The simulation of the heath care has been done by arena master development 14-version software. The performance measurement for this study are patients output, service rate, service efficiency and it is directly related to waiting time of patients in each service station, work in progress, resource utilization.Simulation model was building for Bahir Dar clinic and then, prepared the proposed model for the system. Based on the simulation model run result, the output of the existing healthcare service system is low due to presence of bottlenecks on the service system. Moreover, the station with the largest queue and high resource utilization are identified as a bottleneck. The bottlenecks, which have identified are reduced by using reassigning the existing resources and add new resources and merging the similar services, which has under low resource utilization (nurses). Finally, the researchers have proposed a developed model from different scenarios. Moreover, the best scenario is developed by combining scenario 2 and 3. And then, service efficiency of the healthcare has increased by 9.86 percent, the work in progress (WIP) are reduced by 3 patients from the system and the service capacity of the system is increased 34 to 40 patients per day due to the reduction of bottleneck stations.

It is not new in medical history to propose a global concern to be classified as a disease. Defining a concern into disease allows to assign ethical responsibilities to develop powerful and effective interventions. It also allow to appropriate distribute the resources uniformly economically and morally. In 2003, World Health Organization report stated that 30-50 % of patients do not take their medications as prescribed associated with morbidity, mortality and health cost. It was considered a global concern, however, irrespective of decades of researches conducted on medication adherence, we are still unable to state that medication adherence issues are being resolved. In this review, we have described few apprehensions in current understandings of medication adherence that have limited its research. We have also proposed medication adherence as disorder and provided its’ definition and classification

Background: Healthcare attention is sometimes considered purely technical, but communication has proven to be closely related to clinical results and patient satisfaction. Therefore, evaluation of communication in the scope of healthcare is a priority. The purpose of this study was to validate and adapt, if necessary, the Spanish version of the Communication Styles Inventory (CSI) in a sample of nursing professionals. (2) Methods: The sample was made up of 2313 nursing professionals selected at random from various medical centers in Spain, and is therefore a sample actively employed at the time data were acquired. We started out from the Communication Style Inventory, a questionnaire for evaluating the predominance of certain individual communication behaviors on six scales (expressiveness, preciseness, verbal aggressiveness, questioningness, emotionality and impression manipulativeness). (3) Results: Confirmatory Factor Analysis of the model proposed showed god fit indices. The reliability of the model shown by the Cronbach’s alpha of α=.81 was adequate, and so was single-level and aggregate consistency. Finally, in the analysis of variance by type of contract, configural, metric and scalar invariance was acceptable, but not strict invariance. (4) Conclusions: This instrument progresses in measuring non-technical attributes, such as communication styles, in nursing personnel.

In hospitals and smart nursing homes, ambient-intelligent care rooms are equipped with many sensors. They can monitor environmental and body parameters, and detect wearable devices of patients and nurses. Hence, they continuously produce data streams. This offers the opportunity to collect, integrate and interpret this data in a context-aware manner, with a focus on reactivity and autonomy. However, doing this in real-time on huge data streams is a challenging task. In this context, cascading reasoning is an emerging research approach that exploits the trade-off between reasoning complexity and data velocity by constructing a processing hierarchy of reasoners. Therefore, a cascading reasoning framework is proposed in this paper. A generic architecture is presented allowing to create a pipeline of reasoning components hosted locally, in the edge of the network, and in the cloud. The architecture is implemented on a pervasive health use case, where medically diagnosed patients are constantly monitored, and alarming situations can be detected and reacted upon in a context-aware manner. A performance evaluation shows that the total system latency is mostly lower than 5 seconds, allowing for responsive intervention by a nurse in alarming situations. Using the evaluation results, the benefits of cascading reasoning for healthcare are analyzed.

In service economy, scholars and practitioners focus on the development and the appliance of innovative services. The importance of service innovation is rising in many sectors and among different organizations. Several disciplines (e.g. marketing, management, operations research, etc.) focus on this innovation, a concept widely used, but with different definitions. In this paper, service innovation has been analyzed according to SD Logic and a service ecosystem perspective. Literature still call for a deeper understanding of how new or renewed resources’ combination affect the shaping of service ecosystems. To contribute to fill this gap, the study explores the practices that different actors, internal and external to a healthcare service ecosystem, enact to co-create value in novel ways that is service innovation. The paper is structured as follows. In the next section, the main academic contributions on service research have been reviewed, focusing on healthcare service innovation. Follows, the research method and the discussion of research findings. Finally, theoretical and managerial implications have been detailed and an agenda for future research suggested. The paper offers interesting insights to develop new or renewed practices that foster the reshaping and maintaining of a healthcare service ecosystem. Some recommendations are included to support managers in the development of service innovation strategies.

Approximately 10–20% of individuals suffering from COVID-19 develop prolonged symptoms known as long COVID or post-COVID condition (LC). This review aimed to assess healthcare resource use (HCRU) and healthcare costs associated with LC. Because LC is not clearly defined and often remains undiagnosed, studies reporting on long-term follow-up of individuals with a COVID-19 diagnosis were also included. Among the 41 publications included, 36 reported on HCRU and 16 on costs. Individuals with LC had significantly elevated HCRU and healthcare cost vs controls without a COVID-19 diagnosis over ≥15 months, with a 7.6%–13.1% increase in total healthcare costs per person per month as assessed by difference-in-difference analysis. Among studies that did not specifically refer to LC, having a COVID-19 diagnosis was associated with a significant 4–10% increase in long-term total HCRU over 6–8 months and a 1.3- to 2.9-fold relative increase in total healthcare costs over 6 months. Due to the heterogeneity of included studies, high-quality evidence is needed to better understand the economic burden of LC. In the absence of effective treatments, prioritizing prevention of acute COVID-19, e.g., through vaccination, may be crucial for preventing LC and the associated long-term HCRU and medical spending.

Populations with healthcare needs often reside in post-conflict settings where basic services needed to maintain good health may be non-existent or hard to access. Therefore, there is a need for better identification and reallocation of resources as part of the post-conflict health rehabilitation effort. This study applies an asset-based approach to explore the more optimal design of health services and to identify the resource constraints for basic health service delivery to the most vulnerable communities in eastern Congo. We implemented the asset mapping in two phases. Firstly, we combined a qualitative survey with community walks to identify the assets already present in the communities. Secondly, we conducted group discussions to map out assets that are the core of Asset-Based Community Development (ABCD) practice. We finally documented all assets in a Community Asset Spreadsheet. Overall, 209 assets were identified as available and potentially valuable resources for the communities in eastern Congo. Among them, 60 were local associations, 24 were land and physical environment, 43 were local institutions, 46 were individuals, 32 to economy and exchange, and only 6 were related to culture, history, and stories. Drawing upon the findings from the qualitative survey, community walks, and group discussions, we conclude that an important number of resources were in place for basic health service delivery. By activating the existing and potential resources, the most vulnerable populations in eastern Congo might have the required resources for basic health service delivery. Our findings support the use of an asset-mapping research method as appropriate to identify existing and potential resources for basic health services in a post-conflict setting.

With increased life expectancy and improved modern lifestyles, there has been a growing concern for health, including the prevention of disease and the improvement of physical appearance. Consumers are increasingly aware of the benefits of using natural ingredients in healthcare products and at the same time are concerned about the challenges of sustainability. In this sense, the use of marine bioactive compounds as cosmetic ingredients and in food supplements has become increasingly popular due to the benefits derived from their various properties. However, some of these compounds have limited use, mainly due to their low stability and poor aqueous solubility, and solutions need to be developed to overcome these limitations. In this sense, the use of lipid nanoparticles, such as solid lipid nanoparticles (SLN) and nanostructured lipid carriers (NLC), has been explored as these carriers show ability to protect and enhance the absorption of molecules. Several studies have demonstrated the efficacy of encapsulating these compounds and incorporating them into cosmetics and food supplements. However, there is still no global legislation and safety concerns have been raised. Further clinical studies in animals and humans are needed to clarify safety issues.

This study aims to comprehensively understand the provision of skincare solutions for individuals living with HIV, focusing on the efficacy of existing treatments, challenges in accessing dermatological care, and the preferences of individuals living with HIV for personalized skincare solutions. The study triangulated data from structured surveys and in-depth interviews with a purposive sample of individuals living with HIV, healthcare professionals, and experts in public health and social work, using a mixed-methods approach. The structured surveys provided specific data points, while the in-depth interviews and participant observations yielded rich, contextual insights. The results revealed a need for more personalized skincare solutions for individuals living with HIV, challenges in accessing dermatological care, and concerns regarding the efficacy of existing treatments. The integrated analysis of quantitative and qualitative data provided a nuanced understanding of the factors influencing skincare solutions for this population. Conclusions drawn from the study emphasize the importance of tailored skincare interventions, improved access to dermatological care, and the need for collaborative efforts between healthcare providers and individuals living with HIV. Future research directions include longitudinal studies to assess the long-term effectiveness of personalized skincare solutions and the exploration of innovative interventions integrating dermatological care and social support for individuals living with HIV.

Preventing COVID-19 in Gaza is crucial due to the devastation of advanced health services infrastructure by war. Despite the high protection offered by COVID-19 vaccines against severe disease, a 2021 survey in Gaza found only half of the population vaccinated and one-third vaccine hesitant. This follow-up study conducted in March 2023 aimed to re-evaluate vaccination levels, hesitancy, exposure to vaccine promotion efforts, and other risk factors in Gaza. A community-based cross-sectional survey with multistage stratified sampling was used. Associations of primary exposures and other determinants with vaccine status and hesitancy were quantified using bivariate and multivariate logistic regression. In 2023, 63.5% of adults received at least one vaccine dose compared to 49.1% in 2021. Vaccine hesitancy prevalence was 31.7% in 2023 versus 34.1% in 2021 (p=0.395). Adjusted odds of vaccination were 4.2 times higher among those referred by health workers compared to those not referred. Adjusted odds of vaccine hesitancy among those who received information on the vaccine from health workers were 0.3 times that of people who did not receive information. Results suggest health workers could play a crucial role in future vaccination strategies, as their vaccine promotion efforts were linked to better vaccine outcomes. Investing in the skills development of community health workers to contribute to these efforts is recommended.

Additive Manufacturing (AM), commonly known as 3D printing, has revolutionized various industries, including the medical field. This technology enables the creation of complex structures layer by layer, offering unprecedented customization and precision. In medical applications, AM has proven transformative in producing patient-specific implants, prosthetics, and anatomical models, facilitating better surgical planning and outcomes. Additionally, it has shown promise in bioprinting, where cells and biomaterials are used to create tissue-like structures for regenerative medicine. The ability to rapidly prototype and manufacture medical devices reduces time and costs, and enhances personalized patient care. This abstract explores the diverse applications, benefits, and challenges of AM in the medical sector, highlighting its potential to revolutionize healthcare and improve patient outcomes.

The fulfillment of rights to maternal healthcare is a key factor for wellbeing of woman. However, there is a lack of instrument to know the experience of women during maternity to bind the monitoring. The aim of this study was to validate an instrument to measure the woman’s perception of the fulfillment of rights during healthcare in pregnancy, childbirth and immediate postpartum. The instrument consist in 50 items was screening by an exploratory factor analysis. Additionally, the final version of the instrument consists in 29 items which was validate by confirmatory factor analysis and know-group validity. The instrument was applied in 185 Spanish women. The global Aiken’s V of initial instrument proposal was 0.89. Process resolves an instrument with 5 factors (information, privacy, consent, support, and participation) that explained the 60% of the total variance. The score of the instrument was correlated with resilience, maternity beliefs, and positive and negative affect. External validation showed relations with age, gravida, and number of labors. Additionally, the reliability Cronbach´s was 0.93 [0.91; 0.94]. In conclusion, the instrument developed is consistent and has appropriate psychometric properties for assess the fulfillment rights maternity healthcare.

