The emergence of blockchain know-how currently presents the opportunity for the health sector to adopt such technologies in electronic health records. Blockchain assists in maintaining and sharing the relevant medical records of the patient with the relevant group of healthcare providers and the hospital. Numerous specific applications include traceability of drug and patient monitoring or Electronic Health Records (EHR). While Blockchain assists in maintaining and sharing the relevant medical records of the patient with the relevant group of healthcare providers and the hospital, it is important to note that the moral consciousness of the healthcare professionals is the main guide of the moral consciousness is ethics. This paper presents an overview of the application of blockchain in the healthcare and medical sector, highlighting the specific challenges and concerns. The study adopted a systematic review of secondary literature in answering the research question.

In this ‘New Normal' post-COVID-19 modern world, people's health is becoming increasingly important to track. An advanced technology that uses sensory instruments to track and record critical parameters and communicates with others is the need of the time. It's difficult to keep track of all of the medical parameters and post-operative data of people with non-communicable diseases like diabetes and heart disease on a continuous basis. The system discussed here to be designed for patients who are confined to their homes, particularly when going out and being exposed to the outer world is prohibited. This paper proposed a groundbreaking health management system based on the Internet of Things (IoT) for accessing patient medical parameters in both local and remote areas. When a person's wellbeing becomes urgent, this initiative seeks to send an emergency alert to family members or loved ones. A cloud server records data from the patient's temperature sensor and pulse sensor; the data is analyzed using support vector machine algorithms to identify irregular conditions, and an emergency message is sent to the rest of the family via a mobile application, as well as a warning message to the nearest hospital.

1) Background: Capturing patients’ medical histories significantly influences clinical decisions. Errors in this process lead to clinical errors, increase costs and dissatisfaction among physicians and patients. Physicians in developing countries are overloaded with patients and cannot always follow the proper history-taking procedure. The challenges are acknowledged; however, a comprehensive understanding of the status and the remedies remained unexplored. 2) Objective: This paper aims to investigate the workload, history-taking challenges, and the willingness of the physicians to accept digital solutions. 3) Methods: A cross-sectional online survey was conducted on 104 physicians across Bangladesh, featuring 22 questions regarding their professional environment, workload, digitization status of health records, challenges in history-taking, and attitudes toward adopting digital solutions for managing patient histories; 4) Results: 92.67% of the physicians face workloads, 88.46% struggle in medical history-taking, and only 4.81% use digital medical records. About 70% struggle to complete the necessary history-taking steps, emphasizing the urgent need for solutions. An AI-based Smart Health Gantt Chart (SHGC) system has been introduced for their instant feedback. 93.27% of physicians expressed their willingness to use such a system. 5) Conclusions: The proposed SHGC has the potential to enhance healthcare efficiency in developing nations, benefit physicians, and improve patient-centered care.

Healthcare sector is a truly dynamic and multidisciplinary system. Progressive practice of computational technologies in healthcare has enhanced electronic therapeutic measures in the care units. The healthcare decision-makers are accenting on the operational usage of digital technology in the system, to improve the health service by reducing human error and excessive load also by increasing possibility to attend more patients simultaneously. Sophisticated medical instruments are using advanced robotics, artificial intelligence to enhance their efficacy. Virtual treatments, self-diagnostics is increasing over time with the advancement of technical support in health. Electronic Health Records (EHR) of patients has created huge medical data (clinical information), which is undoubtedly a good resource for health professionals to take critical decisions and implement them accordingly. The aim of this article is to elucidate how technological developments are associated with clinical improvements in terms of constructing an upgraded health ecosystem. It is imperative to analyze how recent digital paradigms in health are helping to tackle regular and rare clinical challenges.

International migrants comprised 14% of the UK population in 2020, but migrant health in the UK has rarely been studied at a population level using primary care electronic health records (EHRs). Given the difficulty of determining migration status using EHRs, this study developed a migration phenotype and assessed its validity. We developed a phenotyping algorithm using codes for country of birth, visa status, non-English main/first language and non-UK origin. It was applied to a Clinical Practice Research Datalink (CPRD) GOLD database of 16,071,111 primary care patients between 1997 and 2018. We compared the completeness and representativeness of the identified migrant population to Office for National Statistics (ONS) country of birth and 2011 census data by year, age, sex, geographic region of birth and ethnicity. Between 1997-2018, 403,768 migrants (2.51% of the CPRD GOLD population) were identified using the phenotype. 178,749 (1.11%) of these migrants were identified by codes indicating foreign country of birth or visa status, 216,731 (1.35%) a non-English main/first language, and 8,288 (0.05%) non-UK origin. The cohort was similarly distributed compared to ONS migration statistics in terms of sex and region of birth. Recording of migration improved from identifying approximately one-tenth of the expected proportion of migrants according to the ONS in 2004 to a quarter in 2018. Younger migrants were better represented than those aged 50 and over. The migration phenotype identified a large number of migrants and can be used to undertake large-scale migration health research in CPRD GOLD to inform healthcare policy, practice and action. While the cohort was representative of the UK migrant population in terms of sex and region of birth, migration status was under-recorded in earlier years and older ages, and future studies for these groups should therefore be interpreted with caution.

Management of a healthcare unit demands high prerequisites. It is a challenging organizational job for the healthcare decision-makers or leaders to tackle biomedical threats and deliver care service to huge number of affected populations in different demographic area. Health administration take innovative strategies to provide fundamental and life-saving services to the patients, when keeping the safety of the frontline medical workers is undoubtedly a priority. COVID-19 pandemic has changed the overall functioning of the healthcare system globally with alteration in the health decision-making protocols. Through this article, I have elucidated the challenges of healthcare along with today’s managerial paradigms to tackle the problems and run the system in a regulated manner.

The ageing of the population is growing significantly and will challenge healthcare systems. Chronic diseases in the older population require a change in service delivery, and new technologies can be a key element in ensuring the viability and sustainability of these systems. However, the generation gap and the physical and cognitive decline commonly associated with the older generation are barriers to the transition to these models of care. Despite this, there has been a trend towards digital healthcare, which has many potential benefits for the older population. Numerous studies have assessed the acceptability of new technologies for older people in health care. These studies highlight the importance of perceived usefulness, compatibility, ease of use and personalisation of the technology. Personalisation is necessary to ensure that the system is useful for users, and different characteristics such as country of origin, gender, age or comfort with the technology should be taken into account. A person-centred approach in the development of new health technology systems is essential to ensure that applications can be better tailored to the needs of different ageing populations. Many organisations have dedicated time and resources to ensure a person-centred approach in the development of new health technology systems, and putting the individual first is the best way forward in digital health. This article presents the work carried out in this regard in the framework of the European TeNDER project together with an analysis of the results obtained in terms of satisfaction, usefulness and usability by end users.

Biobanks linked to electronic health records provide a rich data resource for health-related research. With the establishment of large-scale infrastructure, the availability and utility of data from biobanks has dramatically increased over time. As more researchers become interested in using biobank data to explore a diverse spectrum of scientific questions, resources guiding the data access, design, and analysis of biobank-based studies will be crucial. The first aim of this review is to characterize the types of biobanks that are discussed in the recent literature and provide detailed descriptions of specific biobanks including their location, size, data access, data linkages and more. The development and accessibility of large-scale biorepositories provide the opportunity to accelerate agnostic searches, new discoveries, and hypothesis-generating studies of disease-treatment, disease-exposure and disease-gene associations. Rather than spending time and money designing and implementing a single study with pre-defined objectives, researchers can use biobanks’ existing data-rich resources to answer scientific questions as quickly as they can analyze them. While the data are becoming increasingly available, additional thought is needed to address issues related to the design of such studies and analysis of these data. In the second aim of this review, we discuss statistical issues related to biobank research in general including study design, sampling strategy, phenotype identification, and missing data. These issues are illustrated using data from the Michigan Genomics Initiative, UK Biobank, and Genes for Good. We summarize the current body of statistical literature aimed at addressing some of these challenges and discuss some of the standing open problems in this area. This work serves to complement and extend recent reviews about biobank-based research and aims to provide a resource catalog with statistical and practical guidance to researchers pursuing biobank-based research.

This work presents the computation of reliable warming trends for central Australia around Alice Springs within a circle of radius 1,000 km. Between 1880 and 2011, the average warming for the centre of Australia is +0.166 ºC/century, slightly smaller than the warming of Alice Springs, that is +0.176 ºC/century. Over a shorter time between 1910 and 2011, the centre of Australia is warming +0.794 ºC/century, slightly more than the warming of Alice Springs, that is +0.719 ºC/century.

Background: Internal migrants had obstacles in accessing local public health services in China. This study aimed to estimate the utilization of local public health services and its determinants among internal migrants. Methods: Data were from the 2014 and 2015 nationally representative cross-sectional survey of internal migrants in China. Multivariate logistic regressions were used to estimate the relationship between socioeconomic, migration, demographic characteristics and public health services utilization. Results: Internal migrants in more developed eastern regions used less public health services. Those with higher socioeconomic status were more likely to use public health services. The broader and shorter they migrated, the less they used public health services. Compared to migration within the city, migration across provinces is negatively associated with health records (OR=0.88, 95% CI: 0.86-0.90), health education (OR=0.97, 95% CI: 0.94-1.00), and health education on NCDs (OR=0.92, 95% CI: 0.89-0.95) or through Internet channel (OR=0.96, 95% CI: 0.94-0.99). Conclusion: Public health services coverage for internal migrants has seen great improvement due to government subsides. Internal migrants with lower socioeconomic status and across provinces need to be targeted. More attention should be given to the local government in the developed eastern regions in order to narrow the regional gaps.

(1) Background: The aim of this study was to identify predictors of the unmet health care needs during the financial and recent health crisis in Greece. (2) Methods: Time series analysis was performed for the years 2008 through 2022 using the Eurostat database. The dependent variable was the percentage of people who reported unmet need for medical care. Demographic, socioeconomic and health data as well as health expenditures were used as independent variables. Correlation analysis and simple linear regression models were conducted to analyze the results. (3) Results: Unmet health needs in Greece increased from the start of the crisis until 2016, as a gradual de-escalation of the crisis is observed. However, in 2019 the country recorded the second highest level of unmet needs for medical care before the health crisis. People with limitations in usual activities, those who report bad/very bad health status, unemployed and with low-income increased the likelihood of unmet needs. Health expenditures (public or private) were also significant determinants of unmet healthcare needs. (4) Conclusions: The increased unmet health needs widen inequalities in health and healthcare access. Therefore, health policy should eliminate barriers which restrict the access to health and enhance healthcare services, developing conditions for citizens' well-being.

We performed an epi and molecular characterization of two healthcare workers MPXV occupational infection. Five days after the sampling collection, nurses developed typical MPXV infection symptoms. Infection was confirmed by qPCR and whole genome sequencing. The most likely transmission route was through contact with fomites in the patient belonging/house.

This literature review was aimed to identifying the opportunistic bacterial pathogens that can be transmitted by contaminated food and represent a current threat for patients particularly suscep-tible to infections because of underlying conditions or predisposing factors. The analysis was focused on recent case or outbreak reports, and systematic reviews published in years 2019 - 2023 and resulted in sorting 24 bacterial groups comprising genera or species able to cause a variety of systemic or invasive infections if ingested with food or drinking water. These included both bacteria known to cause mild infections in immunocompetent persons and bacteria considered innocuous that are used in food fermentation or as probiotics. No recent cases from dietary routes were reported for bacteria of critical importance as nosocomial pathogens and widely occurring in food products, primarily, Acinetobacter baumanii and Klebsiella pneumoniae. However, the very first sources of their introduction in the clinical environment still need to be estab-lished. In many instances, risky dietary habits such as eating raw fish, seafood, raw meat, unpasteurized milk and derived products or the lack of control on fermentation processes led to the reported illnesses, pointing out to the necessity to improve the hygiene of production and consumer’s awareness of risks.

