Search results

Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively.

This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics.

Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h.

This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.

All colleges of medicine in the Gulf Cooperation Council (GCC) adopt English as a language of instructions. This study aimed to examine medical students' views on introducing medical terminology in Arabic within an English-based curriculum.

This descriptive study targeted preclinical second- and fourth-year students in the College of Medicine and Medical Sciences at the Arabian Gulf University, during the academic year 2022–2023 (n = 407). Within the pharmacology teaching material in unit I (second year) and unit VIII (fourth year), which are taught in English, students were provided with medical terms in Arabic. At the end of these two units, students' views were sought by using a self-administered questionnaire.

The number of respondents was 263 (response rate 64.1%: 22.2% males, 77.8% females). Most participants received their school education mainly in Arabic (78.8%). A significant percentage of students believed that providing Arabic terms helped their learning (79.8%). If pharmacology is taught exclusively in English, majority of the students anticipated to face difficulties when explaining drug treatment to their patients in the future (71.3%). Most respondents expected this intervention to help them communicate with patients (86.7%), and preferred to include it in the clinical skills training (82.2%). The second-year students and those whose school education was mainly in Arabic were more likely to agree to the intervention (p < 0.05 for both).

The introduction of medical terms in Arabic is an acceptable alternative to complete Arabization, and is believed to help students in their learning and communication with their patients.

Medical schools aspire to graduate doctors who are competent in interpreting, conducting and publishing scientific research. Hence, the purpose of the paper is explore the impact of a structured compulsory community-oriented, project-based research program in the undergraduate medical curriculum on medical graduates’ future careers, publications and motivation for scientific research.

An online questionnaire was sent through the Alumni Association of the Arabian Gulf University (AGU) to medical graduates who have valid email addresses, seeking information on their scientific productivity along with demographic and current employment data. Responses were collated and analyzed using a standard statistical software package. The chi-square test and p-value were calculated. P-value <0.05 was considered statistically significant.

Completed forms were received from 91 medical graduates. In this sample, almost a quarter of the respondents have published a research paper out of their undergraduate research project, and about 50% have published at least one paper (as main or co-author) after graduation. Both demographic and medical specialty was not related to the doctor's perception of the benefits they have attained from the compulsory undergraduate research program. However, medical graduates who are at senior levels in their medical careers and those who are employed in secondary healthcare are significantly more likely to publish research papers.

The compulsory community-oriented, project-based research program in AGU has positively contributed to the research productivity of graduates, and it would be worthwhile to include such programs as an integral part of the undergraduate medical curriculum.

The purpose of this paper is to investigate the way technology affects the provision of prehospital emergency care, upgrading the quality of services offered and significantly reducing the risk of premature termination of the patients.

The paper presents the development of the eEKAB, a pilot emergency medical information system that simulates the main services offered by the Greek National Instant Aid Centre (EKAB). The eEKAB was developed on an agile system methodology. From a technical perspective, the features and the technology were mainly chosen to provide reliable and user-friendly interfaces that will attract many users. eEKAB is based on three important pillars for offering health care to the patients: the “On-time Incident Reporting”, the “On-time Arrival at the Incident” and “Transfer to the Health Center”. According to the literature review, the emergency medical services (EMS) systems that combine all the features are very few.

It reduces the total time of the EMS procedures and it allows for an easier management of EMS, by providing a better allocation of human resources and a better geographical distribution of ambulances. The evaluation displayed that it is a very helpful application for the ambulance drivers as it reduces the ambulance response time to arrive in the patient's location and contributes significantly to the general performance of the prehospital medical care system. Also, the survey verified the importance of implementing eEKAB on a larger scale beyond the pilot usage. It is worth mentioning that the younger ambulance drivers had a more positive view for the purpose of the application.

The paper clearly identifies implications for further research. Regarding interoperability, the mobile app cooperates with the Operational Center of EKAB, while further collaboration could be achieved with other operational ambulance handling center, mainly, of the private sector. The system can evolve to include better communications among the EKAB departments. Particularly, the ambulance crew as well as the doctors should be informed with more incident features such as the emergency signal so that they know whether to open the siren, the patient's name, etc. The authors are currently working on implementing some features to provide effective medical health services to the patient in the ambulance.

eEKAB will have very significant implications in case of its enforcement, such as the reduction of the total time of EMS procedures with a corresponding reduction of the operating costs of an accident management system and an ambulance fleet handling system while in parallel informing in time the doctors/clinics. It will provide better distribution of ambulances as well as of total human resources. It will greatly assist ambulance drivers, while reducing ambulance response time to reach the patient's location. In other words, the authors will have a better performance of the whole prehospital care system.