This study addresses a gap in literature by comprehensively analyzing the emotional well-being of healthcare workers. Methods: The study employed an analytical cross-sectional design utilizing both qualitative and quantitative methodologies among 84 healthcare workers. Quantitative data was analyzed using STATA version 17 while qualitative data was analyzed using thematic analysis. Ethical approval was sought from the University of Livingstonia Research Ethics Committee (UNILIA-REC). Results: 88% of the participants had experienced verbal abuse; stress and anger, 87% emotional tiredness, 22% depression, and 4% physical abuse. Emotional tiredness was associated with department (p=0.004) and work demand (p=0.0047), stress and anger were associated with experience (p=0.033), department (p=0.002) and work demand (p=0.002), depression was associated with age (p=0.035), experience (p=0.025), cadre (p=0.046), staffing (p=0.005) and work demand(p=0.044), verbal abuse was associated with department (p=0.035) and physical abuse was associated with knowledge of policies (p=0.002). Being aware of emotions and controlling them was the common coping strategy used by most (26%) of the respondents. The study established that most (78%) of healthcare workers did not receive formal training on coping skills for emotional disturbances. Conclusions: Healthcare workers experience some emotional disturbances within their professional roles. There is a need for healthcare workers to be trained on how to cope with emotional disturbances.

Antimicrobial resistance (AMR) is a major public health threat linked to increased morbidity and mortality. It has the potential to return us to the pre-antibiotic era. Antimicrobial stewardship (AMS) programs are recognized as a key intervention to improve antimicrobial use and combat AMR. However, implementation of AMS programs remains limited in Africa, particularly in Rwanda. This qualitative study, conducted at King Faisal Hospital (KFH) in Rwanda, aimed at assessing current prescription practices to identify areas for improvement and promote adherence to AMS principles. The interviews were recorded, transcribed, and thematically analyzed, revealing four emerging themes. First, emerged on AMS activities that were working well which includes availability of microbiology laboratory results, and prescription guidelines as factors influencing antibiotic prescription adjustments. Second, Implementations challenges to AMS which identified the prescription of broad-spectrum antibiotics, limited local data on AMR patterns, stock-outs of essential antibiotics, Thirdly, the importance of adhering to AMR management guidelines at KFH was underscored. Lastly, participant recommendations centered on regular training for healthcare workers, widespread dissemination of AMR findings across departments, and the enforcement of antibiotic restriction policies. These actions can improve prescription behaviors, upholding the highest standards of patient care, and strengthening the nascent AMS program.

In areas like commercial and policy decisions—it's important to know how different treatments affect things and how well they work. However, treatments affect things on average—but now—with fancy computer methods and big sets of data, interest lies in figuring out how treatments might work differently for different people. For instance, let's say instead of just looking at what works for most people, researchers want to know which treatment is best for each person. This would help doctors to decide the right treatment for each patient. This idea isn't just for healthcare—it can help in other areas too, like deciding how to govern employees or making government policies. There are some ways people have been trying to do this already, but they struggle when there are lots of different factors to consider. New computer methods, though, are good at handling lots of factors, but they need a ton of data to work well. Therefore, this study looks at three computer methods that are—Virtual Twin Random Forest (VTRF), Causal Forest (CF), and Causal Net (CN) using real-world data about encouraging people to do manual labour. One problem this study is trying to solve is something called the "winner's curse", where a treatment might seem better than it really is because of how it's predicted by the computer. We are also testing some ideas to see if we can fix this problem and make the predictions more accurate.

Background Praziquantel is the commonly used conventional treatment recommended for schistosomiasis in the mainstream healthcare system. Although Praziquantel may be free in healthcare facilities, many individuals may resort to the use of traditional medicine. This study aimed to assess perceptions of participants on the availability of Praziquantel and to ascertain whether individuals infected with schistosomiasis used concurrently African traditional medicines with this treatment. Methods A cross–sectional descriptive study, using face-to-face interviews, was conducted from January to April 2023 among healthcare workers (HCWs) and patients. A review of medical chart records of patients was further carried out to triangulate the information from interviews. Ddescriptive statistics including frequency and percentage were used; categorical data were represented as tables. Chi-squared tests were performed for the association between continuous variables. A p value ≤ 0.05 was estimated as statistically significant. Results Most of HCWs (114/124; 91.9%) reported that Praziquantel was available in healthcare facilities. Majority of HCWs (76/124; 61.3%) did not know whether patients seen by them used concurrently traditional medicine and Praziquantel for schistosomiasis. There was no significant relationship between the availability of Praziquantel and the concurrent use of TM by patients for schistosomiasis (X2 = 3.042, p = 0.551). Patients seen by THPs (8/20, 40%) did not use Praziquantel for schistosomiasis. Those patients (8/15, 53.3%) who crossed from TM to the mainstream healthcare system did not disclose their use of TM to HCWs. Their main reason was that concurrent use of TM and Praziquantel could destroy organs or make Praziquantel not to work properly. None of the medical chart records analysed documented the concurrent use of TM and Praziquantel. Conclusion Most of HCWs were not aware of the concurrent use of TM and Praziquantel by patients for the treatment of schistosomiasis. Patients seen by THPs relied solely on TM for schistosomiasis. Although patients indicated crossing from TM to the mainstream healthcare system, there was no evidence of documented use of TM in medical chart records of patients. Further studies are needed to contribute to the knowledge of medicinal plants used by THPs for schistosomiasis.

To study the spatial accessibility of healthcare services in cities on the Tibetan Plateau, this paper proposes an improved 3SFCA method in the main urban area of Xining City. The improved 3SFCA method incorporates both selection weights from the Huff model and the M2SFCA approach to addressing suboptimal allocation of supply resources. Results show that the accessibility of healthcare for the main urban area of Xining City decreases in a circle to four axes, with good accessibility in the east and center but poor accessibility in the north. And there is a positive spatial relationship between population and accessibility. Besides, this paper proposes a framework for studying the spatial accessibility of healthcare on the Tibetan Plateau.

Background: The COVID-19 pandemic has affected Madagascar, Cameroon, and the Central African Republic (CAR), with each experiencing multiple waves by mid-2022. This study aimed to evaluate immunity against SARS-CoV-2 strains Wuhan (W) and BA.2 (BA.2) among healthcare workers (HCWs) in these countries, focusing on vaccination and natural infection effects. Methods: HCWs' serum samples were analyzed for neutralizing antibodies (nAbs) against W and BA.2 variants, with statistical analyses comparing responses between countries and vaccination statuses. Results: Madagascar showed significantly higher nAb titers against both strains compared to CAR and Cameroon. Vaccination notably increased nAb levels against W by 2.6-fold in CAR and 1.8-fold in Madagascar, and against BA.2 by 1.6-fold in Madagascar and 1.5-fold in CAR. However, in Cameroon, there was no significant difference in nAb levels between vaccinated and unvaccinated groups. Conclusion: The study highlights the complex relationship between natural and vaccine-induced immunity, emphasizing the importance of assessing immunity in regions with varied epidemic experiences and low vaccination rates.

Fall detection systems play a crucial role in addressing the significant health concern of elderly falls, a leading cause of health deterioration and mortality. As the aging population grows and life expectancy increases, the development of accessible tools becomes vital for predicting and preventing falls, offering a practical and widely applicable solution in contrast to costly and expertise-dependent assessment tools. In contrast, due to the formidable challenges encountered, a comprehensive investigation into the comparative performance of standard ML models within this field still needs to be explored. This paper proposes a standard pipeline for pre-processing, training, and evaluating ML models for fall detection on the SisFall dataset. We conducted extensive experiments to evaluate the performance of various ML models for fall detection. The results validate the efficiency of the deep model in identifying the time windows in which a fall occurred. Among the deep models, the architecture, including a combination of convolutional neural networks and fully connected layers, outperforms the others by macro-averaged Precision, macro-averaged Recall, and macro-averaged F1-Score of 87.03\%, 86.83\%, and 86.93\%, respectively.

The coronavirus (COVID-19) pandemic limitations may negatively affect children and youth in terms of health behaviors, and it might be especially challenging for children who are diagnosed with neurodevelopmental disorders such as children and youth diagnosed with Autism Spectrum Disorder (ASD). The present study assessed alterations in physical activity, screen time, and sleep duration of ASD children and the prevalence of meeting the 24-hour movement guidelines during the COVID-19 outbreak. Forty-six Arab Israeli mothers of children with ASD were surveyed by an online cross-sectional survey. As reported by the mothers, the results show a significant decrease in physical activity, a significant increase in screen time, and a significant increase in sleep duration during the COVID-19 pandemic. Moreover, the proportion of the sample who gained the physical activity and screen time recommendations lessened while the percentage of children who met the sleep duration guidelines increased. The prevalence of ASD children who achieved the overall 24-hour movement guidelines was very small during the COVID-19 outbreak. The outcomes extend the body of knowledge regarding the negative effects of the COVID-19 pandemic on children diagnosed with neurodevelopmental disorders and highlight the need for instant healthcare and interventions and programs for children with ASD.

In the present study, we aimed to assess the prevalence and the relationships between alexithymia, burnout and hopelessness in a large sample of healthcare workers (HCWs) during the third wave of Covid-19 in Italy. Alexithymia was evaluated by the Italian version of the 20-item Toronto Alexithymia Scale (TAS-20), hopelessness was measured using the Beck Hopelessness Scale (BHS) and irritability (IRR), depression (DEP) and anxiety (ANX) were evaluated with the Italian version of Irritability‚ Depression‚ Anxiety Scale (IDA). This cross-sectional study recruited a sample of 1445 HCWs from a large urban healthcare facility in Italy from 1 June—31 May 2021. Comparison between individuals positive (n=214, 14.8%) or not for alexithymia (n=1231, 85.2%) controlling for age, gender and working seniority revealed that positive subjects showed higher scores on BHS, MBI, IRR, DEP and ANX than not positive ones (p<0.001). In the linear regression model, higher working seniority and higher MBI, DEP, ANX and TAS-20 scores were associated with higher hopelessness. In conclusion, increased hopelessness was associated with higher burnout and alexithymia. Comprehensive strategies should be implemented to support HCWs mental health and mitigate the negative consequences of alexithymia, burnout, and hopelessness

University students, particularly those in the healthcare disciplines, constitute a category of particular interest in regard to COVID-19 vaccines and the attitudes to vaccination, as their future professional role will enable them to inform and educate citizens regarding vaccination. The objectives of the study were to investigate the vaccination coverage with a COVID-19 vaccine among students from different degree programs at the Medical universities in Bulgaria behaviors and attitudes toward vaccination with a COVID-19 vaccine. A prospective cross-sectional study in the period September 2021- March 2022 was conducted. Information on demographics, university program, year of study, general attitudes and behavior towards vaccines and attitudes and personal experience with COVID-19 and COVID-19 vaccines were collected. The chi-square test was used to test for associations and binominal logistic regression was used to identify possible predictors for vaccination. A total of 3050 students with a median age of 22 years, predominantly female took part in the study. Three-thirds of the students (73.5%) have been vaccinated against COVID-19. The main reasons for vaccine hesitancy in both group of students were the fear of side effects and the doubts about the safety of the vaccines although non-vaccinated students significantly more frequently express those fears. Respondents who considered to have: a) limited access to sufficient information to inform COVID-19 vaccine uptake; b) lack of public awareness and education campaigns about effectiveness and safety of COVID-19 vaccines; c) insufficient information about COVID-19 vaccines during the University education; and d) had a positive COVID-19 diagnosis were less likely to be vaccinated. Students who have not completed the mandatory immunization cycle according to country schedule were also less likely to have completed COVID-19 vaccination. The students showed an overall positive attitude towards the COVID-19 vaccines. Promoting informational campaigns that emphasize the vaccine's safety will be more effective to further increase the vaccination coverage with COVID-19 vaccines.