The contemporary landscape of eHealth is characterized by major concerns related to electronic medical records (EMRs). In an EMR, critical patient health information gets its own repository, which is the core of the eHealth system. Notably, the EMR not only retrieves health information generated in ambulatory clinical settings but also includes court-generated records. These overlapping records assume the role of a foundational data source for a comprehensive electronic health record (EHR). This scholarly review sheds light on recent trends in medical records and associated challenges, while at the same time providing insights into Saudi Arabia’s targeted approaches to healthcare delivery. Additionally, the talk expands to include a description of blockchain technology and its underlying conceptual framework. This demonstration positions blockchain technology as a promising approach that requires consideration for future use in the healthcare system.

A patient will visit physicians when he/she feels ill. This illness is not for COVID-19 but it is a general tendency of human being to visit doctor probably it can not be controlled by general drug. When a patient comes to a doctor, the doctor examines him/her after knowing his/her problem. The physician always asks him/her about some questions related to him/her daily life. For example, if a young male patient comes to a doctor with a symptom of fever and cough, the first question doctor asked him that he has a habit of smoking. Then doctor asks him whether this type of symptom appeared often to him previously or not. If the answers of both questions are yes, then the first one is habit and the second one is that he may suffering from some serious disease or a disease due to the weather. The aim of this paper is to consider habit of the patient as well as he/she has been affected by a critical disease. This information is used to build a model that will predict whether there is any possibility of his/her being affected by COVID-19. This research work contributes to tackle the pandemic situation occurred due to Corona Virus Infectious Disease, 2019 (Covid-19). Outbreak of this disease happens based on numerous factors such as past health records and habits of patients. Health records include diabetes tendency, cardiovascular disease existence, pregnancy, asthma, hypertension, pneumonia; chronic renal disease may contribute to this disease occurrence. Past lifestyles such as tobacco, alcohol consumption may be analyzed. A deep learning based framework is investigated to verify the relationship between past health records, habits of patients and covid-19 occurrence. A stacked Gated Recurrent Unit (GRU) based model is proposed in this paper that identifies whether a patient can be infected by this disease or not. The proposed predictive system is compared against existing benchmark Machine Learning classifiers such as Support Vector Machine (SVM) and Decision Tree (DT).

Switzerland, a wealthy country, has a cutting-edge healthcare system, yet per capita, it emits over one ton of CO2, ranking among the world's most polluting healthcare systems. To estimate the carbon footprint of the healthcare system of Geneva’s canton, we collected raw data on the activities of its stakeholders. Our analysis shows that when excluding medicines and medical devices hospitals are the main greenhouse gas emitter by far, accounting for 48% of the healthcare system’s emission, followed by nursing homes (20%), private practice (18%), analysis laboratories (7%), dispensing pharmacies (4%), the homecare institution (3%) and the ambulance services (

Artificial Intelligence (AI) in healthcare has ushered in a revolutionary era by transforming the way we provide care and reduce adverse consequences. This paper explores the field of AI applications in healthcare, including side effect management, streamlined administrative procedures, and customized treatment programs.

The 26 June 1917 tsunamigenic earthquake in Samoa is considered the largest historical event on record to have impacted this region in terms of earthquake magnitude and intensity. Yet, very little is known about the scale and distribution of tsunami impacts compared with the recent 2009 event which originated about 150 km east along the subduction zone bend of the Northern Tonga Trench (NTT). In this study we set out to: 1) reconstruct the 1917 tsunami from source to inundation to understand its hazard risk characteristics in the Samoan islands of Savai’i and Upolu; and 2) assess the hazard implications of tsunamis sourced from different locations along the subduction zone bend of the NTT on present-day exposure of coastal assets relative to the 2009 tsunami benchmark. We use the BG-Flood numerical modelling suite to produce model outputs representing inundation extent and hazard depth intensities at spatially flexible grid resolution (10 m, 20 m and 40 m). These are validated using available tide gauge records in Apia harbour and limited observations of runup that were derived from historical records. We then combine the inundation model with available digital distributions of buildings in the RiskScape multi-hazard risk analysis software, to produce exposure metrics for understanding the likely impacts on present-day coastal asset and population distributions if a similar tsunami were to occur. Results of the tsunami modelling indicate variable modelled-to-observed consistency using available source models, wave and runup validation data. Discrepancies in recorded vs modelled wave arrival time at Apia of between 30—40 mins are observed, with modelled runup underestimated in southeast Upolu Island compared with the rest of the country where runup observations are available (e.g., Savai’i Island). These differences likely reflect complexities in the tsunami source mechanism which might not currently be represented in our modelling. Nevertheless, our results suggest that a larger proportion of people would be exposed in Savai’i island (71% of exposure total), compared with Upolu island if a characteristic 1917-type event were to occur. While this study provides the first detailed inundation model of the 1917 tsunami in the Samoan region, the observed discrepancies suggest that further investigation is required to constrain potential tsunami source complexities which might not be accounted for in this study. Notwithstanding these limitations, our findings help to reinforce an appreciation of the risk to the greater Samoan region faced by local tsunamis sourced at different locations along the subduction zone bend of the NTT.

The medical sector is of the utmost importance in every country for well-known reasons such as their economic development, national security, quality of life, and so on. Many researchers were dedicated to this topic, however, in Romania there are limited studies on this subject. One reason is that most of the businesses in this sector are individual enterprises or small family businesses. In our research paper we deploy several analysis methods to see the financial sustainability of companies operating in the medical industry. By analyzing a sample of 23931 companies and we have concluded that their performance has increase in the peak of the pandemic and that the financial stability is high. Our results are in line with other similar studies that were conducted in other regions.

Three autonomous communities have been the ones that, in the 2022-2023 season, anticipated the document approved by the Public Health Commission, recommending influenza vaccination for all children aged 6 to 59 months. The main objective of this work is to evaluate the attitude of healthcare professionals towards the first universal vaccination campaign in our region, as well as the acceptability of the vaccines used and the attitude towards the piloting of school vaccination. Cross-sectional, survey-based, descriptive study. All healthcare professionals involved in the campaign were invited to participate. The 91.9% of surveyed professionals thought that flu vaccination from 6 to 59 months was important or very important. 89.8% had previous experience regarding the intramuscular vaccine. The professionals valued the intranasal vaccine significantly more positively; however, there were no differences when asking for each of the vaccines without comparison. The inhaled vaccine was preferred by 97.5% for the following campaign. Piloted school vaccination showed 75% acceptance. The inhaled vaccine was preferred by most professionals and the piloted school vaccination was highly accepted, and independently associated to the importance of vaccination as considered by physicians, being a medical doctor, and participation in the pilot program.

In the context of the COVID-19 pandemic, thousands of healthcare workers (HCWs) infected with COVID-19 have lost their lives worldwide. At the early stage of the epidemic, when COVID-19 was still not considered as a pandemic, a large number of Chinese HCWs were infected. Officials reported that more than 3,000 HCWs in Hubei contracted the virus at the early stage of the outbreak due to limited knowledge of the virus. Following reports of overloaded local hospitals, more than 42,000 medical staff, including those from the military, were dispatched to Hubei from across the country. At the peak of the fight, one in 10 intensive care medics in China were working in Wuhan. During fighting against COVID-19 in China, although a large number of HCWs were infected by SARS-CoV-2 in the early stages of the epidemic, the timely adoption of measures indicated that, a faster rate of diagnosis could be achieved, patients were isolated in-time, HCWs’ safety was prioritized, training on basic protective knowledge and unified management of HCWs was strengthened, and effective protective measures were implemented. This resulted in the accomplishment of zero SARS-CoV-2 infection among the 42,632 members of the national medical teams sent to Hubei, and the number of COVID-19 cases among HCWs in local hospitals also significantly decreased, thereby indicating that hospital-acquired infections of SARS-CoV-2 among HCWs are fully preventable.

Thromboprophylaxis of hospitalized patients at risk of venous thromboembolism (VTE) presents challenges owing to patient heterogeneity and lack of adoption of evidence-based methods. Intuitive practices for thromboprophylaxis have resulted in many patients being inappropriately prophylaxed. Multiple interventions for thromboprophylaxis have been tested, including use of multifaceted approaches such as national VTE prevention programs with audits, use of passive alerts (either human or electronic), and more recently use of active clinical decision support (CDS) tools incorporated into electronic health records (EHRs). Multifaceted health-system interventions have shown mixed results in their ability to increase appropriate thromboprophylaxis and reduce VTE, unless mandated through a national VTE prevention program, though the latter approach is potentially costly, effort- and time-dependent. Studies utilizing passive human or electronic alerts have also shown mixed results in increasing appropriate thromboprophylaxis and reducing VTE. The use of active CDS tools holds the greatest promise, especially with further refinement and widespread implementation within various EHRs and clinical workflows. Recent-ly a universal cloud-based and EHR-agnostic CDS VTE tool revealed high adoption and effectiveness in increasing appropriate thromboprophylaxis and reducing major thromboembolism. This narrative review summarizes the literature on system-wide thromboprophylaxis interventions in hospitalized patients, with a focus on CDS tools.

Cloud computing appears to be the dreamed vision of the healthcare industry; it refers to means of storing and accessing data and programs over the internet instead of the computer’s hard drive. However, the adoption of cloud computing requires solving several issues and infor-mation privacy is a major one. This work proposes a cloud architecture design for the healthcare information system. The proposed architecture enables for storing and sharing information in a privacy-preserving manner. Patients’ information in the proposed architecture is divided into four categories identified in the case study data analysis. User identity management protocol (U-IDM) is employed for controlling the access to patients’ information, and patients have means of control over who can access their information. A scenario-based instantiation validated the proposed architecture's privacy-preserving patient data exchange. The instantiation proved that the proposed architecture allows sharing healthcare information without violating the privacy of patients.

Documenting prehistoric and historical hemp retting for fiber extraction is important in the study of human uses of this iconic plant and its cultural implications. In paleoecology, hemp retting is usually inferred from indirect proxies, notably anomalously high percentages of Cannabis pollen in lake sediments, but some recent studies have also used specific molecular biomarkers (cannabinol, Cannabis DNA) as a more straightforward evidence. Here we provide direct evidence of hemp retting by identifying phylogenetic signatures (16S rRNA genes) from pectinolytic bacteria actually responsible for the fermentation process that separates the fiber from the stalk, namely Bacillus, Clostridium, Escherichia, Massilia, Methylobacterium, Pseusomonas, Rhizobium and Rhodobacter. These analyses have been performed in the sediments from an Iberian lake previously considered as an important hemp retting site during the last five centuries, on the basis of Cannabis pollen abundances. The good match between biomarker and pollen evidence, in the context of the recent historical development of hemp industry in Spain, can be useful to interpret paleoecological records from other similar lakes in the way toward a more regional view on the introduction, spreading, uses and associated cultural connotations of Cannabis in the Iberian Peninsula within European and Mediterranean contexts.

Medical records contain many terms which are difficult to process. Our aim in this study is to allow the visual exploration of the information in medical databases where the texts presents a large number of syntactic variations and abbreviations, through an interface which facilitates content identification, navigation and information retrieval. We propose the use of multi-term tag clouds as content representation tools and as assistants for the browsing and querying tasks. The tag cloud generation is achieved through a novelty mathematical method that allows related terms to remain grouped together within the tags To evaluate this proposal, we have used a database with 24,481 records. 23 expert users in the medical field were tasked to complete a survey to evaluate the generated tag clouds properties and we obtained a precision of 0.990, a recall of 0.870 and a F1score of 0.904 in the evaluation of the tag cloud as an information retrieval tool. The main contribution of this approach is that we automatically generate a visual interface over the text capable of capturing the semantics of the information and facilitating access to medical records.

