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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.

Cannabis use continues to increase worldwide, and a number of nation states are changing their cannabis policies. Policy changes require research into key populations, namely, people who use cannabis. This study aims to examine sociodemographic differences of young Finns who reported using cannabis mainly for self-medication versus mainly recreationally, as well as their reported effects of cannabis use.

The data come from an anonymous online survey (N = 247, 70.0% males, 25.9% females, 4.1% other) that was analysed using multiple logistic regression. The authors focused on whether various demographic indicators differed between those who reportedly used cannabis mainly for recreational purposes and mainly for self-medicinal purposes. The authors also qualitatively examined the respondents’ experienced effects of cannabis, both desired and undesired.

Being older and female, living in a smaller city and earlier age of initiation of cannabis use were statistically significant in predicting the medicinal use of cannabis. The majority of recreational effects were related to themes such as relaxation and pleasure, but many participants also reported desired medical effects. Similarly, many participants reported several undesired effects.

Understanding especially young people’s motivations to use cannabis, which include using it for various medical effects, can improve the design of harm reduction and treatment programmes as well as enhance the well-being of people who use cannabis.

This study gives a nuanced account of sociodemographic factors and motivations of young people who use cannabis in Finland as well as the reported effects it has on them, which complements data from national drug surveys.

This paper aims to examine lean thinking in medical commodities supply chains by considering its applications and success factors. It determines the drivers and wastes of medical commodity supply chain, and the existing lean tools and practices together with their application in the supply chain processes. The paper also examined the challenges and success factors for effective lean application in the medical commodities supply chains.

The study used qualitative approaches, in-depth interviews and focus group discussions with key informants to form the basis for data collection. Through thematic analysis, the collected data were analyzed by developing themes reflecting the objectives of the study.

The main drivers for waste associated with the supply chain were demand management, supplier development, institutional framework and governance. The wastes were observed at the level of inventory, operation costs, transaction costs, delays in terms of service, commodity delivery time and quality. Digitalization, information technology and standardization were the tools for medical supply chain. Poor infrastructure, unreliable internet supply, environmental uncertainty and poor management support were challenges to realizing an effective supply chain.

Although the qualitative approach used in the study provides detailed information, a quantitative study covers a larger sample for generalization.

Capacity building and professionalism should be given a priority because the philosophy of lean focuses on waste removal and continuous improvement, which highly depends on the quality of human resource (Brito et al., 2020). Limited human resource capabilities in supply chain management will, therefore, result into poor operational efficiency, which are wasted. Moreover, systems interoperability is key waste minimization and, therefore, demands interventions.

The government under the Ministry of Health and other key sector ministries such as local and regional governments should better understand the role of the waste drivers and adopt system-wide reforms to support improvements to remove waste in the medical supply chain. For example, the current institutional framework creates an administrative block and hence leads to wastes. This bureaucratic procedure should be removed to minimize wastes along the chain.

This study is among the first studies to determine applicability and implementation of lean in a resource-constrained context. The paper identifies contextual factors for lean implementation. This paper focused on a holistic view of the entire supply chains to enhance a well-functioning supply chain in delivering health commodities.

This study aims to investigate the supply chain gaps during the COVID-19 pandemic in Tanzania amid the pandemic era.

This study adopted a mixed approach, using both structured questionnaires and individual interviews to gather raw data (quantitative and qualitative data). To assess quantitative data for statistical (descriptive and inferential) analysis, this study used a sample of 57 wholesale and retail pharmacies and 10 hospital pharmacies, which were randomly selected. The thematic analysis was applied to the gathered qualitative data to authenticate the quantitative findings and conclusions which were the outcome of the descriptive and inferential analysis (binary logistics regression) analysed by the SPSS.

The results revealed the presence of various supply chain gaps in terms of target gaps, time gaps and coverage gaps. This study highlighted the disruption on demand and uncertainty in business environment as ways that the COVID-19 pandemic contributed to the gaps and revealed the negative effects of the supply chain gaps on the effectiveness of medical supplies in Tanzania.

The results revealed the presence of various supply chain gaps (in terms of target gaps, time gaps and coverage gaps), underlined the disruption in demand and uncertainty in the business environment as ways that the COVID-19 pandemic contributed to the gaps and revealed the negative effects of the supply chain gaps on the effectiveness of medical supplies in Tanzania.

Data generated and used in this study is from participants from one country only (Tanzania), despite the supply chain gaps being common to many developing countries in general.

This study provides a novel framework in medical supply chain literature by identifying numerous disruptions in the medical supply chain which emerged during the COVID-19 emergence and serves as a basis for future studies on how to counter the gaps and rebuild a resilient and sustainable medical supply chain in developing countries.