Background: Fungi are ubiquitous microorganisms that are easily dispersed through the air. In healthcare environments, indoor air can favor the spread of healthcare-associated fungal infections, compromising mainly immunocompromised hospitalized individuals. Thus, this study aimed to evaluate the indoor air contamination in healthcare environments, investigating mainly the presence of potentially pathogenic yeasts. Methods: Indoor air samples were collected from twelve healthcare environments (hospital and medical clinics). After the growth, isolation, and purification of the yeast colonies, the isolates were identified by polymerase chain reaction using species-specific primers for yeasts of the genus Candida and sequencing of D1/D2 domains of the large ribosomal subunit (LSU rRNA). Results: Fourteen yeast species were identified, including emerging pathogens. Species of clinical importance such as Candida parapsilosis, Candida orthopsilosis, Candida glabrata, Rhodotorula mucilaginosa, and Trichosporon mucoides were present. C. Parapsilosis was the most prevalent species, followed by Rodothorula mucilaginosa. Conclusions: The present study shows that potentially fungal pathogens were present in air samples from healthcare environments, proving the role of indoor air in spreading infections. Thus, monitoring air quality in healthcare environments is a fundamental approach in developing infection control measures, especially those related to invasive fungal infections.

High-fidelity patient simulation (HFPS) is widely used in professional training to enhance students’ competence in clinical management. Problem-solving (PS) and clinical reasoning (CR) skills are essential to developing students in professional competence in safe and effective care. These two skills should be initiated at the early training. However, little is known about the effects of HFPS on developing PS and CR skills in first year undergraduate students. Therefore, this pre- and post-experimental study aimed to investigate the effects of HFPS on development of PS and CR skills in first-year nursing students. The students were required to go through four sessions, preparation, pre-briefing and orientation, simulation role-playing, and debriefing, for the HFPS. The study utilized the Problem-Solving Inventory (PSI) and the Nurses Clinical Reasoning Scale (NCRS) to measure problem-solving and clinical reasoning abilities before and after HFPS. Bivariate analysis, one-sample t-test, and independent t-test were performed to evaluate the performance of the PS and CR skills at the two study periods. One hundred eighty-nine students were recruited, with a mean age of 20.56 years, and 73% were female students. The analytic results showed that the PSI, particularly in domains of Problem-Solving Confidence (PSC) (p&lt;0.001) and overall PS (p&lt;0.001), and the CR (p&lt;0.001) had significant improvement after HFPS. The study concluded that HFPS is an effective innovative method to significantly improve students’ problem-solving and clinical reasoning abilities. Nurse educators play an important role in providing explicit learning instructions in a simulation guideline that directs and guides students to learn at each stage of HFPS. Students should take more initiative and engage in their learning through HFPS to enhance their competence in knowledge and higher intellectual skills for personal and professional developments.

The aim of this study was to investigate the work engagement and burnout in healthcare professionals in a private health unit in Greece. A cross-sectional study was conducted with a sample of 151 professionals (doctors, nurses, administrative staff and professionals of other specialties). The questionnaire included demographic and work-related information and the Utrecht Work Engagement Scale and Maslach Burnout Inventory. Analysis was performed by SPSS v.26. With regard to the work engagement, the participants presented a medium score in absorption and a medium to high score in vigor and dedication. In addition, they presented low score in depersonalization, a medium score in emotional exhaustion and a high score in personal accomplishment. Those who had a working contract for an indefinite period had higher score in all the dimensions of burnout. Vigor, dedication and absorption were negatively correlated with emotional exhaustion and depersonalization and positively with personal accomplishment. Healthcare professionals in private health sector in Greece present moderate work engagement and experience moderate levels of burnout. Work engagement is associated with burnout and plays an important role in its prevention. There are some significant differences in work engagement and burnout based on several demographic and work-related characteristics.

Background: The diagnosis of phenylketonuria (PKU) in an infant is a devastating and overwhelming event for their parents. Providing appropriate information and support is paramount, especially at the beginning of a child’s life. Investigating if parents are receiving the right support is important for their continued care. Methodology: An online survey was distributed to explore parents’ perceptions of current support and information provided by their healthcare provider and to rate sources of other support (n=169 participants). Results: Dietitians received the highest (85%) rate of “very helpful” support. Overall, parents found Facebook to be helpful for support, but had mixed reactions when asked if healthcare professionals (HCPs) should provide advice as part of the groups. When rating the most effective learning methods, the top three were: 1:1 sessions (n=109, 70%), picture books (n=73, 50%) and written handouts (n=70, 46%). Conclusion: Most parents were happy with the support and information they received from their dietitian, but required more support from other HCPs. Facebook groups provide parents with the social support that HCPs and their family may be unable to offer, suggesting a place for social media in future PKU care.

Access to healthcare services is an essential component of promoting public health and sustainable development. Our aim was to assess socio-demographic correlates of barriers to access healthcare services among children in Albania, a post-communist country in Europe. An online survey was conducted in September 2022, including a nationwide representative sample of 7831 schoolchildren (≈54% girls) pertinent to grades 6-9 from all regions of Albania. A structured and anonymous questionnaire was administered to all children inquiring about a range of potential barriers to access healthcare services. Overall, about 42% of the children reported that they had barriers to access healthcare services. There were no gender differences, but significant: ethnic differences (51% among Roma/Egyptian children vs. 42% among the general sample of the children); urban/rural differences (46% rural vs. 39% urban); and socioeconomic differences (52% among children with a lower maternal education vs. 31% among children with a higher maternal education; 66% among children from poor families vs. 35% among children with a higher family income). In transitional Albania, children residing in rural areas, children from Roma and/or Egyptian communities and especially those pertinent to low socioeconomic families report considerably more barriers to access healthcare services, which is a cause of concern.

Vaccination attitudes among healthcare workers (HCWs) is a vital factor for measuring their level of vaccination uptake and intention to recommend vaccinations to their patients. To our knowledge, no study has been conducted in South Africa to assess hesitancy to influenza vaccines among HCWs. We used questionnaire adapted from Betsch and colleagues to conduct an online and face-to-face cross-sectional study among HCWs at the start of COVID-19 vaccine roll-out prior to the flu season. Main outcome was influenza vaccine hesitancy. We used multivariate logistic regression to assess predictors of influenza vaccine hesitancy. Of 401 participants, 64.5% were women, 49.2% nurses, and 12.5% physicians. A total of 54.9% were willing to accept vaccination, 20.4% were undecided, and 24.7% intended to refuse. Older participants above 17-25 years and physicians were likely to receive the vaccine. Key predictors of vaccine acceptance were confidence in the effectiveness, consideration of benefits and risks, and willingness to be vaccinated to protect others. Influenza vaccine hesitancy was highest in those who did not trust that influenza vaccines are safe. For future flu seasons, tailored education programs targeting younger HCWs and more information about the composition of flu vaccines would be vital to improve vaccine uptake.

Objectives: As institutions modified medical practices to mitigate the spread of the SARS-CoV-2 virus, providers were forced to modify care through the implementation of telemedicine. The objective of this article is to review the current practices of otolaryngology during the COVID-19 pandemic and the limitations of telemedicine in current practice. Methods: A thorough review of the PubMed and MEDLINE databases was performed for publications between 2020 and 2021. Studies discussing telemedicine in otolaryngology during COVID-19 pandemic were selected. Results: As worldwide cases of COVID-19 continue to oscillate, we must continue to be vigilant in our clinical practice, implementing safe techniques to mitigate the spread of the SARS-CoV-2 virus through the continual use of telemedicine in all specialties of otolaryngology. Trends of increased patient acceptance of the use of telemedicine have been seen across subspecialities, including otolaryngology. Conclusion: Currently there are challenges associated with the implementation of telemedicine in the field of otolaryngology that rely heavily on adjunct physical examination, imaging studies, and specialty procedures. However, telemedicine has tremendous potential and can be adapted to include in the otolaryngologist’s toolbelt during public health emergencies such as the COVID-19 pandemic.

This study emphasizes the necessity of introducing a blockchain-based joint logistics system to strengthen the competency of medical supply chain management (SCM) and tries to develop a healthcare supply chain management (HSCM) competency measurement item through an analytic hierarchy process. The variables needed for using blockchain-based joint logistics are the performance expectations, effort expectations, promotion conditions, and social impact of the UTAUT model, and the HSCM competency results in increased reliability and transparency, enhanced SCM, and enhanced scalability. Word cloud results, analyzing the most important considerations to realize work efficiency among medical industry-related agencies, mentioned numerous words, including sudden situations, delivery, technology trust, information sharing, effectiveness, urgency, etc. This might imply the need to establish a system that can respond immediately to emergency situations during holidays. It could also suggest the importance of real-time information sharing to increase the efficiency of inventory management. Therefore, there is a need of a business model that can increase the visibility of real-time medical SCM through big data analysis. By analyzing the importance of securing reliability based on the blockchain technology in the establishment of a supply chain network for HSCM competency, we reveal that joint logistics can be achieved and synergistic effects can be created by implementing the integrated database to secure HSCM competency. Strengthening partnerships, such as joint logistics, will eventually lead to HSCM competency. In particular, HSCM should seek ways to upgrade its competitive capabilities through big data analysis based on the establishment of a joint logistics system.

Background: Simulation plays a crucial role in health studies, as it helps medical students apply their theoretical knowledge in real-life situations. Moulage is one of the techniques that helps in making simulation more realistic or high-fidelity. It uses special effects to emulate wounds for a better understanding of what the wound is like visually. Still, moulage is expensive, time-consuming, resource-intensive, and requires the training of staff, which is why we need to find low-cost substitutes for moulage materials. Method: When searching the database “PubMed” for the terms “Low-cost and Medical moulage”, we retrieved 222 studies, out of which when excluding results not related to low-cost, we obtained 62 studies, from which when removing studies that do not contain information regarding moulage, we found two papers, after referring to citations and cited articles of those papers, we ended up with six studies. Based on the selected articles and additional articles sourced from their reference list, a total of 11 studies were included in the review. Results: We understand that moulage is a technique that helps make simulations come alive, but the resources required to use it are at times, expensive, which is why we need to find methods to do low-cost moulage, and many studies address that it can be as simple as using homemade ingredients. Students from a previous study have talked about their opinions regarding the realistic component of moulage and whether if it is any different from other moulages. Most of the students agreed that the moulage ranked well in face and content validity. However, further innovations must be introduced in the field to be widely spread and lead to newer opportunities. Conclusion: Although the research done under moulage is limited, it is accepted that moulage is helpful for simulation-based studies and that low-cost moulage can help make medical studies a better experience for students studying it. Students have a favorable opinion on the realistic aspect of the low-cost moulage applied to them. Newer methods can be introduced to moulage, and it can be implemented in low-income countries.