Providing emergency care before the hospital is of great importance for upgrading the quality of health services provided at the accident site, thus significantly reducing the risk of premature death of patients. This in itself has a significant social implication.

The paper demonstrates a solid understanding in the field of the EMS systems and the corresponding medical services offered. It proposes the development of an effective, feasible and innovative EMS information system that will improve the existing emergency health care system in Greece (EKAB). An in depth literature review and presentation of the adopted new technologies and the respective architecture take place. An evaluation and statistical validation were conducted for proving the high applicability of eEKAB in case of real-life running.

The teaching and learning of anatomy has experienced a significant paradigm shift. The present study assessed the level of knowledge in anatomy in medical postgraduate students and explored the impact of interventions in the form of anatomical videos on knowledge obtained. An awareness of the importance of human anatomy for clinical skills was created to ensure a certain level of competence be achieved by the end of the anatomy course.

Postgraduate medical students were recruited from various specialties on voluntary basis. The first step was to conduct a preliminary screening exam to determine the level of anatomical knowledge. The students were then divided into two groups at random, one of which received no intervention (the control group), and the other of which watched the videos with content that was pertinent to the practical demonstrations (intervention). To assess the effects of the video intervention, a post-test was administered to all students.

Both spot tests (SPOTs) and short answer question (SAQ) components for scores of all the regions from the intervention groups were comparable to the scores obtained by the post-test control group, although the findings were not significant (p > 0.05). However, the intervention group from the abdomen (ABD) region did perform significantly better (p < 0.05) than the screening test score.

The results of the research study imply that interventions like anatomical videos can bridge the postgraduate trainee’s anatomy knowledge gap in a practical method which will immensely help in increasing their knowledge.

Bullying negatively affects victims’ mental health and has been shown to be associated with anxiety and depression. Moreover, many studies have reported the prevalence of mistreatment among medical students (MS), interns and junior physicians. However, there are limited studies on bullying in the Middle East, and no studies on higher education in Bahrain. The authors’ aim was to investigate and compare the prevalence of bullying between MS at a major public university and non-medical students (NMS) at a private university in Bahrain. The authors also sought to explore the associations between bullying, depression and anxiety.

The authors conducted a survey-based cross-sectional study from October 1 to December 31, 2018, using convenient sampling method. A total of 300 students (150 MS and 150 NMS) participated in the study by answering a questionnaire that explored exposure to different types of bullying. In addition, standard anxiety and depression instruments were distributed to students.

The results showed that MS were more exposed to bullying than NMS, with a significant number (41%) reporting mistreatment from multiple sources, including teachers, consultants and peers. Furthermore, the authors found that bullying was significantly correlated with psychological health, anxiety and depression.

There are limited studies on bullying in the Middle East and no studies on the topic of higher education in Bahrain. Furthermore, the learning environment of tertiary education institutions can be improved by addressing the concerns associated with bullying identified in this study.

The purpose of this study is to examine the role of artificial intelligence (AI) in transforming the healthcare sector, with a focus on how AI contributes to entrepreneurship and value creation. This study also aims to explore the potential of combining AI with other technologies, such as cloud computing, blockchain, IoMT, additive manufacturing and 5G, in the healthcare industry.

Exploratory qualitative methodology was chosen to analyze 22 case studies from the USA, EU, Asia and South America. The data source was public and specialized podcast platforms.

The findings show that combining technologies can create a competitive advantage for technology entrepreneurs and bring about transitions from simple consumer devices to actionable healthcare applications. The results of this research identified three main entrepreneurship areas: 1. Analytics, including staff reduction, patient prediction and decision support; 2. Security, including protection against cyberattacks and detection of atypical cases; 3. Performance optimization, which, in addition to reducing the time and costs of medical procedures, includes staff training, reducing capital costs and working with new markets.

This study demonstrates how AI can be used with other technologies to cocreate value in the healthcare industry. This study provides a conceptual framework, “AI facilitators – AI achievers,” based on the findings and offer several theoretical contributions to academic literature in technology entrepreneurship and technology management and industry recommendations for practical implication.