Electronic health records (EHRs) are becoming a vital source of data for healthcare quality improvement, research, and operations. However, much of the most valuable information contained in EHRs remains buried in unstructured text. The field of clinical text mining has advanced rapidly in recent years, transitioning from rule-based approaches to machine learning and, more recently, deep learning. With new methods come new challenges, however, especially for those new to the field. This review provides an overview of clinical text mining for those who are encountering it for the first time (e.g. physician researchers, operational analytics teams, machine learning scientists from other domains). While not a comprehensive survey, it describes the state of the art, with a particular focus on new tasks and methods developed over the past few years. It also identifies key barriers between these remarkable technical advances and the practical realities of implementation at health systems and in industry.

We report new findings of live specimens of Nassarius persicus (Martens, 1874) and N. tadjallii Moolenbeek, 2007, extending their range to the Gulf of Kachchh, Gujarat, India. The known distribution of both species was limited: N. persicus was distributed in the Persian Gulf, Gulf of Oman and Karachi, Pakistan; N. tadjallii was reported from the Persian Gulf and Gulf of Oman. We also provide comprehensive taxonomic descriptions of both species, along with additional morphological and ecological information.

Many reported sea level records are often not a single measurement. They are then a composition of different records from several tide gauges. Sometimes, they are from the same tide gauge, but the tide gauge stability has been affected by earthquakes. This is the case of Guam as discussed in the present manuscript. The claimed sea level acceleration of Guam is only the result of two earthquakes that have compromised the stability of the tide gauge.

Objectives: This study aimed to analyze the awareness of local residents regarding healthcare projects and to suggest some ideas for the revision of local ones. Methods: To delve into the opinions of local residents, the author of this study created a questionnaire composed of eight questions on the general characteristics of the respondents, eight questions on satisfaction with health centers, 16 questions on the awareness of healthcare projects, and 22 questions on local healthcare. The survey was conducted for 409 residents who visited public centers in Gimcheon from 15 March to 14 April 2021. Results: Data analysis revealed the following: The proportion of local residents who use health centers was 39.1%, and those users visit health centers, on average, 3.92 times a year. Among healthcare projects, the project known by the highest proportion of people was vaccinations (84.5%), which was also the project that was most used (38.1%). Among healthcare projects needed in the with-COVID-19 age, respondents awarded the highest score to vaccinations (4.15 points on a five-point Likert scale) and the second highest score to infectious disease management (4.12). Conclusions: For healthcare projects, central and local governments should focus on activating vaccinations, solving the problem of medical accessibility through untact remote treatment and establishing national infectious disease-specializing hospitals and local infectious disease management based on such national hospitals.

Photoplethysmography (PPG) is widely utilized in wearable healthcare devices due to its convenient measurement capabilities. However, the unrestricted behavior of users often introduces artifacts into the PPG signal. As a result, signal processing and quality assessment play a crucial role in ensuring that the information contained in the signal can be effectively acquired and analyzed. Traditionally, researchers have discussed signal quality and processing algorithms separately, with individual algorithms developed to address specific artifacts. In this paper, we propose a quality-aware signal processing mechanism that evaluates incoming PPG signals using signal quality index (SQI) and selects the appropriate processing method based on the SQI. Unlike conventional processing approaches, our proposed mechanism recommends processing algorithms based on the quality of each signal, offering an alternative option for designing signal processing flows. Furthermore, our mechanism achieves a favorable trade-off between accuracy and energy consumption, which are the key considerations in long-term heart rate monitoring.

The management of large medical files is a critical challenge in the health sector. Conventional systems have security, scalability, and efficiency deficiencies. This project proposes a hybrid architecture between blockchain and cloud computing to address these challenges. Blockchain ensures the immutability and traceability of medical records, while the cloud allows scalable and efficient storage. Together, these technologies can transform data management in electronic health record applications. The essential objective of this research is to thoroughly look at the existing strategies, devices, and conventions that encourage a secure interaction between blockchain applications and the cloud. Special emphasis is set on maintaining the integrity and security of the blockchain while tackling the potential and efficiency of cloud infrastructures. Through a meticulous investigation of these approaches, along with their successful usage and encountered challenges, this paper offers a comprehensive overview of the present state of this integration. Altogether, this paper does not propose new concepts or developments. Its central focus is to provide a comprehensive and insightful examination of the modern landscape concerning the integration of blockchain and cloud advances. By shedding light on the existing approaches and assessing their viability, this work aims to highlight the current challenges and build up a solid establishment for future development. This, in turn, will cultivate a consistent integration of blockchain security with the dynamic potential of cloud computing while guaranteeing information integrity and security remain uncompromised. In conclusion, this paper serves as a important resource for analysts, specialists, and partners looking for to dig into and development the integration of blockchain and cloud innovations, subsequently contributing to a more secure and productive cloud environment.

Pituitary adenomas are benign brain tumors that pose a heavy burden on patients worldwide. However, the local burden of disease is yet to be established due to scarcity of data. In line with this, this study aims to present the challenges and gaps in the treatment of pituitary adenomas in the Philippines. A scoping review of available relevant literature on epidemiology, clinical experience with treatment, health financing, and healthcare delivery system based on the Preferred Reporting Items for Systematic reviews and Meta-analysis guidelines extension for Scoping Reviews was conducted. The scarcity of updated local clinical data, inequity of distribution of resources, inadequate government support, and lack of affordable diagnostic testing, medications and neurosurgical procedures are the factors that hinder provision of adequate care of pituitary adenomas in the Philippines. There are notable treatment gaps in the management of pituitary adenomas in the Philippines, which may be addressed by strengthening universal healthcare. Strategies to address these gaps were proposed, including improving public-private insurance coverage, increasing manpower, enhancing accessibility to resources, and spreading more awareness.

Premortem clinical diagnoses and postmortem autopsy findings do not match throughout history. These clinicopathological discrepancies are expected to be raised during the coronavirus disease 2019 (COVID-19) pandemic due to increased pressure on healthcare. At the same time, autopsies and clinicopathological discrepancies accurately display the quality of the healthcare system. To assess that, we examined the relevant works of literature according to the PRISMA-based protocol. As discrepancy rate changes in the correlation to the length of stay in the hospital, we also checked whether studies with patients from the intensive care unit (ICU) differed in discrepancies significantly. We found overall risk differences pretty much alike in "pre-COVID" and "during the pandemic" groups of studies. Based on that, we concluded that healthcare quality did not drop significantly during the pandemic. Be it as it may, the pandemic exposed some shortcomings in mortem healthcare regarding consensus to the autopsy, organ retention, burial, and the postponed burial or the digitalization of post mortem healthcare. All of these issues should be addressed in the future.

This article focuses on the economic dimensions of maternal health, highlighting the benefits of investing in maternal healthcare and the policy implications for sustainable development. Through a comprehensive review of the literature, the article explores the economic impact of maternal health, including its effects on human capital, productivity, and healthcare costs. It emphasizes the importance of addressing social determinants such as access to healthcare services, education, employment, income, and geographical disparities. By prioritizing maternal health, societies can unlock the economic potential of women, promote inclusive growth, and reduce gender disparities. The article discusses policy interventions, including the importance of healthcare infrastructure, financial support for maternal healthcare, and promoting gender equality. It also emphasizes the need for future research to quantify the economic benefits and evaluate the cost-effectiveness of different interventions. Overall, the article underscores the economic imperative of investing in maternal health and provides valuable insights for policymakers and researchers seeking to enhance maternal health outcomes and promote sustainable economic development.

Human Activity Recognition (HAR) is a process to automatically detect human activities based on stream data generated from various sensors, including inertial sensors, physiological sensors, location sensors, cameras, time, and many others. Unsupervised contrastive learning has been excellent, while the contrastive loss mechanism is less studied. In this paper, we provide a temperature (τ) variance study affecting the loss of SimCLR model and ultimately full HAR evaluation results. We focus on understanding the implications of unsupervised contrastive loss in context of HAR data. In this work, also regulation of the temperature(τ) coefficient is incorporated for improving the HAR feature qualities and overall performance for downstream tasks in healthcare setting. Performance boost of 1.3% is observed in experimentation.

The Ministry of Health evaluates hospital management in accordance with the standard of quality of service. The concept of Shariah hospitals offers management services that exceed the standard of quality of hospital care. The study aims to illustrate the concept of Shariah hospitals in Indonesia. We collect related literature from various media via online search with the keywords “Shariah hospitals,” “implementation of Shariah hospitals,” and “application of Shariah hospitals.” Main findings: The study finds that the Shariah hospitals built by the philosophy of Islam are willing to provide the best health-care services to patients. A code of conduct must be fulfilled by the hospital management in Shariah hospitals: (1) general liability, (2) obligations to society and the environment, (3) obligations to patients, (4) obligations to the leaders, staff, and employees, and (4) relationships with related institutions. The foremost challenges include the improvement of health personnel performance and the quality of services in addition to perceptions that are not inclusive of the system of Shariah hospitals. This implementation should run consistently and with the commitment of all parties. Such insight, in turn, can be counted as an input to an approach to health services, particularly in increasing the performance rates, such as hospital. This study is the first to provide new insight into discussion about shariah hospital by presenting its focuses on Islamic approaches in meeting the quality standards of health services in hospitals so as to obtain more value. However, exclusive principles—Islamization, heterogeneity, and the performance of health workers—challenge the implementation of this hospital system.

Reflection in healthcare education is an emergent topic with many studies and reviews being published. The purpose of the present review is to map the literature in this field by performing a systematic review of reviews (umbrella review) and to explore which definitions and models are currently in use, how reflection impacts on design, evaluation and assessment and future challenges. Nineteen reviews were identified that satisfied inclusion criteria. Emerging themes were: reflection is currently portrayed as self-reflection and critical reflection with the epistemology-of-practice notion not being as much as expected in tandem with the evidence-based-medicine paradigm modern science advocates. Reflective techniques were recognised in multiple settings (e.g. summative, formative, group vs individual etc.) and have been associated with learning but assessment remains a research topic with issues of validity, reliability and replicability. Future challenges involve the epistemology of reflection in healthcare education and how to practice and assess reflection without losing its theoretical background.

Background: In a Beveridgean decentralized healthcare system, like the Italian one, where regions are responsible for their own health planning and financing, the analysis of patients’ migration appears very interesting as it has economic and social implications. The study aims to analyze both patients’ migration for hospital rehabilitation and if the beds endowment is a driver for these flows; Methods: from 2011 to 2019, admissions data were collected from the Hospital Dis-charge Cards database of the Italian Ministry of Health, population data from Italian National Institute of Statistics and data of beds endowment from the Italian Ministry of Health website. To evaluate patients’ migration, we used Gandy’s Nomogram, while to assess if beds endowments are mobility drivers, we have created two matrices, one with attraction indexes (AI) and one with escape indexes (EI). The beds endowment, for each Italian region, were correlated with AI and EI. Spearman’s test was carried out through STATA software; Results: Gandy’s Nomogram showed that only some northern regions had good hospital planning for rehabilitation. A statistically significant correlation between beds endowment and AI was found for four regions, while with EI for eight regions. Conclusions: Only some northern regions appear able to satisfy the care needs of their residents, with an attraction minus escapes positive epidemiological balance. The beds endowment seems to be a driver of Patients’ migration, mainly for escapes. Certainly, the search for mobility drivers needs further investigation given the events in Molise and Basilicata.