Machine learning has become an increasingly ubiquitous technology, as big data continues to inform and influence everyday life and decision-making. Currently in healthcare, as well as in most other industries, the two most prevalent machine learning paradigms are supervised learning and transfer learning. Both practices rely on large-scale, manually annotated datasets to train increasingly complex models. However, the requirement of data to be manually labeled leaves an excess of unused, unlabeled data available in both public and private data repositories. Self-supervised learning (SSL) is a growing area of machine learning that has the ability to take advantage of unlabeled data. Contrary to other machine learning paradigms, SSL algorithms create artificial supervisory signals from unlabeled data and pretrain algorithms on these signals. The aim of this review is two-fold: firstly, we provide a formal definition of SSL, divide SSL algorithms into their four unique subsets, and review the state-of-the-art published in each of those subsets between the years of 2014-2020. Second, this work surveys recent SSL algorithms published in healthcare, in order to provide medical experts with a clearer picture of how they can integrate SSL into their research, with the objective of leveraging unlabeled data.

Medical Trust-Network is one of the most promising fields of study in network science. Establishment of trust within medical entities ensures better treatment and increases better medical facilities. The word ‘Trust’ signifies a very important behavioral aspect between any human entities, especially among doctors and patients. To represent such relationships Trust Network Models are built to express the interactions between human entities within such networks. Though the idea of a Trust-Network has traditionally been one of the major areas of research, yet the concept of a medical trust network model is relatively a new domain. In this paper, we introduce an overall multilayered Trust Network to represent the entire healthcare architecture. More specifically our model is based on an evolutionary graph system with a discrete relationship between the three most important entities of any healthcare system, namely – Doctors, Departments, and Hospitals. Observations indicate that based on our model, the medical healthcare system is a multilayered model unlike a feed-forward model as indicated by previous studies.

In recent years, more and more health data are being generated. These data come not only from professional health systems, but also from wearable devices. All these data combined form ‘big data’ that can be utilized to optimize treatments for each unique patient (‘precision medicine’). To achieve this precision medicine, it is necessary that hospitals, academia and industry work together to bridge the ‘valley of death’ of translational medicine. However, hospitals and academia often have problems with sharing their data, even though the patient is actually the owner of his/her own health data, and the sharing of data is associated with increased citation rate. Academic hospitals usually invest a lot of time in setting up clinical trials and collecting data, and want to be the first ones to publish papers on this data. The idea that society benefits the most if the patient’s data are shared as soon as possible so that other researchers can work with it, has not taken root yet. There are some publicly available datasets, but these are usually only shared after studies are finished and/or publications have been written based on the data, which means a severe delay of months or even years before others can use the data for analysis. One solution is to incentivize the hospitals to share their data with (other) academic institutes and the industry. Here we discuss several aspects of data sharing in the medical domain: publisher requirements, data ownership, support for data sharing, data sharing initiatives and how the use of federated data might be a solution. We also discuss some potential future developments around data sharing.

This study investigated co-constructed research poetry as a way to understand the lived experiences of people affected by rarer dementia and as a means to use poetry to convey those experiences to healthcare professionals. Using mixed-methods, 71 people living with rarer dementia and care-partners (stakeholders) contributed to co-constructing 27 poems with professional poets; stakeholders’ verbatim words were analysed with descriptive qualitative analysis. Stakeholders were also surveyed and interviewed about their participation. Healthcare professionals (n = 93) were surveyed to elicit their responses to learning through poetry and its acceptability as a learning tool. Poems conveyed a shared narrative of different aspects of lived experience, often owing to atypical symptoms, misunderstandings by professionals, lack of support pathways, and a continuous struggle to adapt. Stakeholder surveys indicated it was a valuable experience to both co-create and respond to the poems, whilst group interviews revealed people’s experiences of the research poetry were characterised by reflection on lived experience, curiosity and exploration. Healthcare professionals’ responses reinforced the poetry’s capacity to stimulate cognitive and affective learning specific to rare dementia support and prompt both empathy and critical thinking in practice. As the largest poetry-based study that we are aware of, this novel accessible approach of creating group poems yielded substantial information about the experiences and needs of those affected by rarer dementia and how poetry can contribute to healthcare education and training.

The complex progression, specialized care, and comorbidities of chronic diseases place a financial and health burden on society. In some instances, the high hospital readmission rate is also a result of chronic diseases. The readmission rates can be decreased if the quality of life for patients is increased and healthcare costs are reduced through effective management and preventive measures. As a result, healthcare professionals, service providers, and policy-makers are looking for innovative approaches to reduce healthcare costs while enhancing the quality of care. There is an emerging trend in deploying technological advancements like artificial intelligence (AI), the Internet of Things (IoT), sensors, wearables, social media, mobile apps, and genomics to decrease hospital readmissions. In some instances, predictive analytics, early warning systems, personal-ized care management, remote monitoring and Telehealth, decision support systems, patient education and engagement, and other areas of artificial intelligence and machine learning have outperformed traditional approaches in lowering hospital readmissions. Although AI effectively reduces readmission, there are potential risks if it is not combined with efficient interventions. Therefore, real-time monitoring and intervention are required for AI systems to increase patient safety and decrease hospital readmissions. To achieve autonomy, prevent harm, achieve fairness, and achieve explicability, the ethical principles relating to AI systems should be taken into ac-count. This study examines the significant impact on health and the economy of hospital read-missions for chronic diseases and the role of AI in reducing readmissions.

Leveraging on the theory of social exchange theory, the current study investigated the influential role that perceived organizational support plays in understanding the relationship between organizational cynicism and organizational deviant work behaviour. Scant research has addressed contextual factors in determining organizational cynicism and its relationship to negative work outcomes such as deviant work behaviour. An interactive effect of perceived organizational support was investigated to determine if deviant individuals are more or less prone to become organizational cynics based on the presence or absence of organizational support. The study was conducted in South-Eastern Nigeria, involving 575 nurses using two-wave design. Validated self-reported measures were used to collect data for perceived organizational support, organizational cynicism and organizational workplace deviance, which were analyzed using the Hayes PROCESS Macro for SPSS model 1 version 3.00. The results revealed that organizational cynicism positively correlated with organizational workplace deviant behaviour, whereas perceived organizational support negatively correlated with workplace deviant behaviour among nurses. In addition, perceived organizational support moderated the relationship between organizational cynicism and organizational workplace deviant behaviour. The study's findings revealed the imperativeness of a supportive work environment by underscoring the importance of contextual factors like perceived organizational support in mitigating workplace deviant behaviour. By focusing on fostering a supportive environment, organizations can better manage employee attitudes and reduce deviant behaviours, which enhances overall workplace performance and culture.

Background/Objectives: The introduction of robotic surgery has revolutionized surgical procedures bringing significant improvements in procedures such as radical prostatectomy. In Poland, robotic technology was first used in public healthcare in 2010 for colorectal surgery in Wrocław. Public funding for robotic urologic surgery began in 2022. The aim of this study is to evaluate the impact of integrating a stable source of funding on the development and utilization of robotic surgery. Methods: Using data from the National Health Fund, a retrospective analysis of these procedures was conducted, focusing on radical prostatectomies from the beginning of the funding period to November 2023. Results: The study showed that in the first year of public funding (2022), 2,149 radical prostatectomies were performed using robotic systems, and this number almost doubled to 4,331 by October 2023. Patients aged 60 years and older accounted for more than 80% of those undergoing robotic surgery. The rise in the popularity of robotic surgery is attributed to its advantages, including high precision, reduced invasiveness in the surgical field, minimized bleeding and pain, and reduced postoperative wound size. The use of robotic surgery also brings environmental benefits. Conclusions: The growing number of robot-assisted surgeries in Poland reflects the increasing role of robotics in medicine. These advances meet the growing demand for healthcare services and demonstrate the precision and effectiveness of robotic technology, potentially improving healthcare access and outcomes. Further implementation and refinement of robotic solutions are necessary to meet the changing needs of medical specialties.

The escalating antibiotic crisis in Nigeria presents a critical challenge, violating fundamental human rights and ethical obligations. Skyrocketing antibiotic costs severely restrict access to essential medications, particularly for vulnerable populations. This crisis not only exacerbates health disparities but also fuels the emergence of antibiotic resistance, posing grave public health risks. Rooted in regulatory gaps, lack of transparency in drug pricing, and inadequate healthcare infrastructure, the crisis demands a comprehensive, collaborative response. Policy interventions targeting antibiotic affordability, regulatory reforms, and healthcare infrastructure investments are imperative. Upholding ethical standards and accountability mechanisms is essential to ensuring equitable access to antibiotics and safeguarding public health in Nigeria.

The RECONNECT project tackles the fragmentation in Ireland's public healthcare systems, aiming to improve service planning and delivery. It integrates complex systems within the Health Service Executive (HSE) for chronic disease management, prioritizes data privacy, and supports future digital resource integration. The methodology includes: (1) structural integration via a Federated Database design to maintain system autonomy while ensuring privacy; (2) semantic integration through a Record Linkage module to enable integration without individual identifiers; and (3) adoption of the HL7-FHIR framework for high interoperability, aligning with the national electronic health record (EHR) and the Integrated Information Service (IIS). The RECONNECT system is unique in Ireland, featuring a generic architecture for loosely coupled systems, adherence to HL7-FHIR for interoperability, efficient reuse of digital assets, and a robust privacy layer. A demonstration system using synthetic data from the Hospital Inpatient Enquiry (HIPE) and Chronic Disease Management (CDM) systems is implemented on Neo4j for visualization.

The National Institute of Health Stroke Scale (NIHSS) is used worldwide to classify stroke severity as ‘mild’, ‘moderate’ or ‘severe’ based on neurological impairment. Yet stroke survivors argue that the classification of ‘mild’ does not represent the holistic experience and impact of stroke on their daily lives. In this observational cohort study, we aimed to identify different types of impairment among stroke survivors classified as mild. We used mild stroke survivors’ data from the START longitudinal stroke cohort (n=73) with measures related to sensorimotor, cognition, depression, functional disability, physical activity, work and social adjustment over 12 months. Given the multi-source, multi-granular and unlabelled nature of data, we utilised a structure-adapting, unsupervised machine learning approach, the Growing Self-organising Map (GSOM) algorithm to generate distinct clinical profiles. These diverse impairment profiles revealed that mild stroke survivors experience varying degrees of impairment and impact (cognitive, depression, physical activity, work/social adjustment) at different time points, despite the uniformity implied by their NIHSS-classified ‘mild’ stroke. This emphasises the necessity of creating a holistic and comprehensive representation of mild stroke survivors’ needs over the first-year post-stroke to improve rehabilitation and post-stroke care.

The integration of Artificial Intelligence (AI) in healthcare has transformed clinical practices by improving the accuracy of diagnosis, optimizing surgical procedures, improving the patient experience, and accelerating drug development. This article provides a comprehensive overview of the many applications of artificial intelligence (AI) across several industries, including fast diagnostics, where ML algorithms greatly enhance the accuracy and velocity of disease diagnosis. State-of-the-art robotic-assisted minimally invasive surgical procedures that shorten patients' hospitalization and improve their chances of recovery, cutting-edge AI applications in healthcare monitoring, and medication development. The article also looks at the primary challenges that AI in healthcare will inevitably encounter, such as differences in product quality, a shortage of skilled workers, privacy and ethical issues, and the need for improved regulatory frameworks. Despite the challenges, AI contributes significant advantages to the healthcare industry, providing novel and remarkable contributions to the efficiency of medical procedures and the progress of medical outcomes. The paper emphasizes the importance of cooperation in overcoming current challenges and enhancing the acceptability of AI technology in clinical settings. This will ensure that AI-driven innovations continue to enhance the standards of patient care.