This study aims to summarize the critical issues in medical federated learning and applicable solutions. Also, detailed explanations of how federated learning techniques can be applied to the medical field are presented. About 80 reference studies described in the field were reviewed, and the federated learning framework currently being developed by the research team is provided. This paper will help researchers to build an actual medical federated learning environment.

Since machine learning techniques emerged, more efficient analysis was possible with a large amount of data. However, data regulations have been tightened worldwide, and the usage of centralized machine learning methods has become almost infeasible. Federated learning techniques have been introduced as a solution. Even with its powerful structural advantages, there still exist unsolved challenges in federated learning in a real medical data environment. This paper aims to summarize those by category and presents possible solutions.

This paper provides four critical categorized issues to be aware of when applying the federated learning technique to the actual medical data environment, then provides general guidelines for building a federated learning environment as a solution.

Existing studies have dealt with issues such as heterogeneity problems in the federated learning environment itself, but those were lacking on how these issues incur problems in actual working tasks. Therefore, this paper helps researchers understand the federated learning issues through examples of actual medical machine learning environments.

Is humanity heading to immortal living? If so, what areas of society are playing an active role in achieving this? In order to understand this, the study explores the relationship between immortality and the wellness and medical tourism industry to seek potential relationships between them and ultimately, asks difficult questions about the growth of these tourism sectors and the potential need for greater regulation of them.

Taking a pragmatic philosophical approach and through the examination of refined information from secondary sources and published material and reports, the study presents original theoretical knowledge and a model exploring tourism and human immortality.

This paper argues that continued growth in the wellness and medical markets today could lead to a world where transhumanists and cyborgs are present in our world, even taking over from Homo sapiens. The study presents a model highlighting the potential role of wellness and medical tourism markets, illustrating the potential for future consumer services that could further fuel the search for immortality. Thus, how such markets and consumer desires are (in)directly supporting humanities desire for (non-human) immortal existence.

Today, individuals are driven by wellness practices and medical and cosmetic desires and are willing to travel the globe in search of companies who are either capable of carrying out the desired procedures or seeking prices more affordable to them. This research offers novel insights into these complex relationships and maps the affiliation between wellness and medical practices and the concept of immortality.

Medical research requires biological material and data collected through biobanks in reliable processes with quality assurance. Medical studies based on data with unknown or questionable quality are useless or even dangerous, as evidenced by recent examples of withdrawn studies. Medical data sets consist of highly sensitive personal data, which has to be protected carefully and is available for research only after the approval of ethics committees. The purpose of this research is to propose an architecture to support researchers to efficiently and effectively identify relevant collections of material and data with documented quality for their research projects while observing strict privacy rules.

Following a design science approach, this paper develops a conceptual model for capturing and relating metadata of medical data in biobanks to support medical research.

This study describes the landscape of biobanks as federated medical data lakes such as the collections of samples and their annotations in the European federation of biobanks (Biobanking and Biomolecular Resources Research Infrastructure – European Research Infrastructure Consortium, BBMRI-ERIC) and develops a conceptual model capturing schema information with quality annotation. This paper discusses the quality dimensions for data sets for medical research in-depth and proposes representations of both the metadata and data quality documentation with the aim to support researchers to effectively and efficiently identify suitable data sets for medical studies.

This novel conceptual model for metadata for medical data lakes has a unique focus on the high privacy requirements of the data sets contained in medical data lakes and also stands out in the detailed representation of data quality and metadata quality of medical data sets.

Under the Directive 2011/24/EU, medical tourism and cross-border health are interrelated terms regarding the freedom to move to get the most accessible medical treatment into EU Member State within the defined procedures for reimbursement. Little known empirically regarding the efficiency of the cross-border health/medical tourism industry. This study aims to measure its efficiency in Europe for the years 2010-2014, by using Data Envelopment Analysis (DEA).

Data obtained from OECD and the European Core Health Indicators (ECHI), which is collecting the data through Eurostat. Eurostat collects data on health-care activities and provides data on hospital discharges, including the hospital discharges of non-residents and these include hospital discharges of in-patients and day care patients. The analysis uses “DEA.P, 2.1 for windows” by Coelli (1996).

The results show that the Members States health systems were very efficient in handling non-residents in-patients; however, when managing day cases/outpatients, the efficiency scores dropped.

The findings would have significant associations affecting intentions to revisit clinics and the destination country. In addition, will be useful to those seeking a better understanding of the cross-border health and medical tourism industry efficiency.

Extending the findings of the European Commission report (2015c) by examining how well medical tourists are informed about the decision they are making, would be of perceived value. These are important indicators at European level by helping each Member State to measure its medical tourism services.