Background: Health Care Workers (HCWs) are at increased risk of acquiring and transmitting COVID-19 infection. Also, they present role models for communities with regards to attitudes towards COVID-19 vaccination. Hence, hesitancy of HCWs towards vaccination can crucially affect the efforts aiming to contain the pandemic. Previously published studies paid little attention to HCWs in Arab countries, which has a population of over 440 million. Objectives: to assess the rates of COVID-19 vaccine hesitancy in Arabic-speaking HCWs residing in and outside the Arab countries, and their perceived barriers towards vaccination. Methods: a cross-sectional study based on an online survey was conducted from 14-Jan 2021 to 29-Jan 2021, targeting Arabic-speaking HCWs from all around the world. Results: the survey recruited 5,708 eligible participants (55.6% males, 44.4% females, age 30.6±10 years) from 21 Arab countries (87.5%) and 54 other countries (12.5%). Our analysis shows a significant rate of vaccine hesitancy among Arabic-speaking HCWs residing in and outside Arab countries (25.8% and 32.8%, respectively). The highest rates of hesitancy were among participants from the west region of the Arab world (Egypt, Morocco, Tunisia, and Algeria). The most cited reasons for hesitancy were concerns about side effects and distrust in vaccine expedited production and healthcare policies. Factors associated with higher hesitancy included age of 30-59, previous or current suspected or confirmed COVID-19, female gender, not knowing the vaccine type authorized in the participant’s country, and not regularly receiving the influenza vaccine. Conclusion: this is the first large-scale, multinational, post-vaccine-availability study on COVID-19 vaccine hesitancy among HCWs. It reveals high rates of hesitancy among Arab-speaking HCWs. Unless addressed properly, this hesitancy can impede the efforts for achieving widespread vaccination and collective immunity.

This paper considers the reasonability of using GSDMM as a method for clustering short texts - titles and abstracts of publications 2021-2023 of MDPI journals on sustainable energy topics. The paper proposes an approach to identifying relevant research topics based on the use of the Python script Yake!, the Krovetz streamer, the GSDMM algorithm, and short text annotations. It is emphasized that researchers prefer to rely on specific publications rather than keywords when searching for information on a topic of interest. The bibliometric records of sustainable energy publications from 2021 to 2023 in Sustainability (Energy Sustainability section — 1,926 search results) and Energies (Sustainable Energy section — 994 search results) were used as data for analysis. The GSDMM algorithm was used to cluster the texts, and Yake! to extract the keywords for the GSDMM algorithm's vocabulary. This article summarizes topics found in 9 clusters, including general sustainable energy issues, biomass recycling, region-specific issues, building energy use, economic growth and investment, numerical flow modeling, generation cost optimization, heat to energy conversion, weather-related risks, and false data attacks.

Background: Administrative healthcare databases are widespread and are often standardized with regard to their content and data coding, thus they can be used also as data sources for surveillance and epidemiological research. Chronic dialysis requires patients to frequently access hospital and clinic services, causing a heavy burden to healthcare providers. This also means that these patients are routinely tracked on administrative databases, yet very few case definitions for their identification are currently available. The aim of this study was to develop two algorithms derived from administrative data for identifying incident chronic dialysis patients and test their validity compared to the reference standard of the regional dialysis registry. Methods: The algorithms are based on data retrieved from hospital discharge records (HDR) and ambulatory specialty visits (ASV) to identify incident chronic dialysis patients in an Italian region. Subjects are included if they have at least one event in the HDR or ASV databases based on the ICD9-CM dialysis-related diagnosis or procedure codes in the study period. Exclusion criteria comprise non-residents, prevalent cases, or patients undergoing temporary dialysis, and are evaluated only on ASV data by the first algorithm, on both ASV and HDR data by the second algorithm. We validated the algorithms against the Emilia-Romagna regional dialysis registry by searching for incident patients in 2014. Results: Algorithm 1 identified 680 patients and algorithm 2 identified 676 initiating dialysis in 2014, compared to 625 patients included in the regional dialysis registry. Sensitivity for the two algorithms was respectively 90.8% and 88.4%, positive predictive value 84.0% and 82.0%, and percentage agreement was 77.4% and 74.1%. Conclusions: These results suggest that administrative data have high sensitivity and positive predictive value for the identification of incident chronic dialysis patients. Algorithm 1, which showed the higher accuracy and has a simpler case definition, can be used in place of regional dialysis registries when they are not present or sufficiently developed in a region, or to improve the accuracy and timeliness of existing registries.

The integration of Artificial Intelligence (AI) with Digital Twins (DTs) has emerged as a promising approach to revolutionize healthcare, particularly in the diagnosis and management of thoracic disorders. This study proposes a comprehensive framework, named Lung-DT, which leverages IoT sensors and AI algorithms to establish a digital representation of a patient’s respiratory health. Using the YOLOv8 neural network, the Lung-DT system accurately classifies chest X-Rays into five distinct categories of lung diseases, including "Normal," "Covid," "Lung Opacity," "Pneumonia," and "Tuberculosis". The system’s performance was evaluated on a chest X-Ray dataset, demonstrating an impressive average accuracy of 96.6% across all classes. Further tests (prediction) were conducted on the trained network using a third dataset available in the literature and completely unknown to the network, yielding an average accuracy of 98% across three classes. The proposed Lung-DT framework offers several advantages over conventional diagnostic methods. Firstly, it enables real-time monitoring of lung health through continuous data acquisition from IoT sensors, facilitating early diagnosis and intervention. Secondly, the AI-powered classification module provides automated and objective assessments of chest X-Rays, reducing dependence on subjective human interpretation. Thirdly, the twin digital representation of the patient’s respiratory health allows for comprehensive analysis and correlation of multiple data streams, providing valuable insights for personalized treatment plans. The integration of IoT sensors, AI algorithms, and DT technology within the Lung-DT system demonstrates a significant step towards improving thoracic healthcare. By enabling continuous monitoring, automated diagnosis, and comprehensive data analysis, the Lung-DT framework has enormous potential to enhance patient outcomes, reduce healthcare costs, and optimize resource allocation.

Ideas about Artificial Intelligence appeared about half a century ago, but only now is it becoming an essential element of everyday life. The data provided is getting bigger and bigger and, in this case, we need artificial intelligence that helps us with superhuman powers. The interaction with medicine is getting closer and closer, medicine being a field that continues to be perfected. Machine learning, deep learning, neural networks, computer vision are some of the mechanisms that are already applied in medicine, becoming a trend in healthcare worldwide. Artificial intelligence will be the thing that will change contemporary medicine. Developed countries such as Japan, France, Germany have already implemented artificial intelligence in their medical systems. The help is in medical diagnosis, patient monitoring, personalized therapy, and workflow optimization. Artificial intelligence will help surgeons to perfect their skills, to standardize techniques, to choose the best surgical technique. The goal is to predict complications, reduce diagnostic time, diagnose complex pathologies, guide the surgeon intraoperatively and reduce medical errors. We are at the beginning but the potential is enormous.

Background and Aims: The present study analyzed retrospectively the association between socioeconomic deprivation and graft and patient survival in a cohort of 2,568 adult recipients of a liver transplant between 1996 and 2022. Materials and methods: The primary exposure was a nationally validated socioeconomic deprivation index (DI) at census block level and ranking from 1-5, with higher ranks indicating more significant socioeconomic deprivation. Results: At a median (IQR) follow-up of 144.8 (204) months, the overall patient and graft survival rates were 92% and 90.4% at 1 year, 78.4% and 72.2% at 5 years, and 58% and 56.7% at 10 years. Recipients with a DI rank above the median (i.e., more deprived) had 1, 5, and 10-year patient and graft survival rates of 91% and 89.5%, 70.4% and 68.4%, 48% and 46.7%, respectively, versus 92% and 90.4%, 78.4% and 72.2%, and 58% and 56.7% for less deprived patients (log-rank p<0.001). More deprived patients had a higher risk of death (p<0.0001), hypertension (p<0.0001), obesity (p=0.02), diabetes mellitus (p=0.02), graft rejection (p<0.0001), chronic kidney dysfunction (p<0.0001), major cardiovascular events (p<0.0001) and de novo malignancies (p<0.0001) than less deprived recipients. The factors associated with the survival probability were younger donor and recipient ages (p=0.03 and 0.02, respectively), female recipient sex (p=0.04), absence of HCV (p<0.01), absence of HCC (p=0.02), absence of DM at transplantation (p=0.03) and 1 year (p=0.01), lower DI (p=0.02), lower MELD (0.02), shorter CIT (p=0.03), TAC (p=0.01), and EVR in the immunosuppressive regimen (p=0.02). Conclusions: Patients from more deprived areas have a higher risk of death after liver transplantation. Pre- and post-transplant socioeconomic risk profiling is warranted to better tailor care to patient’s needs and expectations.

The healthcare system is intricate and dynamic. For the purpose of organising and planning a system, where allocating funds appropriately is essential and therefore managerial skills play a critical role. A certain portion of each nation's GDP is allotted to the health sectors. Managers and decision-makers in the healthcare systems are using resources effectively, yet the quantity of funding they receive from the government or other stakeholders is insufficient sometimes. A sound understanding of both basic and advanced economics is necessary for the care management, to make cost-effective judgements in public health. Healthcare officials at all levels (regional, state, federal, or international), need to be knowledgeable about public health issues and the related modern economic climates. Business executives and healthcare managers need effective practical knowledge to handle partner-financial allocation (demand-supply chain) and handle economic volatility.

Achieving Universal Health Coverage (UHC) is a strategic objective of the Jordanian Government and has been prioritized in its strategies and plans. However, there are several challenges affecting primary health care in Jordan and the health system in general that prevent Jordan from achieving UHC. This paper highlights the importance of team-based care in the form of Family Health Teams (FHTs) to realize Jordan’s goal of achieving UHC. FHTs are a team-based approach that brings together diverse professionals to provide a comprehensive, efficient, patient-centered primary care system that meets the changing needs of Jordan's population and refugees. However, the implementation of FHT may encounter obstacles, including individual, organizational and institutional, and external barriers. To overcome such obstacles, several actions and processes need to be taken, including political commitment and leadership, implementing good governance and policy frameworks, allocating resources and funding, multisectoral collaboration, and engagement of communities and stakeholders. The successful implementation of FHTs requires participation from government officials, parliamentarians, civil society, and influential community, religious, and business leaders. A strategic policy framework, effective oversight, coalition building, regulation, attention to system design, and accountability are also essential. In conclusion, adopting the FHT approach in Jordan's Primary Health Care system offers a promising path towards achieving UHC, improving healthcare access, quality, and efficiency while addressing the unique challenges faced by the country's healthcare system.

This retrospective observational study describes the results of an ad-hoc designated prevention protocol aimed at containing the spread of the scabies infestation among healthcare workers (HCWs) of a large University Hospital in Italy. The outbreak started on October 2022 and a preventive protocol was set up thanks to a multidisciplinary approach. HCWs at high scabies risk were defined as subjects working in UOs with more than five confirmed cases of scabies, close contacts of a confirmed case of scabies, or HCWs with signs and symptoms of the disease. All cases of at high scabies risk underwent a dermatological examination and the infested HCWs were suspended from work until definitive healing. Mass prophylactic treatment was established for all HCWs working in UOs with more than five confirmed cases of scabies. Until March 2023, out of 183 screening dermatological examinations, 21 (11.5%) were diagnostic for scabies. We obtain a prevalence of scabies of 2.6% (21/800) and a duration of the outbreak of 14.7 weeks. Statistical analysis shows a significant association between scabies and being a nurse and have an allergy to dust mites. We obtained a low prevalence of scabies infection, limiting the duration of the outbreak and the related economic burden.