Large Language Models (LLMs) have demonstrated promising capabilities to solve complex tasks in critical sectors such as healthcare. However, LLMs are limited by their training data which is often outdated, the tendency to generate inaccurate ("hallucinated") content and a lack of transparency in the content they generate. To address these limitations, retrieval augmented generation (RAG) grounds the responses of LLMs by exposing them to external knowledge sources. However, in the healthcare domain there is currently a lack of systematic understanding of which datasets, RAG methodologies and evaluation frameworks are available. This review aims to bridge this gap by assessing RAG-based approaches employed by LLMs in healthcare, focusing on the different steps of retrieval, augmentation and generation. Additionally, we identify the limitations, strengths and gaps in the existing literature. Our synthesis shows that proprietary models such as GPT-3.5/4 are the most used for RAG applications in healthcare. Also, there is a lack of standardized evaluation frameworks for RAG-based applications. In addition, the majority of the studies do not assess or address ethical considerations related to RAG in healthcare. It is important to account for ethical challenges that are inherent when AI systems are implemented in the clinical setting. Lastly, we highlight the need for further research and development to ensure responsible and effective adoption of RAG in the medical domain.

This manuscript offers a concise overview of paper microfluidics, emphasizing its sustainable sensing applications in healthcare, environmental monitoring, and food safety. Researchers have developed innovative sensing platforms for detecting pathogens, pollutants, and contaminants by leveraging the paper’s unique properties, such as biodegradability and affordability. These portable, low-cost sensors facilitate rapid diagnostics and on-site analysis, making them invaluable tools for resource-limited settings. The review discusses fabrication techniques, principles, and applications of paper microfluidics, showcasing its potential to address pressing challenges and enhance human health and environmental sustainability.

The healthcare situation in Africa is characterized by limited resources and a high burden of disease, presenting significant challenges to the healthcare systems in the region. The integration of Artificial Intelligence (AI) technologies in African healthcare holds immense potential for addressing these challenges and improving health outcomes. This paper aims to provide a comprehensive understanding of the current healthcare landscape in Africa and the urgent need for AI-driven solutions.In addition to discussing the potential applications of AI in African healthcare, such as disease diagnosis, treatment planning, and medical imaging analysis, this manuscript seeks to shed light on the specific challenges hindering the implementation of AI in the region. By providing detailed examples and case studies, we aim to offer insights into the obstacles that need to be overcome and potential solutions that can be pursued.By leveraging AI technologies, Africa has the opportunity to revolutionize its health systems, bridging the gap in access to quality healthcare across the continent. The objective of this review article is to not only highlight the potential benefits that AI can bring to African healthcare but also to emphasize the urgent need for action and collaboration in implementing and scaling up AI innovations in the region. By doing so, African countries can pave the way for improved health outcomes and ensure that their populations receive the healthcare services they deserve.

In the context of sustainable development, integrating the work aspect into health promotion systems is essential, ensuring that employees maintain a healthy balance between their professional and personal lives, which respects and amplifies the potential of every individual. Lately, there has been a noticeable shift of medical professionals from the public to the private sector. This trend paints a bleak picture, highlighting the vulnerabilities of a system teetering on the brink of failure, with significant impacts on patient care. Among the myriad reasons behind this shift, burnout stands out prominently. Medical professionals face increasing pressures due to understaffing, limited organizational support, and insufficient resources, leading to feelings of cynicism, exhaustion, and detachment from their roles. Utilizing the Maslach et al. questionnaire, we assessed the risk of burnout among physicians in public hospitals to identify and underscore preventive measures and improvements, correlating our findings with key aspects of organizational empowerment. Our research indicates that enhancing interpersonal relationships and resources—both within teams and between the organization and its physicians—is crucial for the revival of the healthcare system. This approach aims at improving the delivery of healthcare services and offering appropriate recognition to healthcare professionals, aligning with the principles of sustainable employment.

Addressing the increasing nursing demand in the face of a limited nursing workforce, understanding job satisfaction and retention becomes critical. Our cross-sectional study, conducted among 2,572 nurses in Bavaria, Germany, uncovers a dichotomy where nurses have strong empathy for their profession yet yearn for significant improvements. The top areas identified for enhancement include (i) ensuring sufficient time for patient care, (ii) providing a reliable service organization with minimal unplanned shift changes, and (iii) streamlining nursing documentation. Moreover, the largest disparity between expectations and job satisfaction was measured in patient care time. Multivariable regression analysis further investigates factors influencing intentions to stay in the profession, including (i) demographic aspects (age, living conditions), (ii) working area, (iii) working hours, (iv) career choice satisfaction, (v) career opportunities, (vi) payment, (vii) working and rest times, and (viii) satisfaction derived from aiding individuals in challenging life situations. The findings uncover a need to change nursing conditions, and measures for younger nurses and elderly care nursing. Although there are limitations, and a potential bias due to convenience sampling, our study provides key insights into nursing conditions. Future research should broaden its scope to investigate nurse job satisfaction and retention, emphasizing potential relief tools such as digitization.

The prevalence of depression and anxiety among healthcare workers (HCWs) during the Covid-19 pandemics is high. The aim of the study is to identify the importance of self-esteem and occupational factors in association with the incidence of depression and anxiety among HCWs through a longitudinal cohort study during the Covid-19 pandemics in Latvia. Participants were interviewed repeatedly seven times during the Covid-19 pandemics. 322 participants were included in the data analysis for depression and 352 for anxiety. Low self-esteem and working in the general practitioner's office is associated with the incidence of depression and anxiety. Undergraduate education and direct contact with Covid-19 patients are associated with the incidence of depression. The risk of anxiety decreases by 1% each year among HCWs. Our study shows the importance of personality factors of HCWs during the Covid-19 pandemics.

One of the challenges in the healthcare sector is making accurate forecasts across insurance years for claims reserve. The state-of-the-art envisages various methods for estimating the claims reserve but without being applied to systems that do not present huge variability and heterogeneity, such as the healthcare sector. The methodology is based on generalized linear models using the Overdispersed Poisson distribution as shown in the state-of-the-art. In this context, we developed a method to estimate the parameters of the quasi-likelihood function using a Gauss-Newton algorithm optimized through a genetic algorithm. The genetic algorithm plays a crucial role in glimpsing the position of the global minimum to ensure a correct convergence of the Gauss-Newton method, where the choice of the initial guess is fundamental. The proposed methodology has been entirely developed using MATLAB and has been applied to estimate the claims reserve in the healthcare system of the Tuscany Region in Italy, as case study. The results obtained were validated by comparing them with the state-of-the-art by measuring the confidence intervals of the Overdispersed Poisson distribution parameters. Therefore local healthcare authorities could use the proposed and improved methodology to allocate the resources dedicated to healthcare and global management.

The global SARS-Cov-2 which caused the coronavirus disease 2019 (COVID-19) pandemic has had a significant impact over the last 3.5 years, especially among healthcare workers (HCWs) who were constantly in the forefront of the pandemic. Due to the nature of their work, HCWs faced a potential risk of exposure. Therefore, this study investigated the individual-level factors associated with perceived COVID-19 risk among South African HCWs. We used an analytical cross-sectional study design to analyse data from the South African Health Care workers’ response to the Coronavirus (COVID-19) pandemic online survey conducted by the Human Sciences Research Council across the nine provinces in South Africa, from 11th April to 7th May 2020. In this study, only data (n= 5 579) with non-missing values for COVID-19 risk and individual-level factors (age, gender, educational level, occupational category, and race) was analysed. Univariate and Multivariate binomial logistic regression analyses were conducted. The crude and adjusted odds ratio and p-value ≤ 0.05, were used to describe the association between the individual-level factors and perceived COVID-19 risk, from low-medium to high. The binomial logistic regression was used to assess the factors associated with high perceived risk. Perceived COVID-19 risk among HCWs in South Africa was significantly associated with age, race, educational level and occupational category. Being 60 years and older, being “White”, having a Master’s and Doctorate degrees and being a healthcare worker other than a nurse practitioner and medical practitioner, all had higher odds of having high perceived COVID-19 risk. The findings may be used to guide policies and programs aimed at mitigating the impacts of COVID-19 and other similar pandemics.

Climate Change is the most serious planetary emergency of our time. Carbon emissions secondary to the healthcare industry account for about ten percent of all emissions in the United States. Health professionals, therefore, need to understand how they can make a difference in their profession, by understanding the health-related impacts of climate change and the importance of healthcare sustainability. An 8-week telementoring Climate Change Healthcare Sustainability ECHO series was developed to educate healthcare professionals in these topics such as the health-related effects of climate change, healthcare sustainability, quality healthcare and carbon accounting. A total of 376 participants from throughout the US and 16 other countries- completed this 8-week series and received no-cost continuing medical education credits. The evaluation consisted of pre and post Zoom polls, weekly post-session surveys and the registration demographics. Participants were primarily physicians and public health professionals who significantly improved their knowledge and communication skills after the course as compared to starting the training.

The prevalence of chronic diseases is dramatically increasing demand for emergency healthcare. Existing systems rely on patients self-identifying symptoms, causing dangerous delays. This study develops an AI and IoT-powered “digital twin” solution to enable continuous real-time monitoring and timely prediction of diverse medical emergencies. A digital twin is a virtual representation of an individual, modeled using multidimensional physiological data from wearable sensors. Machine learning techniques analyze patterns in this data to identify anomalies and predict emergencies like heart attacks or falls. A key contribution is an optimized ensemble algorithm combining gradient boosted trees, neural networks, and other techniques to accurately detect emergency events. Evaluation on a dataset of 9158 samples shows the digital twin identifies key emergencies with over 90% recall, enabling prevention and rapid response. It allows risk stratification and personalized interventions based on early warnings, circumventing over 2 million avoidable emergency room visits annually. This study demonstrates the feasibility of an integrated, predictive, patient-centric emergency response system enabled by digital twin technology.

The purpose of this study was to evaluate the financial performances of the publicly held healthcare companies in crisis periods in Türkiye. The 2018 Economic Crisis and the COVID-19 pandemic crisis were included in the study as the crisis periods. We collected the financial data of the publicly held healthcare companies and calculated three liquidity, three turnover, three leverage and three profitability ratios by ratio analysis to use as financial performance indicators. We then conducted Wilcoxon signed-rank tests and we did separate analyses for the 2018 Economic Crisis and the COVID-19 pandemic crisis. The results of the analyses showed that there were no statistically significant differences between the publicly held healthcare companies’ liquidity, turnover, leverage, profitability ratios and thus their financial performances before the crises and after the crises. While the results are reassuring and give valuable insights to managers and policy makers to determine the areas that needs to be strengthened to be better prepared for possible future crises, our sample was limited. Therefore, this study presents an exploratory foundation for future studies which are needed to make a case of financial stability for the publicly held healthcare companies before and after the crisis periods.