Patient safety focuses on minimizing risks that might occur to patients during provision of healthcare. The purpose of this study was to explore healthcare practitioners’ attitudes towards patient safety inside different hospital settings in Jeddah, Kingdom of Saudi Arabia.

A descriptive, cross-sectional study was conducted on a sample of healthcare practitioners in main hospitals in Jeddah. Two main hospitals (one governmental and one private) were selected from each region of Jeddah (east, west, north and south), with a total number of eight out of thirty hospitals. Data were collected through the Attitudes to Patient Safety Questionnaire III that was distributed online. The questionnaire used a 5-point scale. Descriptive statistics were used. Comparisons were made by independent t-test and ANOVA. The statistical significance level was set at p < 0.05.

The study included 341 healthcare practitioners of different sexes and specialties in eight major governmental and private hospitals in Jeddah. “Working hours as error cause” subscale had the highest mean score (4.03 ± 0.89), while “Professional incompetence as error cause” had the lowest mean score (3.49 ± 0.97). The total questionnaire had a moderate average score (3.74 ± 0.63). Weak correlations between the average score of the questionnaire and sex, occupation and workplace were found (−0.119, −0.018 and −0.088, respectively).

Hospitals need to develop targeted interventions, including continuing professional development programs, to enhance patient safety culture and practices. Moreover, patient safety training is required at the undergraduate education level, which necessitates health professions education institutions to give more attention to patient safety education in their curricula.

The study contributed to the existing literature on patient safety culture in hospital settings in Jeddah, Saudi Arabia. The insights generated by the study can inform targeted interventions to enhance patient safety culture in hospitals and improve patient outcomes.

The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.

This study is a narrative review of the literature.

The body of medical knowledge has grown far too large for human clinicians to parse. In theory, electronic health records could augment clinical decision-making with electronic clinical decision support systems (CDSSs). However, computer scientists and clinicians have made remarkably little progress in building CDSSs, because health data tend to be siloed across many different systems that are not interoperable and cannot be linked using common identifiers. As a result, medicine in the USA is often practiced inconsistently with poor adherence to the best preventive and clinical practices. Poor information technology infrastructure contributes to medical errors and waste, resulting in suboptimal care and tens of thousands of premature deaths every year. Taiwan’s national health system, in contrast, is underpinned by a coordinated system of electronic data systems but remains underutilized. In this paper, the authors present a theoretical path toward developing artificial intelligence (AI)-driven CDSS systems using Taiwan’s National Health Insurance Research Database. Such a system could in theory not only optimize care and prevent clinical errors but also empower patients to track their progress in achieving their personal health goals.

While research teams have previously built AI systems with limited applications, this study provides a framework for building global AI-based CDSS systems using one of the world’s few unified electronic health data systems.

This study specifically seeks to investigate the strategic implementation of machine learning (ML) algorithms and techniques in healthcare institutions to enhance innovation management in healthcare settings.

The papers from 2011 to 2021 were considered following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. First, relevant keywords were identified, and screening was performed. Bibliometric analysis was performed. One hundred twenty-three relevant documents that passed the eligibility criteria were finalized.

Overall, the annual scientific production section results reveal that ML in the healthcare sector is growing significantly. Performing bibliometric analysis has helped find unexplored areas; understand the trend of scientific publication; and categorize topics based on emerging, trending and essential. The paper discovers the influential authors, sources, countries and ML and healthcare management keywords.

The study helps understand various applications of ML in healthcare institutions, such as the use of Internet of Things in healthcare, the prediction of disease, finding the seriousness of a case, natural language processing, speech and language-based classification, etc. This analysis would help future researchers and developers target the healthcare sector areas that are likely to grow in the coming future.

The study highlights the potential for ML to enhance medical support within healthcare institutions. It suggests that regression algorithms are particularly promising for this purpose. Hospital management can leverage time series ML algorithms to estimate the number of incoming patients, thus increasing hospital availability and optimizing resource allocation. ML has been instrumental in the development of these systems. By embracing telemedicine and remote monitoring, healthcare management can facilitate the creation of online patient surveillance and monitoring systems, allowing for early medical intervention and ultimately improving the efficiency and effectiveness of medical services.

By offering a comprehensive panorama of ML's integration within healthcare institutions, this study underscores the pivotal role of innovation management in healthcare. The findings contribute to a holistic understanding of ML's applications in healthcare and emphasize their potential to transform and optimize healthcare delivery.