Early experience with Covid-19 shows that vaccines can be the most effective way of preventing the spread of infection. However, vaccine hesitancy is among the most significant hurdles in preventing the spread of novel infections. Monkeypox (MPX) has already been declared a global health emergency by WHO. Thus, there is an urgent need to understand the MPX vaccine willingness in various population groups. In this cross-sectional study, an online survey was conducted among Saudi healthcare workers (HCWs) to understand the monkeypox vaccine willingness in healthcare workers in Saudi Arabia. Saudi has already confirmed multiple MPX cases, and thus it is essential to initiate timely protective measures, including vaccination. The study had 743 respondents. The study found that among Saudi HCWs, 52.7% were willing to receive the MPX vaccine. The study found that sociodemographic factors had a small impact on vaccine willingness. However, early experience with vaccination had a significant impact. Thus, more than 70% who had influenza or COVID-19 vaccine were willing to receive the MPX vaccine. Some of the most significant concerns influencing vaccine acceptability were the safety and efficacy of the vaccine. Hence, it is strongly recommended to focus on disseminating information regarding the safety and efficacy of the MPX vaccine.

(1) Background: Emergencies confront civilian and military healthcare providers with medical and hygienic challenges due to the lack of potable water. This pilot study aimed to describe the application of two different methods for microbiological monitoring of water in a harsh environment in terms of performance, ease of use, availability, and the possibility of using the results to evaluate water quality. (2) Methods: Samples from raw water, Potable water, and water for consumers were taken from two different camps with the same raw water source. The samples were analyzed by using IDEXX industry-standard methods (Colilert and Enterolert enzymatic test kits) and a combination of membrane filtration and 3M-Petrifilm. (3) Results: The IDEXX method used at the Norwegian Camp are easier to utilize and has a broader range of analyzing kits for drinking water analysis. In addition, IDEXX is better adapted to the requirements of the national legislation. However, the combination of membrane filtration followed by incubation on 3M-Petrifilm ™, as used at the Swedish camp, is a better field alternative compared to traditional bacteriology, as it eliminates the need to produce and store agar plates. (4) Conclusions: This pilot study highlights the need for adapted technical equipment and tools for internal microbiological control of water production in a harsh field environment and may facilitate the use of a relatively simple method for water control and ensure the safety of deployed staff in both civilian and military settings.

Hand hygiene is among the most important factors of infection control in healthcare settings. Healthcare workers are considered the primary source of hospital acquired infection. We assessed the current state of hand hygiene knowledge, perception and practice among the healthcare workers in Qassim, Saudi Arabia. In this cross-sectional study we used the hand hygiene knowledge and perception questionnaire developed by the World Health Organization. Knowledge and perceptions were classified into good (80 – 100%), moderate (60 – 79%) and poor (<60% score). Majority of the healthcare workers had moderate knowledge (57.8%) and perception (73.4%) of hand hygiene. Males were less likely to have moderate/good knowledge compared to females (OR: 0.52, p<.05). Private healthcare workers were less likely (OR: 0.33, p<0.01) to have moderate/good perception compared to the government healthcare workers. Healthcare workers who received training on hand hygiene were 3.2 times likely (p<.05) to have good/moderate perception and 3.8 times likely (p<0.05) to routinely use alcohol-based hand-rub than the ones without such training. Physicians were 4.9 times likely (p<0.05) to routinely use alcohol-based hand-rub than the technicians. Our research highlighted gaps on hand hygiene knowledge and perception and practice among healthcare workers in Qassim and importance of training in this regard.

Background: The practices of various health-care professionals have been improvised to accommodate the on-going covid-19 pandemic situation. Different guidelines have been set in place to ease the process of re-opening of non-elective healthcare services like out-patient physiotherapy clinics. Although the measures taken should be guided by evidence based information, major consensus amongst practicing therapists needs to guide the India physiotherapy clinics. Objective: To identify and present the opinions of different physiotherapists about the various strategies for re-opening the out-patient physiotherapy clinics. Methods: An online cross-sectional survey was conducted. Over 169 participants were selected to participate in the survey according to the pre-decided inclusion and exclusion criteria. The data was collected and saved via google forms. Result and conclusion: A majority of respondents had a consensus over different strategies for re-opening the physiotherapy OPDs. These were regarding different measures to be adapted including modifications in the clinic infrastructure and the practice pattern. This would help in smoothly re-instating the physiotherapy services post the covid-19 lockdown.

The rise in the volume, variety and complexity of data in healthcare has made it as a fertile-bed for Artificial intelligence (AI) and Machine Learning (ML). Several types of AI are already being employed by healthcare providers and life sciences companies. The review summarises a classical machine learning cycle, different machine learning algorithms; different data analytical approaches and successful implementation in haematology. Although there are many instances where AI has been found to be great tool that can augment the clinician’s ability to provide better health outcomes, implementation factors need to be put in place to ascertain large-scale acceptance and popularity.

With the rapid development of urbanization and industrialization in China, environmental issues have become a knotty problem, especially issues related to air, water, and solid-waste pollution. These pollutants pose threats to the health of the population and to that of communities and have a vicious influence on the healthcare system. Additionally, pollution also exhibits spill-over effects, which means that pollution in the local region could affect the healthcare services in a neighbouring region. Therefore, it is necessary to explore the relationship between pollution and healthcare. A spatial autocorrelation analysis was conducted and spatial panel econometric models were constructed to explore the characteristics of pollution and healthcare services in China and the relationship between them using data on all 31 provinces over twelve consecutive years (2006-2017). The results showed that the utilization of healthcare services and environmental pollution were not randomly distributed; unsurprisingly, air pollution and solid-waste pollution were mainly found in parts of northern China, while water pollution was highest in southern and coastal China. In addition, environmental pollution exhibited spill-over effects on healthcare services. For example, a 1% increase in solid waste in one specific geographical unit was estimated to increase the inpatient visits per capita in adjacent counties by 0.559%. Specifically, pollution showed different degrees of influence on healthcare services, which means that the impact of environmental pollution on the number of outpatient visits is greater than on the number of inpatient visits. Our results provide the government with evidence for effectively formulating and promulgating policies, especially policies aimed at tackling spill-over effects among different regions.

Infection control among patients is critical for diseases like COVID-19. The concentration of patients in a few facilities burdens healthcare providers and the healthcare system. This study examined the operations of an extended anteroom in a dedicated COVID-19 hospital. It presents issues to consider in the deployment and operation of an extended anteroom through discussions by expert working groups. The subjects covered included efficient space, staffing, equipment management, and education. The process involved wearing personal protective equipment (PPE; in this case, Level D), and if necessary, wearing additional powered air purification respirators (PAPR), after moving from the preparation room to the dressing room, and when entering the hospital through the entrance passage. When leaving the hospital, personnel used a mandatory exit-only passage; in the dressing room, they undressed, and then went outside, in this order. The efficient spatial composition of the anteroom facilitated entry and exit and the separation of contaminated areas and non-contaminated areas using colors and lines. It is necessary to develop operational guidelines for hospitals that treat infectious diseases and conduct research to improve care. The study indicated the need to develop educational programs and use educational simulations to address regionally spread infectious diseases

Hospital indebtedness is a complex and very diverse phenomenon. Thus, the goal of this study is the comparison of the financial performance of public hospitals in accordance with their ownership and size. The results of the research lead to the conclusion that the vast majority of public hospitals are indebted, and their ownership structure does not affect their financial condition. What is more, the statistical analysis depicted that large Marshall hospitals are less indebted than poviat-commune ones. In the group of medium-size hospitals, the situation was the opposite. Moreover, the study did not confirm the significant relationship between the size or ownership and the financial status of the hospital. The analysis conducted in the article is aimed at filling in the gap in studies comparing the indebtedness between different types of public hospitals.

The healthcare domain is increasingly adopting IoT and Electronic Health Record (EHR) systems, generating vast volumes of healthcare data. This shift is driven by the growing need of delivering the right information to the right individuals, at the right time. The latter underscores the importance of adopting a comprehensive strategy for efficiently collecting, utilizing, and analyzing health-related data to not only enhance overall healthcare management but also for the provision of timely and personalized prevention strategies. The latter is of highest importance especially in scenarios where lack of effective treatments or poor survival rates (such in pancreatic cancer) renders typical healthcare strategies ineffective. In this article, we introduce an innovative and integrated platform that is specifically designed and developed for accessing, processing, and analyzing data in challenging healthcare scenarios, such as dealing with pancreatic cancer. This platform, called iHelp, combines multidisciplinary technologies and provides healthcare professionals reliable risk modelling, analysis, and prediction techniques so that individuals (at risk of developing pancreatic cancer) can be provided with timely, reliable, and personalized prevention and intervention measures. A key innovation in the iHelp platform is the standardized data management approach called Holistic Health Records (HHRs) that facilitate the capturing of all health determinants in a standardized and well-structured way for processing towards the provision of health risk detection and personalized healthcare decision support. In the development of iHelp platform, the HHRs are evaluated through different real-world healthcare datasets, including datasets coming from hospital systems, data from wearables, questionnaires, and mobile applications.

Deep behavioral covariates (DBCs) introduced in this perspective form a new class of covariates that have the potential to enhance the performance of predictive models and improve analytics in clinical decision support applications. DBCs can measure how engaged a patient tends to be and how he or she tends to respond to events, and they may be highly predictive of the patient’s outcomes for a planned treatment. DBCs may potentially serve as a standard to measure patient engagement and activation and may form highly efficient mechanisms for improving patient outcomes.

Currently, some non-conventional therapies (NCT), such as acupuncture, homeopathy, osteopathy, naturopathy, herbology, and Traditional Chinese Medicine are structured and well-regulated for a market of teaching and clinical practice in Portugal, among which acupuncture has become one of the most appealing and functional branches. Through investigation of acupuncture laws, field surveys, teaching work and interviews with people from NCT field in Portugal, we showed the current acupuncture education in Portugal and found that according to the academic norms and rules of education in Portugal, there is a gradual difficulty in the progression and maintenance of the degree training dynamics, due to the lack of more tolerant transitional measures and also, a timid commitment on the part of the institutions that embark on these complementary programs. Therefore, it will be necessary to promote additional programs and measures that avoid a total emptiness of the teaching of acupuncture and at the same time losses of clinicians, competencies and quality of information that are difficult to recover. It could be very meaningful and thought-provoking to the future development and improvement of acupuncture in Portugal and in other countries that welcome acupuncture and intend to have a better legislation and application.

The emerging concept of planetary health needs to be discussed in a more organized and sustainable way within the global public health and healthcare disciplines. Therefore, planetary health should be considered a cardinal component of the global academic framework for healthcare professionals. The availability of related curricula and courses is crucial to equip health professionals in this relatively new discipline of planetary health. In this review article, we aimed to explore published articles and online databases of courses to summarize the available planetary health education opportunities and discussions for health professionals, to identify the gaps in resource allocation and to suggest future recommendations. We observed a visible re-source inequity in global south with the lack of a universal planetary health module for healthcare professionals. Additionally, there is minimal inclusion of allied health disciplines in this learning process. We, therefore, recommend a dedicated network of motivated healthcare professionals and regional hubs with an agenda to ensure a comprehensive, uniform, and inclusive planetary health education curriculum and practice.