Vaccination has proven highly effective against severe acute res-piratory syndrome coronavirus 2 (SARS-CoV-2), but the long-term immunogenicity and the functional preserved im-mune responses of vaccines are needed to inform evolving evi-dence-based guidelines for boosting schedules. We enrolled 205 healthcare workers into a cohort study; all had received three doses of BBIBP-CorV (China Sinopharm Bio-Beijing Company) inactivated vaccine. We assessed SARS-CoV-2 specific binding antibodies, neutralizing antibody, and peripheral T and B cell responses. We demonstrated that more robust antibody re-sponses to SARS-CoV-2 were elicited by booster immunization compared to primary vaccination. Neutralizing antibody titers to SARS-CoV-2 Omicron variant were also efficiently elevated post homologous vaccine booster despite in a lower titer compared to the prototype stain. In addition to S specific humoral and cellular immunity, BBIBP-CorV also induced N-specific antibody and ef-fector T cell responses. The third-dose vaccination led to further expansion of critical polyfunctional T cell responses, likely an essential element for vaccine protection. In particular, a func-tional role for Tfh cell subsets in immunity was suggested by the correlation between both CD4+Tfh and CD8+Tfh with total anti-body, IgG, B cell responses and neutralizing antibodies. Our study details the humoral and cellular responses generated by the BBIBP-CorV booster vaccination in a seven-month follow up study. There is a clear immunologic boosting value of homolo-gous inactivated SARS-CoV-2 vaccine boosters, a consideration for future vaccine strategies.

Covid-19 has had a significant impact on the lives of populations across the world. Since the first reported case of the coronavirus in Wuhan, China, the world faced a situation of dealing with a novel virus. While the physical health effects of the coronavirus was the center of focus for much of the pandemic, Covid-19 was accompanied with significant social and psychological consequences on the world populations. In this review, we aim to assess how the coronavirus pandemic has affected the African continent at large, highlighting the socio-psychological consequences. Through citing some examples of a few countries in Sub-Saharan Africa, the review will detail the experiences of the populations within this region which remain plagued with economic and health vulnerabilities that were further exposed by the pandemic.

The aim of this study was to measure one-year total cost of stroke and to investigate the value of stroke care, defined as cost per QALY. The study population included 892 patients with first ever acute stroke, hemorrhagic and ischemic, (ICD-10 codes: I61, I63 and I64) admitted within 48 hours of symptoms onset to nine public hospitals located in six cities. We conducted a bottom-up cost analysis from the societal point of view. All cost components including direct medical costs, productivity losses due to morbidity and mortality and informal care costs were considered. We used an annual time horizon, including all costs for 2021 irrespective of the time of disease onset. The average cost (direct and indirect) was extrapolated in order to estimate the national annual burden associated with stroke. We estimated the total cost of stroke in Greece at €343.1 mil a year in 2021, (€10,722/patient or €23,308 per QALY). Out of €343.1 mil., 53.3% (€182.9 mil) consisted direct healthcare cost representing 1.1% of current health expenditure in 2021. Overall, productivity losses were calculated at €160.2 mil. The mean productivity losses were estimated to 116 work days with 55.1 days lost due to premature retirement and absenteeism from work, 18.5 days lost due to mortality and 42.4 days lost due to informal caregiving by family members.This study highlights the burden of stroke and underlines the need for stakeholders and policy makers to re-organize stroke care and promote interventions that have been proved as cost-effective

Context. During the COVID-19 pandemic, patient care was mainly organised around the hospital. Pre-hospital care has, to our knowledge, never been evaluated. Objective: To evaluate the impact of pre-hospital pathways on hospitalisation during the last part of the pandemic. Design. This was a monocentric retrospective analysis of prospectively collected medical records. Data from patients admitted to our institute between 1 February and 7 March 2022 were analysed. Main Outcome Measure(s): The primary outcomes were defined as the number of hospitalisations, resuscitations, and deaths at the time of interview and in the subsequent 30 days. The main explanatory variables were times from onset of symptoms to care, age, gender, News2 score, comorbidities, and pre-hospital pathways and their duration. Results: Three pre-hospital pathways have been identified: a pathway in which the patient consults a general practitioner for a test (PHP1); a pathway in which the patient consulted for care (PHP2); and no pre-hospital pathway and direct admission to hospital (PHP3). Factors independently associated with outcome (hospitalisation) were being male (OR 95% CI; 2.21 [1.01–4.84], p=0,04), News2 score (OR 95% CI; 2.04 [1.65–2.51], p<0.001), obesity (OR 95% CI; 3.45 [1.48–8.09], p=0.005), D-dimers > 0.5 µg/ml (OR 95% CI; 3.45 [1.47–8.12], p=0.005), prolonged time from symptoms to hospital care (PHP duration) (OR 95% CI; 1.07 [1.01–1.14], p=0.03). All things being equal, patients with a “PHP2” pre-hospital pathway had a higher probability of hospitalisation compared to those with a “PHP3” pre-hospital pathway (OR 95% CI; 4.31 [1.48–12.55], p=0.007). Conclusions. Along with recognised risk factors such as gender, News 2 score, and obesity, the patient’s pre-hospital pathway is an important risk factor associated with hospitalisation.

(1) Background: The prevalence of SARS-CoV-2 infection among healthcare workers (HCWs) in Poland is not exactly known. This study aims to present secondary epidemiological data identifying the scale of the spread of novel coronavirus infection in selected professional groups of HCWs in Poland. (2) Methods: The secondary epidemiological data included both the number of infections and the number and percentages of deaths in individual occupational groups, which occurred throughout the observation period, both in the country and in individual voivodeships. (3) Results: The prevalence of SARS-CoV-2 infections among HCWs was 16.48%. The highest percentage of infected concerned laboratory scientists (21.62%) and paramedics (18%). The highest frequency of infections among HCWs occurred in the province of Zachodnio-Pomorskie (18.9%). Due to COVID-19, 558 healthcare workers died during the analysed period, mostly nurses (n=236) and doctors (n=200). The results regarding the vaccination coverage of HCWs against COVID-19 indicate the highest percentage of vaccinated were among doctors (83.63%) and the smallest among physiotherapists (38.2%). (4) Conclusions: In general, the percentage of infections was high in Poland during the pandemic (16.48%). Significant territorial differences were observed in the frequency of infections, deaths, and percentage of vaccinated workers in individual voivodeships.

Background: Community-based medical education (CBME) is an essential component of medical education, where primary healthcare physicians (PHPs) play a crucial role. This study explores PHPs' awareness and engagement in CBME and investigates the factors influencing their participation. Methods: This mixed study was conducted in two phases. In the first phase, a qual-itative study was conducted using semi-structured interviews with PHPs, and thematic analysis related to their awareness and engagement in CBME. In the second phase, a quantitative survey was conducted among 72 PHPs pre- and post-training programs. Results: Primary healthcare physicians had a positive attitude toward community-based medical education. The participants have an acceptable level of awareness and engagement, which increased substantially (p-value = 0.03) and (p-value = 0.003), respectively. Logistic analysis indicated that non-Saudi physicians were likelier to participate in the CBME (p-value=0.001). Professions and academic experiences influence their willingness and engagement to participate in CBME (OR= 7.5, p-value=0.001) and (OR=0.21, p-value=0.001), respectively. Conclusion: The study findings highlighted the importance of increased awareness and the factors that enhance PHPs' engagement in CBME. This positive perspective of the PHPs helps build effective partnerships and facilitates the extension of the curriculum to apply CBME.

Background Out-of-pocket costs are key expenses that many individuals incur in order to receive health services. They have been identified as a key access barrier for vulnerable populations, in particular for populations affected by neglected diseases with a chronic progression, such as Chagas disease. It is important to understand the costs of accessing healthcare services that are borne by patients with T. cruzi infection. Methodology We prepared a structured survey for patients with T. cruzi infection/Chagas disease who were all treated by the healthcare system in endemic municipalities in Colombia. The results were analyzed according to three categories: 1. the socioeconomic profiling of the patients; 2. the costs of and time spent on transportation; and 3. the opportunity costs (money that was not earned) related to treatment at the local primary care hospital or at the high-complexity reference hospital. Main findings Ninety-one patients answered the survey voluntarily. The data revealed that, when treated at the specialized reference hospital, patients spent 5.5 times more on food and accommodation, transportation costs were five times higher, and the loss of earnings was three times higher than when they were treated at the local primary care hospital. Moreover, the amount of time spent on transportation was 4 times higher at the reference hospital. Conclusions Providing comprehensive healthcare services for Chagas management at local primary healthcare hospitals would allow the most vulnerable patients to save on expenses related to medical and non-medical costs (out-of-pocket costs), in turn leading to higher adhesion to treatment thus benefiting the health system as a whole. These findings are in alignment with the WHO’s World Health Assembly 2010 Resolution on the importance of treating Chagas at local primary care hospitals, thereby saving patients time and money, allowing for timely care, and promoting access to healthcare.

Abstract Background COVID-19 vaccination program among Adults in India is one of the highly successful vaccination drives globally. Indian children aged 15–18 years old became eligible for COVID-19 vaccination on 3rd January, 2022 followed by 12-14 years old children on 16th March, 2022. As parents are primary decision-makers for their children, we aimed to assess parents' perceptions and intentions regarding COVID-19 vaccination for children in India. Aim To assess parental perceptions and intention to get COVID-19 vaccination for their children (aged<18 years), Materials and Methods A cross-sectional anonymous web-based survey was designed. Healthcare workers of a tertiary care institute in Eastern U.P. having any children aged <18 years were the study population. They were recruited through snowball sampling and were sent the study questionnaire in Google form through email and WhatsApp. Cross-tabulation was performed by parents' intention to vaccinate their children against COVID-19 virus with socio-demographic characteristics and their risk perception toward COVID-19, trust in the healthcare system, and their history of vaccine hesitancy behavior routine childhood immunization. Bi-variate analysis was performed to find out the predictors of child vaccination intention among the parents. Results A total of 388 healthcare workers parents (HCWPs) having A child < 18 years of age completed the survey. Mean age of the parents were 40.28 ±11.34 years with majority(97.0%) completing recommended 2 doses of COVIID-19 vaccine. Around 91% of the parents agreed that COVID-19 vaccines are important for child’s health whereas about 89% agreed to the statement that COVID-19 vaccines are effective. A total 356 (91.7%) participants were willing to vaccinate their child against COVID-19, 91.3% of them liked to do so as soon as possible. The factors significantly associated with the stated likelihood of child vaccination among the participants were younger age, female gender, urban residence, absence of any chronic illness, lower monthly income, history of COVID-19 in child and the child/children completed with routine childhood vaccines. Parental concerns mainly centered around vaccine need, safety and side effects. Conclusion The healthcare worker parents(HCWPs) have good knowledge and positive attitude towards COVID-19 vaccination for children. Around 92% of them were willing to vaccinate their children with COVID vaccine currently, which implies very low vaccine hesitancy among the HCWPs . Further longitudinal studies are required to be conducted to assess the trend of parental acceptance of COVID vaccine.

Healthcare workers (HCWs) are regarded as role models regarding health-related issues including vaccination. Therefore, it is essential to identify the predictors for COVID-19 vaccine acceptance among them. A cross-sectional study to assess the risk perception, attitudes and knowledge of HCWs toward COVID-19 vaccination was carried out. A total of 710 responses were received between September 2021 to March 2022, from HCWs in the Northern, Western and Eastern regions of Nigeria. Cross tabulations were performed to determine statistical relations between sociodemographic variables, knowledge, attitudes and risk perceptions concerning COVID-19 vaccine acceptance. Multinomial Logistic Regression analysis was performed to determine the predictive variables for COVID-19 vaccine acceptance. Statistical analyses were performed and P-values less than 0.05 were considered statistically significant at a CI of 95%. Results showed that 59.3% of the participants were amenable to COVID-19 vaccines. Multinomial regression analysis identified 14 variables at α <0.05 as predictors for vaccine acceptance. Male HCWs were 2.8 times more likely to accept the vaccine than their female counterparts. HCWs that were knowledgeable of the different kinds of vaccines, willing to recommend the vaccines to their patients, believe that the timing of COVID-19 vaccination was appropriate and had recent vaccination history within three years were 1.6, 24.9, 4.4 and 3.1 times more likely to take COVID-19 vaccine than those not sure. The study found a relatively high trust (51.3%) in the Nigerian Center for Disease Control (NCDC) for information regarding COVID-19 vaccines. Therefore, the NDCD should disseminate more robust insights regarding the safety profiles of various COVID-19 vaccines.

COVID-19 has become a part of everyone's day-to-day life, since the outbreak in 2019 the novel coronavirus disease (COVID-19) has caused more than 4.5 million deaths with over 200 million cases reported globally. Currently, the number of infections and deaths are gradually lowering in different countries however the underlying challenges still exist. COVID-19 threatens human life, social functioning and development. Although numerous studies have been carried out in the past to highlight the key challenges very limited studies have been conducted from an ordinary person's viewpoint. In the fight against COVID-19, humanity has been pushed to a level which cannot be accepted where establishing that balance is a priority. This study focuses on highlighting the common issues faced by the ordinary public in the current era. Five key areas were identified to be the most essential; education, technological adaptation, transportation, mental health and gender-based violence (GBV).

The COVID19 pandemic tested the performance of hospitals and intensive care units around the world. Health care workers (HCWs) have been used to develop mental symptoms, but this was especially true during the COVID19 pandemic when HCWs must deal with many other sources of stress and anxiety that can usually be avoided, and long-term shifts and unprecedented population restrictions have weakened people's ability to cope with stress. The research aims to observe the dynamic interplay between burnout, depression, distress, and anxiety in HCWs working in various settings, with specific a focus on Emotional exhaustion, depersonalization, and a diminished sense of personal achievement in mediating a worst mental health status during the first wave of the COVID19 pandemic in Italy. To analyze that we performed a mediation analysis, from which resulted a strong correlation among depression, psychological distress, health perception and anxiety, and the impact of job burnout on anxiety, depression, and distress. Gender seemed to have a strong correlation with burnout, anxiety, and distress; the impact of COVID19 pandemic on Quality of Life seemed to affect anxiety and depression; the changing of mansion influenced depression and job burnout. Encouraging supportive and educational strategies would certainly be recommended to policy makers.

Today, across the most critical problems faced by hospitals and health centers are those caused by the existence of patients who do not attend their appointments. Among others, this practice generates waste of resources and increases the patients’ waiting list. To handle these problems, hospitals are actively trying to implement methods to reduce the idle time caused by patient no-shows. Many scheduling systems developed require predicting whether a patient will show up for an appointment or not. Although, a challenging problem resides in obtaining these estimates precisely. The goal of this work is to analyze how objective factors influence a patient not to attending their appointment, to identify the main causes that contribute to a patient’s decision, and to be able to predict whether or not the patient will attend the scheduled appointment. As a result, the obtained model is tested on a real dataset collected in a health center linked to the University of Vale do Itajaí (UNIVALI), which includes 25 features and about 5000 samples. The algorithm that produced the best results for the available dataset is the Random Forest classifier. It reveals the best recall rate (0.91), since it measures the ability of a classifier to find all the positive instances and achieves a receiver operating characteristic curve rate of 0.969.

Background: Sudden changes in clinical practice and the altered ability to care for patients due to the COVID-19 pandemic have been associated with moral distress and mental health concerns in healthcare workers internationally. This study aimed to investigate the severity, prevalence, and predictors of moral distress experienced by Australian healthcare workers during the COVID-19 pandemic. Methods: A nationwide, voluntary, anonymous, single time-point, online survey of self-identified frontline healthcare workers was conducted between 27th August and 23rd October 2020. Participants were recruited through health organisations, professional associations or colleges, universities, government contacts, and national media. Results: 7846 complete responses were received from nurses (39.4%), doctors (31.1%), allied health staff (16.7%) or other roles (6.7%). Many participants reported moral distress related to resource scarcity (58.3%), wearing PPE (31.7%) limiting their ability to care for patients, exclusion of family going against their values (60.2%), and fear of letting co-workers down if they were infected (55.0%). Many personal and workplace predictors of moral distress were identified, with those working in certain frontline areas, metropolitan locations, and with prior mental health diagnoses at particular risk of distress. Moral distress was associated with an increased risk of adverse mental health outcomes. Feeling appreciated by the community mitigated this risk in healthcare workers. Conclusions: Safeguarding healthcare workforces during crises is important for both patient safety and workforce longevity. Targeted interventions are required to prevent or minimise moral distress and associated mental health concerns in healthcare workers during COVID-19 and other crises.

The impact of organizational accreditation and professional certification and the evidence-based measurable impact of those for both academic programs and affiliates is one of specific interest to universities and individuals in the healthcare management field [1]. The authors’ analysis examined the impact of hiring graduates from higher education programs that held external accreditation from the Commission on Accreditation of Healthcare Management Education (CAHME). Graduates’ affiliation with the American College of Healthcare Executives (ACHE) professional healthcare leadership organization was also assessed as an independent variable. Study outcomes focused on these graduates’ respective healthcare organization’s performance measures (cost, quality, and access) to assess the researchers’ inquiry into the perceived value of a CAHME-accredited graduate degree in healthcare administration and a professional ACHE affiliation [2]. The results from this study found no effect of CAHME accreditation or ACHE affiliation on healthcare organization performance outcomes. The study findings support the need for future research surrounding healthcare administration professional graduate degree program characteristics and leader development affiliations, as perceived by various industry stakeholders.

Little is known about family medicine academic staff in Taiwan, and basic data about this workforce may aid healthcare decision makers. We analysed data on Taiwan’s 13 medical schools collected by the Taiwan Association of Family Medicine from June to September 2019. Items included medical school names and total staff, and the gender, age, degree, working title (part-time/full-time), academic level, and sub-specialty of each current family medicine faculty member. A total of 116 family medicine faculty members were reported; most were male (n= 85, 73.3%). Ages ranged between 30 and 69 years, with a mean (SD) age of 43.3 (8.09). Faculty members with a master’s degree were the largest group (n= 49, 42.2%), and most were academic lecturers (n=49, 42.2%). Additionally, only about one-fourth (n=26, 22.4%) of family medicine faculty in medical schools were full-time, while the other three-fourths (n=90, 77.6%) were part-time faculty; most were located in northern Taiwan (n=79, 68.1%) and specialized in gerontology and geriatrics (n=55, 47.4%) and hospice palliative care (n=53, 45.7%). Our research provides the most complete census of family medicine academic physicians in medical schools in Taiwan. The results inform efforts to improve the establishment and development of family medicine departments in Taiwan.

Purpose: The ongoing COVID-19 crisis has created the need for social distancing between medical staff and patients, therefore, healthcare robotics is increasingly important as regards infectious control. The purpose of this study was to design and fabricate a remote controlled transport robot that could provide an optimum technology base for developing countries, having dual functions of telepresence and delivery operations inside or outside buildings, is easy to assemble and also easily able to be cleaned using standard chemical agents.Methods: This machine was designed and fabricated to incorporate two main functions; delivery and telepresence. The robot consists of a base frame, DC motors for driving and steering systems, actuator motor for driving wheel elevation, Wi-Fi AP/Repeater, network camera, and a necessary a back-up power system.Results: This robot can be used both indoors and outdoors. It can carry loads of more than 80 kg. The machine can cross obstacles greater than 3 cm. It can be cleaned by disinfectant agents. An actuator motor can lift the driving wheels above the surface to prevent gear damage. Conclusion: This article demonstrates the concept of a healthcare telepresence and delivery robot that can provide distancing during the present COVID-19 crisis, using optimum technology for low and middle-income countries. In the future, the researcher should consider development of the delivery controls, combined with the telepresence system using the internet of things, to improve the navigation system, the manipulator system for supporting multi-floor transportation, and also other multi-functional purposes.

When all countries are battling Covid-19 by adopting different policies, it could help address the issue of government response policy efficiency. This study examines the efficiency of government intervention policies in 19 countries, the efficiency of preventing the spread, and also the mortality caused by the virus. The policies are categorized based on the Oxford COVID-19 Government Response Tracker, which combines various indicators, including Containment and closure, Economic response, and Health systems. Given that the governments apply a top-down approach to design these policies, the current research evaluates the efficiency of policies based on the same approach. Here, two different models have been used to calculate the efficiency of policies. We designed a combined index in both models and applied Window DEA method to determine the output quantities in the efficiency ratio. The results of our study show that in both models, Japan, Finland and Thailand had the highest level of government response efficiency. The countries with the lowest government response efficiency were the United States, Spain, and Russia in the first model, and China, Italy, and Spain in the second.

Learning systems have been very focused on creating models that are capable of obtaining the best results in error metrics. Recently, the focus has shifted to improvement in order to interpret and explain their results. The need for interpretation is greater when these models are used to support decision making. In some areas this becomes an indispensable requirement, such as in medicine. This paper focuses on the prediction of cardiovascular disease by analyzing the well-known Statlog (Heart) Data Set from the UCI’s Automated Learning Repository. This study will analyze the cost of making predictions easier to interpret by reducing the number of features that explain the classification of health status versus the cost in accuracy. It will be analyzed on a large set of classification techniques and performance metrics. Demonstrating that it is possible to make explainable and reliable models that have a good commitment to predictive performance.

Objectives: The aim of this study was to assess the knowledge, attitude and practice of healthcare professionals regarding adverse drug reaction [ADR] monitoring and pharmacovigilance [PV] in India. Materials and Methods: It was a questionnaire based cross sectional observational study. Data was collected with the help of data collection Google form that included the demographics and twenty two survey based questions. Data were analysed by using Microsoft Excel sheet, further analysed for results, including frequency, percentage, mean and standard deviation. Result: The questionnaire was filled by two hundred ten healthcare professionals in which 52.9 % were male and 47.10% of female. Most of the respondents were pharm d students (50.47%). Out of the total 91.4% responded to the definition of pharmacovigilance correctly. 87.6% participants said all ADR should be reported. 86.20% participants think Pharmacovigilance should be taught in detail to healthcare professionals. Most of the respondents (43.8%) always informed the patients about ADR while prescribing the medicines. Conclusion: Study revealed most of the participants have good knowledge about ADR and pharmacovigilance. Difficult to decide whether ADR occur or not and extra work load being major factors responsible for under reporting.

Background: The healthcare workers are exposed to dangerous pathogen agents during the outbreak of the new coronavirus COVID-19. To minimize the risk of becoming infected by this virus, healthcare workers need to wear the most appropriate personal protective equipment (PPE). Objective: The objective of this study was to analyze the guidelines that the World Health Organization (WHO) and the Centers for the Disease Control and Prevention (CDC) recommend for the rational use of EPP to protect healthcare workers against the novel coronavirus COVID-19.Methodology: To learn how to effectively protect healthcare workers against the COVID-19, a detailed analysis and comparison of the WHO and CDC guidelines related to the proper use of personal protection equipment (PPE) in different healthcare settings was carried out. Results: The results of this study based on an analysis of PPE recommended by the World Health Organization (WHO) and the Centers for the Disease Control and Prevention (CDC) indicated that the safety and protection of healthcare workers can be maximized if the guidelines suggested by these institutions are followed. In general, the WHO and CDC recommendations based on medical practices are similar, and depending on the healthcare activities and settings where the healthcare workers perform their work, suggest wearing medical/surgical facemasks, respirators, googles and face shields (eye protection), gloves, gowns and aprons. Conclusions: The protection and safety of the healthcare workers can be maximized during the outbreak of COVID-19 by following the WHO and CDC recommendations described in this study. The general guidelines offered by these institutions are similar and based on medical practices.