With the availability of wearable health monitoring sensor modules like 3-Lead Electrocardiogram (ECG), Pulse Oximeter (SpO2), Galvanic Skin Response (GSR), Hall effect sensor (for measuring Respiratory Rate), Blood Pressure and Temperature measuring and sensing elements, it has now become possible to device a composite health status monitoring kit that can measure vital signs and other physiological parameters pertaining to human health in real time. Traditionally, the physiological parameters along with vital signs related examination was possible only in a hospitalized or ambulatory environment, however due to advances in sensing and embedded system technology and miniaturization of data acquisition and processing elements health monitoring has become possible even when individuals remain engaged in their day to day activities at the convenience of space and location. The patients or individuals subject to monitoring may suffer from a traumatic experience due to their medical condition and may need emergent incidence response and the critical care team may have to prepare for the treatment only after the patient arrives, which often is too late, as in case of cardiac arrests or severe injuries. The research focused on real-time health status monitoring and trauma scoring using standard physiological parameters along with standard telemetry protocols to make the critical care team aware of an emergent situation and prepare for a medical emergency. Vital signs and physiological parameters (heart rate, temperature, respiratory rate, and blood pressure, SpO2) were measured in real time from human subjects non-invasively. In order to enable monitoring of the patients engaged in day to day activities, errors due to the motion were removed using stationary wavelet transform correction (correlation coefficient of 0.9 after correction) and signals from various sensors were denoised, filtered and were encoded in a format suitable for further data analysis. A composite sensor kit capable of monitoring vital signs and physiological parameters can be very useful in incident response when an individual undergoes a traumatic experience related to stroke, cardiac arrest, fits or even injury, as along with monitoring information the kit can calculate scores related to trauma like the Injury Severity Score (ISS), National Early Warning Signs (NEWS), Revised Trauma Score (RTS). Trauma Injury Severity Score (TRISS), Probability of Survival (Ps) score. An open access database of vital signs and physiological parameters from Physionet, MIMIC 2 Numerics (mimicdb/numerics) database was used to calculate NEWS and RTS and to generate correlation and regression models using the vital signs/physiological parameters for a clinical class of patients with respiratory failure and admitted to Intensive Care Unit (ICU). NEWS and RTS scores showed no significant correlation (r = 0.25, p<0.001) amongst themselves, however together NEWS and RTS showed significant correlation with Ps (blunt) (r = 0.70, p<0.001). RTS and Ps (blunt) scores showed some correlation (r = 0.63, p<0.001) and NEWS score showed significant correlation (r = 0.79, p<0.001) with Ps (blunt) scores. Furthermore, since individuals have to be monitored regardless of location, these kits have to have a built-in capability to locate the individual so that the incident response team can locate the individual based on Global Positioning System coordinates (GPS). A Quantum GIS (Geographical Information System) application using real-time GPS coordinates (OpenStreetMap coordinates) was used to calculate the shortest path using QGIS Network Analysis tool to demonstrate the calculation of shortest path and direction to locate the nearest service provider in shortest time. Along with locating the nearest healthcare service provider, it would help if the critical care team could be made aware of the physiological parameters and trauma scores using standard protocols accepted across the globe. The physiological parameters from the sensors along with the calculated trauma scores were encoded according to a standard Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT) coding system and International Code of Diseases (ICD) codes and the trauma information was logged to Electronic Health Records (EHR) using Fast Health Interoperability Resources (FHIR) servers. FHIR servers provided interoperable web services to log the event information in real time. It could be concluded that analytical models trained on existing datasets can help in analyzing a traumatic experience or an injury and the information can be logged using a standard telemetry protocol as a telemedicine initiative. These scores enable the healthcare service providers to estimate the extent of trauma and prepare for medical emergency procedures and find applications in general and military healthcare.

Background: All Payer Claims Databases (APCD) are a rich source of health information, however, race and ethnicity (R&E) data are largely missing. Bayesian Improved Surname Geocoding (BISG) is a common R&E imputation method, yet, validation of BISG in APCDs is lacking. We used the BISG to impute missing R&E in the Oregon APCD. Methods: BISG imputed R&E for Asian Pacific Islanders (API), Blacks, Hispanics and Whites were contrasted to the gold standard (vital statistics) and sensitivity and specificity improvements were assessed. Logistic regression examined whether missing R&E was random across patient characteristics. Results: Among 85,857 individuals in the study, 32.1% (n=27,594) had missing R&E. Missing R&E was not randomly distributed. There were higher odds of missingness among males, Whites, those age 65 and older, and commercially insured individuals. Differences in the percent missing were also found by co-morbid conditions and mortality causes. Imputing the missing R&E with BISG method improved the sensitivity to identify White, Black, API, and Hispanics. Conclusions: APCDs can benefit from enhancing missing R&E with BISG imputation to perform more robust population-health level analyses and identify inequities according to R&E without losing power or dropping non-random records with missing R&E data.

A large body of evidence has linked unhealthy eating patterns with an alarming increase in obesity and chronic disease worldwide. However, existing methods of assessing dietary intake in nutritional epidemiology rely on food frequency questionnaires or dietary records that are prone to bias and selective reporting. Herein, metabolic phenotyping was performed on 42 healthy participants from the Diet and Gene Intervention (DIGEST) pilot study, a parallel two-arm randomized clinical trial that provided complete diets to all participants. Matching urine and plasma specimens were collected at baseline and following 2 weeks of provision of either a Prudent or Western diet with a weight-maintaining menu plan designed by a dietician. Targeted and nontargeted metabolite profiling was conducted using three complementary analytical platforms, where 80 plasma metabolites and 84 creatinine-normalized urinary metabolites were reliably measured (CV < 30%) in the majority of participants (> 75%) after implementing a rigorous data workflow for metabolite authentication with stringent quality control. We classified a panel of metabolites with distinctive trajectories following 2 weeks of food provisions when using complementary univariate and multivariate statistical models. Unknown metabolites associated with contrasting dietary patterns were identified with high resolution MS/MS and/or co-elution after spiking with authentic standards. Overall, 3-methylhistidine and proline betaine concentrations increased consistently after participants were assigned a Prudent diet (q< 0.05) in both plasma and urine samples with a corresponding decrease in the Western diet group. Similarly, creatinine-normalized urinary imidazole propionate, hydroxypipecolic acid, dihydroxybenzoic acid, and enterolactone glucuronide, as well as plasma ketoleucine and ketovaline increased with a Prudent diet (p< 0.05) after adjustments for age, sex and BMI. In contrast, plasma myristic acid, linoelaidic acid, linoleic acid, a-linoleic acid, pentadecanoic acid, alanine, proline, carnitine and deoxycarnitine, as well as urinary acesulfame K increased among participants following a Western diet. Most metabolites were also correlated (r > ±0.30, p< 0.05) to changes in average intake of specific nutrients from self-reported diet records reflecting good adherence to assigned food provisions. Our study revealed robust biomarkers sensitive to short-term changes in habitual diet for accurate monitoring of healthy eating patterns in free-living populations, which is required for validating evidence-based public health policies for chronic disease prevention.

This study delves into hospital mobility, understood as an indicator of perceived service quality, across the Italian regions of Apulia and Emilia Romagna, utilizing logistic regression among machine learning techniques. The focus is on how structural, operational, and clinical variables impact patient perceptions of service quality, influencing their healthcare choices. Through the analysis of mobility trends with machine learning, significant differences between regions were uncovered, highlighting the influence of regional context on perceived quality. The integration of SHAP (SHapley Additive exPlanations) values into our analysis provided deeper insights into the logistic regression model, elucidating the specific contribution of each variable to perceived healthcare quality. This incorporation of SHAP values underscores the study's commitment to employing advanced, explainable AI techniques to enhance the interpretability and fairness of healthcare service evaluations. The choice of logistic regression elucidated the impact of specific variables on quality perception, offering essential insights for optimizing healthcare resource distribution and underscoring the importance of data-driven strategies to foster more equitable, efficient, and patient-centred healthcare systems. Contributing to the understanding of perceived quality dynamics within the healthcare context, the research paves the way for further investigations into enhancing accessibility and service quality, leveraging machine learning as a tool for improving healthcare services efficiency in diverse regional settings.

Personal protective equipment (P PE) rules must be respected and followed to the letter of healthcare professionals in Cameroon to avoid the transmission of infectious diseases. This research proposes solutions to the problems of non-adherence and non-compliance among healthcare workers in Cameroon towards PPE rules. Inadequate access to suitable PPE, discomfort when wearing PPE during poor quality, and a lack of training on correct PPE use are just a few of these obstacles amongst HCWs in Cameroon. Hospitals and healthcare facilities should prioritize offering thorough instruction on PPE use and pinpoint the need to adhere consistently to PPE rules to remove these obstacles. They should also ensure that all healthcare personnel have access to and a sufficient supply of the proper PPE. Through the organization of impromptu visits by surveillance teams to identify areas of support and training, there is a need for assistance from government bodies and public health groups in creating awareness of the security value of PPE use among healthcare professionals. There is a lack of PPE in health care settings in rural areas in Cameroon, thus a need for an adequate supply. Then can we put appropriate PPE policies and practices for HCWs in Cameroon, as they will keep to it.Healthcare professionals in Cameroon must comprehend that following PPE standards protects not just their selves from diseases but also their patients, coworkers, and communities. We are accountable for ensuring everyone's safety and well-being, and adhering to PPE regulations is an essential first step.

Despite the importance of influenza vaccination for healthcare workers (HCWs), their uptake remains challenging. This study aimed to measure influenza vaccine hesitancy among HCWs in Nakhon Phanom province, Thailand. A representative cross-sectional survey was conducted at six hospitals during August – September 2020 using a self-administered questionnaire. HCWs delaying getting influenza vaccines, accepting but unsure, or refusing with doubts were categorized as hesitant. Those accepting without any doubts were classified as non-hesitant. Vaccine hesitancy determinants were identified by multivariable logistic regression analysis. A total of 338 participants (97%) completed the questionnaires; most were female nurses working at district hospitals without pre-existing chronic medical conditions. Nearly 60% of participants (197/338) exhibited influenza vaccine hesitancy, and significant factors included age above 50 years adjusted odds ratio [aOR] 3.2, 95% CI 1.3-8.5), fair knowledge of influenza/vaccination (aOR 0.4, 95% CI 0.2-0.8), and negative influence of other HCW (High level– aOR 2.3, 95% CI 1.1-4.8; Moderate level- aOR 2.1, 95% CI 1.1-4.4). Imparting updated information to the HCW combined with positive guidance from influential peers may help reduce this hesitancy.

This study investigates the pivotal areas where Artificial Intelligence (AI) integration in healthcare warrants further exploration, leveraging insights from Boston Specialists, a forefront healthcare provider in AI adoption. Employing a qualitative case study approach, enriched by in-depth interviews and comprehensive literature reviews, we identify three main domains for potential AI expansion: scheduling efficiency, clinical documentation, and AI-driven medical research. Our results underscore the substantial enhancements AI brings to operational workflows and patient care, notably through improved scheduling systems, accuracy in medical documentation, and the facilitation of data-driven research methodologies. These findings suggest a critical need for healthcare institutions to further invest in AI technologies, focusing on these key areas to harness AI's full potential in personalizing care, optimizing efficiency, and advancing medical knowledge. The study concludes with a call for continued investigation into AI's integration within healthcare settings, emphasizing the importance of a supportive organizational infrastructure, ethical considerations, and data security in realizing AI's transformative impact on healthcare delivery and patient outcomes.

Healthcare professionals constantly face situations that reflect ecosystems’ degradation. These can negatively affect their mental health. Research suggests that hope and resilience can play an important role in this scenario, since they are related to/predict mental health in highly heterogeneous samples (considering geography, age, profession, health, etc.). In this context, the aims of the present study are: to characterize and explore the relationship between hope, resilient coping and mental health of Portuguese healthcare professionals. Using Google Forms, 276 healthcare professionals answered to the GHQ-28, the (adult) Trait Hope Scale, and the Brief Resilient Coping Scale (cross-sectional study). The minimum and maximum possible scores were reached, with the exception of the maximum score of GHQ-28-Total. Regarding Hope, 19.6% scored below the midpoint (M=43.46, SD=11.97); 29.3% revealed low resilience (M=14.93, SD=4.05); and the average of 4 of the 5 Mental Health scores (exception: Severe Depression) indicates the probability of a psychiatric case. Hope correlated with Social Dysfunction and GHQ-28-Total; resilient coping proved to be a (weak) predictor of 4 of the 5 GHQ-28 indicators (exception: Severe depression). The results support the need to promote the sample's mental health, hope and resilient coping. They also suggest that stimulating resilient coping may contribute to improving healthcare professionals’ mental health.

The study conducts a comparative life cycle assessment (LCA) analysis to assess the environmental impact of two different manufacturing processes used to produce transparent dental aligners. The former method consists of thermoforming a polymeric disc over 3D printed, customized models, while the second, more innovative approach involves the direct printing of aligners using additive manufacturing (AM), specifically applying digital light processing (DLP) technology. The analysis results highlight how adopting direct printing through AM brings significant advantages in terms of environmental sustainability, thanks to the substantial reduction in raw materials and electricity consumption. These drops translate into decreased potential environmental impacts across all impact categories considered within the EF 3.1 method. Furthermore, lowering the amount of raw materials needed in the direct printing process contributes to a notable decrease in the overall volume of waste generated, emphasising the environmental benefits of this innovative technique.

BACKGROUND: Body mass index (BMI) is calculated by dividing a person's height in meters by their weight in kilograms and is always expressed in kg/m². BMI is a reliable risk indicator for various diseases that can develop due to a higher percentage of body fat. There is a possibility of developing certain medical conditions including heart disease, high blood pressure, type 2 diabetes, gallstones, breathing problems and some malignancies that increase with BMI. OBJECTIVE: This study seeks to identify the trends in the Body Mass Index (BMI) of women visiting Better Life Primary Health Care Centre in Ondo City, Ondo State, Nigeria for various healthcare services. METHODOLOGY: Seventy (70) women who participated in this study were randomly selected using systematic random sampling. Their necessary information was obtained using a prepared record sheet to collect their data. Results were analysed using SPSS version 21. RESULTS: The results show mean age of the respondents is 30.50 + 6.52921 21 (30%) were between 31 – 35 years, 21 (30%) were traders, 36 (51%) had tertiary education, 39 (55.7%) were between 151 – 160 cm in height. 32 (45.7%) were between 60 – 80 kg in weight and 30 (42.9%) had normal weight, respectively. CONCLUSION: Body Mass Index (BMI) calculation is an essential tool that can help in identifying one of the significant public health issues that leads to obesity; a predisposing factor to various medical conditions like hypertension, musculoskeletal issues, heart diseases, cancers, and lots more. It is therefore important to incorporate BMI calculation into routine checks to prevent or reduce health burdens that may arise from obesity.

Questionnaires are useful instruments for gathering responses to specific factual questions. However, the problems of questionnaire responses impede the effective use of the questionnaire. Some of these problems including non-responses, non-completion, issues of judgement, and social desirability such as information that the respondent is not willing to disclose need to be dealt with. The situation is more compounded in a scenario where an information security practice study in a typical hospital consists of broad categories of respondents and the survey findings are to be relied on to actually address information security compliance issues. This study, therefore, shares "pitfalls" to watch when preparing a questionnaire to measure the information security practice level in a hospital which is characterized by different respondents with varying domain knowledge such as knowledge in information security, information communication technology, and that of the domain knowledge of healthcare. A synergy of a conventional pretesting method and behaviour coding were therefore used to pretest the questionnaire. Questionnaire problems including a lack of understanding of the healthcare information systems’ structure of all hospitals, unclear questions, the insignificant difference between questions, problematic questions, inadequate questions, and complex terms were among the identified pitfalls to watch. Out of a total of 118 questionnaire items that were used in the pretesting, a total of 50 questionnaire items (representing 42%) were identified to have problems after the pretesting was conducted with a total of 36 respondents in behavior coding and 21 respondents in conventional pretesting.

Introduction: Blood transfusion involves the transfer of blood from donors to patients. A blood transfusion is carried out every 2 seconds in the US. It is made up of about 29000 units of red blood cells and is transfused every day in the US. When blood transfusion is done correctly, it can result in the saving of lives and the improvement of healthcare. However, it may also lead to immediate, late, delayed, and chronic complications. No previous studies have been conducted in Qatar to address this issue. Methods: This is a cross-sectional study intended to determine the knowledge, attitude, and practice toward blood transfusion among healthcare providers at Hamad Medical Corporation (HMC), which is the principal healthcare provider in Qatar. Participants between 18 and 25 years of age were selected for the research study. A 10-item online questionnaire that people can fill out on their own will be used to get the data needed for the analysis and meet the study's goals. Results: the analysis has indicated that facing negative reactions after blood transfusion and being worried about getting affected by any infection have a small positive association, with the specific values coming in at r = 0.317, p = 0.000. Fever after blood transfusion and feeling like refusing blood transfusion have a significant and moderate positive correlation, with the specific values coming in at r = 0.630 and p = 0.000. Conclusion: The findings of this study have helped us figure out how healthcare providers feel, what they know, and what they do during a blood transfusion.

Smart primary healthcare building facility services capture a new level of process and operational data through advanced monitoring, enabling experts to use the building facilities to produce significant and efficient healthcare service delivery within the individual spheres of influence. This study assessed the impact of IoT services on achieving smart primary healthcare building facilities in the rural area of South Africa to enhance primary healthcare delivery. The study identified three (3) basic constructs of IoT services that comprised the application of IoT location recognition and tracking services, the application of the IoT high-speed communication network-based services, and the application of IoT-based services. The study is quantitative, and a questionnaire was used to collect data from the project managers and healthcare practitioners working with the primary healthcare agency in South Africa. The study found a variable degree of impact between the three (3) IoT constructs and the achievement of primary healthcare building facility services in South Africa. The study recommends adopting IoT essential services for achieving smart primary healthcare building facility services in the rural areas of South Africa and other developing countries facing similar primary healthcare delivery challenges.

Recent reports have it that over 85\% of data breaches are still caused by the human element, of which healthcare is one of the suitable organizations mostly targeted by cybercriminals. The work of healthcare staff is often associated with high workloads, high emergency cases, and a broad range of psychological, social, and cultural factors. The significance of these factors could undermine conscious care information security (IS) practice leading to serious violations. This study comprehensively examined the correlation between the psycho-social-cultural factors, work factors with IS and privacy behaviour in a hospital that has fully adopted electronic health records (EHR) management system. The findings are to facilitate the decision-making process towards improving the cyber-security practice in healthcare. A quantitative approach was adopted where we collected responses from 212 healthcare staff through an online questionnaire survey. A broad range of constructs was selected from psychological, social, cultural perception and work factors based on earlier review work. These were therefore related to some security practices, to assess the IS knowledge, attitude and behaviour gaps among healthcare staff in a comprehensive way. From the study, IS self-reported conscious care behaviour (ISCCB) risk was relatively higher as compared to information security knowledge (ISK) risks and information security attitude (ISA) risk. Furthermore, the study revealed that work emergency has a positive correlation with ISCCB (r=1.95, p-value =0.001) risk. Conscientiousness also had positive correlation with ISCCB risk (r=0.157, p-value=0.05) however agreeableness negatively correlated with ISK risk (r=-0.166, p-value =0.05), and ISA risk (r=-0.140, p-value =0.05). Based on these findings, intrinsic and extrinsic motivation methods combined with cutting-edge technologies can be explored to discourage IS risks behaviours while enhancing conscious care security practice.

Background: To determine vitamin D supplementation frequency among infants, factors that influence adherence, and reasons for discontinuation of initiated vitamin D. Methods: This cross-sectional study was conducted using a questionnaire administered to the mothers via a face-to-face interview on 560 infants aged from 1 to 24 months admitted to outpatient clinics from June to December 2017. Results: A total of 351 infants were administered vitamin D, and the rate of supplementation in the first year of life was 83%, while it was only 28% between 13 and 24 months. The rate of vitamin D supplementation was higher among infants who were exclusively formula-fed (p<.05). When the data were analyzed using logistic regression analysis, only visit family physicians seems to be a statistically significant independent variable in increasing supplementation (p<.05). Compared with family refusal, the rate of discontinuation of vitamin D by the healthcare providers was higher after the first year of life (p<.05). The rates of vitamin D discontinuation by healthcare providers, especially by nurses who considered the duration of supplementation adequate, were statistically significantly higher when compared with the fontanel closure and other reasons (p<0.05). Conclusions: The rate of vitamin D supplementation was higher among families who visited family physicians, which suggests the importance of well-baby visits. Since vitamin D supplementation was less common among exclusively breastfed infants, mothers should be educated. Healthcare professionals need further education about the importance of vitamin D supplementation and indications for discontinuation.

Health literacy is an indicator of a society’s ability to make better health judgement for themselves and the people around them. This study investigates the prevalence of health literacy among Malaysian adults and provides an overall picture of the current health literacy state of the society. The study also highlights socio-demographics markers of communities with limited health literacy which may warrant future intervention. A population based self-administered survey using the Health Literacy Survey Malaysian Questionnaire18 (HLS-M-Q18) instrument was conducted as part of the National Health Morbidity Survey 2019 in Malaysia. The nationwide survey utilized two-staged stratified random sampling method. A sample of 9478 individuals aged 18 and above participated in the study. The health literacy score was divided into three levels; limited, sufficient and excellent. Findings showed that majority Malaysian population has sufficient health literacy level, albeit leaning towards the lower end of the category with an average score of 35.5. The limited health literacy groups are associated with respondents with older age, lower education level and lower household income. Overall health literacy state for Malaysia is categorized at a lower sufficient level. Health literacy improvements should focus on communities with limited health literacy level.

Background: Disability and caste are two different forms of oppression, however Dalits and people with disabilities commonly face similar types of marginalities. Dalit women with disabilities may experience double discrimination because of the intersectionality of disability and caste. This study examines whether the disability and caste identity of women together affects and compounds the utilization of maternal healthcare services. Methods: A cross-sectional survey was conducted using a semi-structured questionnaire among a total of 354 Dalit and non-Dalit women, with and without a disability aged between 15 – 49 years. Maternal healthcare service utilization was assessed by Ante-Natal Care (ANC), health facility (HF) delivery, and Post-Natal Care (PNC) during the last pregnancy. Logistic regression was performed to detect the predictors of service utilization and identify whether disability and caste were associated with service utilization. First, disability and caste were fitted separately in models. Secondly, the intersectionality of disability and caste was tested by the inclusion of disability*caste interaction term. Finally, the confounding effect of socio-demographic factors was investigated. Results: Out of surveyed women, 73% had 4+ ANC visits, 65% had HF delivery and 29% had a PNC visit during their last pregnancy. Women with a disability had lower odds of HF delivery (OR 0.50, CI 0.30 – 0.84) and PNC (OR 0.47, CI 0.25 – 0.88) than women without a disability. Adjustment for women’s age and household wealth explained associations in HF delivery by women with disabilities. There was no association between caste and service utilization. Disability overrode caste and there was no other evidence of effect modification by women’s caste status in the utilization. However, a weak interaction effect in the utilization of ANC services was found in the caste group by their education (OR 0.19, 95% CI 0.05 – 0.74). Conclusions: Disabled women – whether Dalit or non-Dalit - had lower rates of utilizing all maternal healthcare services than non-disabled women. However, Dalit women with disabilities were more likely to receive PNC than non-Dalit women with disabilities. Increasing equity in maternal healthcare service utilization requires that traditional approaches to service development and program intervention to be re-examined and more nuanced interventions considered to ensure improved access and outcome among all vulnerable groups.