In the wake of the novel coronavirus, SARS-CoV-19, the world has undergone a critical situation in which grave threats to global public health emerged. Among human populations across the planet, travel restraints, border enforcement measures, quarantine, and isolation provisions were implemented in an attempt to control and limit the spread of the contagion. Decisions on how to implement and enforce various control policies should be determined based on available real-world evidence and theoretical prediction. In this study, we propose a novel exportation- importation epidemic model associated with the quarantine and hospitalized-isolation policies by considering the two-body system: a source country of a contagious disease and a neighboring country that is initially disease-free. The model is first applied to the original COVID-19 data in China, Italy, and the Republic of Korea (ROK) and observed through consistent fitting results with equivalent goodness-of-fit. Then, the data are estimated per the fitting parameters. Driven by these parametric settings and considering the normalized population, the numerical analysis, and epidemiological exploration, this work further elucidates the substantial impact of quarantine policies, healthcare facilities, and the public counter-compliance effect.

In the area of dental healthcare services, where patients and professionals deal with multiple auditory stimuli, this cross-sectional study reports on the intricate dynamics of sound preferences, noise obstacles, and the profound impact of music on anxiety reduction within dental office set-tings. The sample comprises of 134 dental patients, primarily females (56.7%), with varying age groups, education levels, and therapy durations in the university clinics of the department of Dentistry, National and Kapodistrian University of Athens and four private dental offices at the metropolitan area of Athens, Greece. Notably, 92.5% of the participants report no hearing loss, and 56.7% exhibit some level of noise sensitivity. The study reveals a moderate to good perceived health status (M=3.84, SD=0.95) among participants, with low perceived noise disturbance in university dental clinics. Preferences for instrumental music, foreign pop, and classical music are prominent during waiting times. Potential irritations include impersonal treatment (44%) and staff behavior (41.8%). Music player usage within the settings of the dental clinic involves radios (49.3%) and headphones (41.0%). Correlations and predictors indicate associations between health status, music preferences, and noise disturbances. More specifically, visiting the university dental clinics (β = .300, p = .005) as well as younger age (β = .300, p = .034) were significant predictors of better perceived health status. Clearer perception of external sounds while using the music player (β = .190, p = .039) was a significant predictor of better perceived health status, while poorer health was predicted by the preference of Greek folk songs (β = -.200, p = .030). Also, the use of smartphones for playing music was related to poorer health (β = -.370, p < .001). Following, younger age (β = -.270, p = .015), lower education (β = -.210, p = .035), higher noise sensitivity (β = .190, p = .027), as well as feelings of anxiety and nervousness due to ambient noise from people and machines (β = .510, p = .027) were significant predictors of noise disturbance from machines. Also, visiting private clinics (β = .240, p = .018), preferences of specific playlist (β = .310, p = .012), no music (β = .280, p = .016) and use of smartphones to play music (β = .230, p = .029) were significant predictors of noise disturbance from patients or staff. Finally, the preference of listening to a specific playlist was related to better health status (r = .190, p < .05). Findings aim to optimize eco-soundscapes in dental offices, con-tributing to enhanced patient well-being. The research underscores the potential of music inter-ventions to alleviate dental anxiety and improve the overall dental experience and quality care.

Quality of life (QOL) is based on their perception of their position in life in respect to their goals, expectations, standards, and concerns, as well as their culture and value systems, their workflow and workplace situations while it influences quality of services. In this study we aim to report on dental and nursing academians’ QOL and well-being at the end of the third year of the COVID-19 pandemic. The World Health Organization Quality of Life-BREF Scale (WHOQOL-BREF) tool, recording Physical, Psychological, Social and Environmental dimensions of QOL, was used. The WHOQOL-BREF was modified on a spiritual, coaching/mentoring approach in a two-step designing and validated procedure. The modified SHQOL-BREF (Spiritual Healthcare version) designed for this study, was uploaded, and filled in online during April-June 2023. Staff (N=120, 75% female) of both departments of Dentistry (44.2%) and Nursing (55.8%) of the National and Kapodistrian university of Athens, participated in anonymity. QOL in terms of physical health was reported at a higher level (M=72.2 points) compared to social relationships (M=69 points), psychological health (M=65 points) and environment (M=59 points) (scores reported in 0-100 score). Overall QOL was rated at 66 points while satisfaction from health at 72 points. Job satisfaction (M1=3.2) and spirituality (M2=3.0) were reported at a medium level in a 5-point scale, while personal beliefs and values were reported at a high level (M3=4.0). Participants age presented a significant, moderate to strong effect on physical health [F(3,97)=2.89, p&lt;.05, η2p=.08] and on environment [F(3,97)=2.80, p&lt;.05, η2p=.08] and marital status on social relationships [F(1,97)=9.66, p&lt;.05, η2p=.09]. Married participants reported consistently higher levels of QOL compared to single participants, for all age groups. Department had a significant moderate effect on social relationships (F(1,97)=5.10, p&lt;.05, η2p=.05) and education a significant moderate to strong effect on psychological health (F(2,97)=3.74, p&lt;.05, η2p=.07). PhD level participants in both departments presented higher levels of psychological health compared to lower educational levels. Also, participants from the department of Dentistry reported higher levels of social relationships QOL in all educational groups, compared to the department of Nursing. Strategic planning on sustainability and QOL initiatives should be introduced after the COVID-19 pandemic for dental and nursing academic personnel to promote resilience and QOL scores.

This paper explores the overall picture regarding security systems in healthcare through an extensive review of the literature. As the healthcare sector has now become digitalized, the security of healthcare systems and, by extension, the protection of patient data is a key concern in the modern era of technological advances. Therefore, a secure and integrated system is now essential. Thus, to evaluate the relationship between security systems and healthcare quality, we conducted literature research to identify studies reporting their association. The timeline of our review is based on published studies covering the period from 2018 to 2024, with entries identified through a search of the relevant literature, focusing on the most recent developments due to advances in artificial intelligence and algorithmic approaches. Thirty-three studies were included in our final survey. Our findings underscore the critical role of security systems in healthcare that significantly improve patient outcomes and maintain the integrity of healthcare services. According to our approach, the studies analyzed highlight the growing importance of advanced security frameworks, especially those incorporating artificial intelligence and algorithmic methodologies, in safeguarding healthcare systems while enhancing patient care quality. According to this study, most of the research analyzed uses algorithmic technology approaches, many researchers prove that ransomware is the most common threat to hospital information systems, and more studies are needed to evaluate the performance of the systems created against this attack.

Background and Objectives: Low-density lipoprotein cholesterol (LDL-C) is a marker of cardiovascular risk and its management. This study evaluated LDL-C control trends in patients treated at a single healthcare centre in Lithuania. Materials and Methods: The study was conducted at the primary healthcare centre Saulės šeimos medicinos centras. Five-year (2019-2023) data on patients aged 40 years or older diagnosed with dyslipidaemia were extracted from a real-world data and analytics platform TriNetX. For analysis, patients were grouped into three groups: patients with dyslipidaemia only (control group), patients with dyslipidaemia and diabetes, and patients with dyslipidaemia and cardiovascular disease (CVD). The following LDL-C goals were used for analysis: &lt; 1.4 mmol/L (a goal for very-high-risk patients in primary or secondary prevention), &lt; 1.8 mmol/L (a goal for high-risk patients), and &lt; 3.0 mmol/L (a goal for low-risk patients). Results: There were 18646 patients with dyslipidaemia. Of them, 8.9% of patients had diabetes and 3.1% of patients had CVD. The median LDL-C concentration was significantly lower in patients with diabetes (2.82 mmol/L, p &lt; 0.05) and in patients with CVD (2.45 mmol/L, p &lt; 0.05) than in the control group (3.35 mmol/L). A trend of decreasing median LDL-C over the years was observed in all groups, with the lowest median values in 2023. The proportion of patients with LDL-C level &lt; 3 mmol/L increased from 32.0% in 2019 to 41.5% in 2023. The proportion of diabetic patients achieving LDL-C &lt; 1.8 mmol/L increased from 7.4% to 25.9% and those achieving LDL-C &lt; 1.4 mmol/L increased from 3.1% to 10.6%. The proportion of patients with CVD achieving LDL-C &lt; 1.8 mmol/L increased from 14.2% to 36.6% and those achieving LDL-C &lt; 1.4 mmol/L increased from 3.0% to 14.0%. Conclusions: Trends in the control of LDL-C levels are positive over 5 years, but a significant proportion of patients still did not reach the recommended target levels.

Introduction: Rural areas face additional challenges in preventing, preparing for, responding to, and recovering from disasters. This study aimed to understand how rural General Practitioners PHCPs perceive their roles, involvement, and capacity in disaster health management. Methods: For this qualitative descriptive research, semi-structured interviews were carried out with convenience and purposive samples of rural PHCPs before and during the COVID pandemic. Open, axial, and selective coding were employed to analyse the data inductively. Results: five interviews were conducted pre-COVID and ten interviews during the second and third waves of COVID. Identified themes were similar between the two periods. Rural PHCPs were underutilised due to a lack of awareness of their capacity and a lack of infrastructure and support for greater involvement. Conclusion: Rural PHCPs can be better integrated and supported in readiness for a whole of system response to future disasters.

The recent growth of wearable medical device technology in the form of fitness trackers, smart watches, smartphone apps, and patient monitoring systems has created people-generated health data (PGHD) that may benefit medical science with large amounts of continuous real-world data. The prevalence of these devices speaks to their broad popularity and user-friendliness and may lead us one day to a more fully “connected healthcare system.” Meanwhile, data security, confidentiality, and privacy issues have emerged in these hackable systems. Despite the promise of anonymized data, data can sometimes be re-identified, but even without that step, data breaches may reveal information (name, address, date of birth, social security number, and so on) sufficient for identity theft. Clinicians are often asked about the utility and value of wearable devices or monitors, but most are unaware that data from these systems may be transmitted, stored, and even sold without the user’s specific knowledge. Despite the confidentiality of medical information, cybersecurity surrounding wearables and monitors remains relatively lax, making them comparatively easy targets for cyber-villains. It is also important that efforts be taken to make PGHD more secure, since medical data may have great value to telehealth applications and AI-physician assistants. Clinicians should take an active role in informing patients about both risks and benefits of wearables and similar devices.

Delving into the transformative role of digital health in Nigeria's remote communities, aiming to bridge healthcare gaps and enhance overall well-being. As digital interventions gain prominence, their impact on healthcare accessibility, quality, and awareness becomes pivotal in the unique context of remote regions. We explore the historical overview of digital health initiatives in Nigeria, contextualize healthcare challenges, and analyse the global and regional influences shaping digital health adoption. Challenges such as digital literacy, infrastructural constraints, and cultural barriers are addressed alongside solutions, emphasizing the need for inclusive policies and community engagement. Through examining the quantitative and qualitative impacts of digital health interventions, including telehealth, mobile applications, and electronic health records, we unveil the strides made in healthcare delivery. Voices from communities, healthcare providers, and leaders provide first-hand perspectives, offering insights into the effectiveness and challenges faced. Additionally, policy implications, grassroots advocacy, and collaborative efforts between public and private sectors are discussed as integral components for sustainable change. As we measure the data-driven insights and envision future directions, this article advocates for a comprehensive and inclusive approach to digital health, envisioning a future where remote communities in Nigeria experience improved healthcare outcomes and resilience.