While it is not new that Nigeria is challenged by a huge infrastructure deficit, the COVID-19 pandemic has exposed the country’s comatose healthcare system. Given the country’s dwindling revenue, massive debt profile and the inability of the public-sector to efficiently manage public facilities in the country, this paper examines how the public-private partnership model of infrastructure procurement can be deployed as a solution for Nigeria’s healthcare crisis. In addition to the above, this paper takes a look at how a partnership with the private sector can aid Nigeria’s quest towards achieving healthcare-related Sustainable Development Goals. The paper also considers two healthcare-based projects as case studies to serve as lessons for future projects in the country. Among others, the paper recommends a holistic long-term solution for the country’s healthcare needs.

Implications of the novel usage adoption of the internet of things in various sectors of works and life are researched and documented at pace. This is related to the overall high rate at which new technologies are adopted in modern society. Healthcare is a vital aspect of everyday activities and as such overlaps with the increasingly important role played by use of the internet and associated technologies. The purpose of this review article is to draw attention to the potential social, ethical, legal and professional limitations to using IoT in the context of healthcare. The social and ethical aspects in particular, focus on IoT usage in care of the elderly with relevant case studies as reference.

With an increasing demand for quality of care and lower costs, hospitals are looking for industry-based methods to improve efficiency in their processes. This study aims to reduce waste in a public hospital in Mexico by improving the medical supply process for the operating room. To this end, a lean healthcare (LH) implementation following the DMAIC approach (Define-Measure-Analyze-Improve-Control) is carried out. We analyze the value stream of the supply process, including main surgical procedures and their related medical supplies, and identify different causes of inefficiency, which are evaluated and controlled through different tools, including a value stream map, Kanban, and the 5S program. As a result, five types of waste were reduced. Over-processing requests were reduced by 15.3%, defective identification numbers were reduced by 46.5%, redundant processing was improved by 94.8%, near 2.8% of the unnecessary inventory was reduced, and transportation waste was reduced by up to 16.7%. Finally, the lead-time for the main supplies was reduced by 33 days. This work demonstrates that LH and DMAIC are effective in reducing waste and are highly conducive to improving sustainability in healthcare processes. Moreover, it provides practical insights for practitioners regarding the implementation of LH in public hospitals in developing countries.

The burnout syndrome, which affects so many healthcare workers, has recently awakened wide interest due to the severe repercussions related to its appearance. Even though job factors are determinant to its development, not all individuals exposed to the same work conditions show burnout, which demonstrates the importance of individual variables such as personality. The purpose of this study was to determine personality characteristics of a sample of nursing professionals based on the Big Five model, and then, having determined the personality profiles, analyze the differences in burnout and engagement based on those profiles. The sample was made up of 1236 nurses. An ad hoc questionnaire was prepared to collect the sociodemographic data, and the Brief Burnout Questionnaire, the Utrecht Work Engagement Scale and the Big Five Inventory-10 were used. The results showed that the existence of burnout in this group of workers, is associated negatively with extraversion, agreeableness, conscientiousness and openness to experience, and positively with the neuroticism personality trait. These personality factors showed the opposite pattern with regard to engagement. Three different personality profiles were also found in nursing personnel, in which professionals who had a profile marked by strong neuroticism and low scores on the rest of the personality traits where those who were most affected by burnout.

Blockchain technology enables a decentralized and distributed environment with no need for a central authority. Transactions are simultaneously secure and trustworthy due to the use of cryptographic principles. In recent years, blockchain technology has become very trendy and penetrated different domains, mostly due to the popularity of cryptocurrencies. One field where blockchain technology has tremendous potential is healthcare, due to the need for a more patient-centric approach to healthcare systems and to connect disparate systems and increase the accuracy of electronic healthcare records (EHRs). In this systematic review, an analysis of state-of-the-art blockchain research in the field of healthcare is conducted. The aim is to reveal the potential applications of the technology and to highlight the challenges and possible directions of blockchain research in healthcare. First, background information is discussed, followed by a description of the exact methodology used in this paper. Next, an analysis of the results is given, which includes a bibliometric overview, an analysis of gathered data and its properties, and the results of a literature quality assessment. Lastly, there is a discussion of the results from the analysis. The findings indicate that blockchain technology research in healthcare is increasing and it is mostly used for data sharing, managing health records and access control. Other scenarios are very rare. Most research is aimed at presenting novel structural designs in the form of frameworks, architectures or models. Findings also show that technical details about the used blockchain elements are not given in most of the analyzed publications and that most research does not present any prototype implementation or implementation details. Often even with a prototype implementation, no details about blockchain elements are given.

Interdisciplinary conferences play a vital role in advancing explainable Artificial Intelligence (AI) within increasingly intersecting healthcare and computational biology arenas. Challenges result-ing from algorithmic bias and the necessity for domain-specific Explainable AI (XAI) techniques underscore the increasing significance of transparent and interpretable AI systems used in patient care. Collaborative efforts between clinicians, data scientists, and various stakeholders are nec-essary to innovate solutions tailored to healthcare needs. Specialized conferences may foster these interdisciplinary interactions, providing platforms for knowledge exchange, networking, and collaborative partnerships. The legal, ethical, and societal dimensions of medical AI advocate for an integrative approach that aligns technological advancements with patient-centered care val-ues. The role of specialized conferences is therefore essential for shaping future directions in ex-plainable AI and computational biology that contribute to improved patient outcomes and healthcare innovations.

A distinction is made between data rescue (i.e., copying, digitizing and archiving) and data recovery that implies deciphering, interpreting and transforming early instrumental readings and their metadata to obtain high-quality datasets in modern units. This requires a multidisciplinary approach that includes: palaeography and knowledge of Latin and other languages to read the handwritten logs and additional documents; history of science to interpret the original text, data e metadata within the cultural frame of the 17th, 18th and early 19th century; physics and technology to recognize bias of early instruments or calibrations, or to correct for observational bias; astronomy to calculate and transform the original time in canonical hours that started from twilight. The liquid-in-glass thermometer was invented in 1641 and the earliest temperature records started in 1654. Since then, different types of thermometers were invented, based on the thermal expansion of air or selected thermometric liquids with deviation from linearity. Reference points, thermometric scales, calibration methodologies were not comparable, and not always adequately described. Thermometers had various locations and exposures, e.g., indoor, outdoor, on windows, gardens or roofs, facing different directions. Readings were made only one or a few times a day, not necessarily respecting a precise time schedule: this bias is analysed for the most popular combinations of reading times. The time was based on sundials and local Sun, but the hours were counted starting from twilight. In 1789-90 Italy changed system and all cities counted hours from their lower culmination (i.e., local midnight), so that every city had its local time; in 1866, all the Italian cities followed the local time of Rome; in 1893, the whole Italy adopted the present-day system, based on the Coordinated Universal Time and the time zones. In 1873, when the International Meteorological Committee (IMO) was founded, later transformed in World Meteorological Organization (WMO), a standardization of instruments and observational protocols was established, and all data became fully comparable. In the early instrumental period, from 1654 to 1873, the comparison, correction and homogenization of records is quite difficult, mainly because of the scarcity or even absence of metadata. This paper deals about this confused situation, discussing the main problems, but also the methodologies to recognize missing metadata, distinguish indoor from outdoor readings; correct and transform early datasets in unknown or arbitrary units into modern units; finally, in which cases it is possible to reach the quality level required by WMO. The focus is to explain the methodology needed to recover early instrumental records, i.e., the operations that should be performed to interpret, correct, and transform the original raw data into a high-quality dataset of temperature, usable for climate studies.

40 years of cloud observations are available globally from satellites allowing derivation of climate data records (CDRs) for climate change studies. The aim of this study is to investigate how stable these cloud CDRs are and whether they qualify stability requirements recommended by the WMO’s Global Climate Observing System (GCOS). We also investigate robust trends in global total cloud amount (CA) and cloud top temperature (CTT) that are significant and common across all CDRs. The latest versions of four global cloud CDRs, namely CLARA-A3, ESA Cloud CCI, PATMOS-x and ISCCP-HGM, are analysed. This assessment finds that all three AVHRR based cloud CDRs satisfy even the strictest GCOS stability requirements for CA and CTT when averaged globally. While CLARA-A3 is most stable in global averages, PATMOS-x offers the most stable CDR spatially. While we find these results highly encouraging, there however remain large spatial differences in the stability of and across the CDRs. All four CDRs continue to agree on the statistically significant decrease in global cloud amount over the last four decades, although this decrease is now weaker compared to the previous assessments. This decreasing trend is stabilizing or even reversing in the last two decades; the latter is seen also in MODIS-Aqua and CALIPSO GEWEX datasets. Statistically significant trends in CTT are observed in global averages in the AVHRR-based CDRs, but the spatial agreement in the sign and the magnitude of the trends is weaker compared to those in CA. We also present maps of Common Stability Coverage and Common Trend Coverage that could provide a valuable metric to carry out an ensemble-based analysis of the CDRs.

COVID-19 pandemic-related pressures on primary care may have driven inappropriate continuation of antibiotic prescriptions. Yet prescribing modality (repeat/non-repeat) has not previously been investigated in a pandemic context. Using the OpenSAFELY-TPP analytics platform, we analysed repeat/non-repeat prescribing frequency in monthly patient cohorts between Jan 2020–2022. In-depth analysis was conducted on Jan 2020 (“pre-pandemic”) and Jan 2021 (“pandemic”) cohorts. Per-patient prescribing and clinical conditions were determined by searching primary care record data using clinical code lists. Repeat prescribing was defined as >=3 prescriptions in a 6 month lookback period. Associations between demographics (e.g. age, sex, geography) and repeat/non-repeat prescribing were explored using unadjusted risk ratios. Antibiotic prescribing declined from May 2020; non-repeat prescribing declined more strongly than repeat prescribing (maximum declines -26% vs -11%, respectively). In the pandemic cohort, older patients were at higher risk of prescribing (especially repeat prescribing). The most common clinical conditions for repeat prescribing were COPD comorbidity and urinary tract infection. Comorbidities were more common among repeat vs non-repeat prescribed patients. In the pandemic cohort, vs pre-pandemic, repeat and non-repeat prescribing for comorbidities generally declined less compared with shorter-term conditions (infections, including COPD exacerbation/lower respiratory tract infection). Our findings inform ongoing development of stewardship interventions in England..

The COVID-19 pandemic had a significant impact on the mental health of individuals globally, and primary healthcare (PHC) nurses play a critical role in providing mental healthcare services. However, limited research has explored the experiences of PHC nurses in providing mental healthcare services during the COVID-19 pandemic. This study explored the experiences of PHC nurses in providing mental healthcare services during the pandemic in Durban, South Africa. The aim was to identify the challenges faced by healthcare providers and the potential for innovative approaches to improve access to care. A qualitative, exploratory design guided the study, and data were collected through in-depth interviews with twelve PHC nurses purposively selected. Thematic analysis was used to analyse the data. Findings from interviews with primary healthcare nurses reveal that the pandemic exacerbated existing challenges, including medication adherence issues, fear and uncertainty among patients, vaccine hesitancy, decreased clinic visits, and the mental and emotional toll on both patients and healthcare workers. PHC nurses adapted their services by increasing outreach efforts, prioritising patient care, and utilising technology and non-governmental organisations’ (NGO) support. Challenges included reduced patient visits, complexities in healthcare provision, and lack of adequate support. Positive changes observed include increased mental health awareness among healthcare professionals and younger generations. Recommendations include implementing outreach and awareness campaigns, providing accurate information about COVID-19 and vaccinations, and promoting cultural sensitivity in mental healthcare provision.

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.