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The mass exodus of the professional healthcare workforce has become a cankerworm for a developing nation like Nigeria, and this worsens the already depleted healthcare systems in underdeveloped nation. This study investigated the rationale behind medical workers' brain-drain syndrome and the quality healthcare delivery in the Nigerian public healthcare sector.

To stimulate an understanding of the effect of the phenomenon called brain drain, the study adopted a diagnostic research design to survey the public healthcare personnel in government hospitals. The study administered a battery of adapted research scales of different measures to confirm the variables of interest of this study on a probability sampling strategy. The study surveyed 450 public healthcare sector employees from four government hospitals to gather pertinent data. The study used a structural equation model (SEM) and artificial neural networks (ANNs) to analyse the collected data from the medical personnel of government hospitals.

The findings of this study are significant as postulated. The study discovered that poor quality worklife experienced by Nigerian medical personnel was attributed to the brain-drain effect and poor healthcare delivery. The study further demonstrated that job dissatisfaction suffered among the public healthcare workforce forced the workforce to migrate to the international labour market, and this same factor is a reason for poor healthcare delivery. Lastly, the study discovered that inadequate remuneration and pay discouraged Nigerian professionals and allied healthcare workers from being productive and ultimately pushed them to the global market.

Practically, this study has shown three major elements that caused the mass movement of Nigerian healthcare personnel to other countries of the world and that seems novel given the peculiarity of the Nigerian labour market. The study is original and novel as much study has not been put forward in the public healthcare sector in Nigeria concerning this phenomenon.

This study aims to deepen the understanding of the challenges and implications entailed by deploying mobile clinics in conflict zones to reach populations affected by violence and cut off from health-care services.

This research combines an integrated literature review and an instrumental case study. The literature review comprises two targeted reviews to provide insights: one on conflict zones and one on mobile clinics. The case study describes the process and challenges faced throughout a mobile clinic deployment during and after the Iraq War. The data was gathered using mixed methods over a two-year period (2017–2018).

Armed conflicts directly impact the populations’ health and access to health care. Mobile clinic deployments are often used and recommended to provide health-care access to vulnerable populations cut off from health-care services. However, there is a dearth of peer-reviewed literature documenting decision support tools for mobile clinic deployments.

This study highlights the gaps in the literature and provides direction for future research to support the development of valuable insights and decision support tools for practitioners.

The purpose of this study is to analyse the crisis network response of European countries and the role played by defence organizations (DOs) during the early response phase of the pandemic, here set to encompass 75 days.

Published materials – reports, news and communications – provided by authorities and DOs were used. Some of the authors actively participated in national pandemic response networks. An exploratory approach and qualitative content analysis were applied. The data were collected in national languages from 13 European countries, and they were coded and analysed using the actors, resources and activities (ARA) framework.

This study identified three main categories of activity structures in which the DOs interacted with civilian members of response networks, health-related services, logistics services and public support services. These networks among actors were found within formal response systems and emergent networks. The DOs engaged as actors that provided a range of services when civil authorities could not cope with the huge demand for specific services and when resources were scarce in the initial response phase.

This study contributes by filling an important research gap with regard to the civil-military relations associated with the use of DO resources in the civil response to the pandemic crisis in Europe, which is described as an untraditional response. The ARA network approach provides a framework for arranging ARA and extends the wider civil-military network to expand the formal networks of the early crisis response. The study lays knowledge about the co-operation between civilian and military actors in different contexts and provides a broader understanding of the roles that DOs played in the response operations.

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.

This study aims to describe survivors of stroke circumstances, issues with providing care for survivors of stroke and services expected by caregivers and survivors of stroke.

A qualitative research design was conducted in Singburi Province. Data collection methods included in-depth interviews, focus groups and participatory observations. Semi-structured in-depth interview guides, quality-of-life scale and depression scale were used to collect data from survivors of stroke, their caregivers, health personnel, local governors and village health volunteers. Naturalistic research tradition was used for qualitative data analysis and descriptive statistics for quantitative data analysis.

The majority of survivors of stroke had hemiplegic limb and severe deficits in their activities of daily living. Caregivers were family members, and they often developed depression. Issues with providing care to stroke survivors included lack of knowledge about stroke and home care, inadequacy and discontinuity of care and the shortage of stroke care personnel in the community. A stakeholder's expected stroke services included the provision of effective continuing care, community participation in care and enhancing the village health volunteer's capacity.

This study illustrated the stroke service systems in rural Thai communities. The study's findings could be applied when planning future research using community participation to test a model of care for stroke survivors to promote better outcomes and be responsive to the needs of stroke survivors, especially those who are disabled.

The purpose of this paper is to describe the quality of life (QOL) and to examine factors predicting the QOL among the demographic characteristics, injury severity, effect on work, pain intensity, disability point, coping and resilience factors, in Thai patients following multiple injuries.

A cross-sectional research design was used. A total of multiple 106 trauma patients were obtained by simple random sampling. The patients were between 18 and 59 years of age, and had visited an outpatient clinic at one of three randomly selected tertiary hospitals in Metropolitan Bangkok, Thailand. Dependent variable was QOL measured by Trauma Outcome Profile (TOP) questionnaire. Independent variables were demographic and illness-related factors collected from patients’ medical records, coping measured by the Jalowiec Coping Scale, pain measured by the Chronic Pain Grade questionnaire (CPGQ) and resilience measured by the Connor-Davidson Resilience Scale (CD-RISC-10). Data were analyzed using descriptive statistics and multiple regression analysis.

Except for satisfaction, the other nine dimensions of the QOL in patients following traumatic injuries were poor. Pain intensity was the most influential factor predicting the QOL, but the patient’s resilience, emotional coping and disability points were also able to predict the QOL.

The TOP, CPGQ and CD-RISC-10 were translated into Thai and used in the current study for the first time. The results of the study revealed that the pain intensity, and the patient’s resilience and coping influenced the QOL more than other factors, such as the demographic data and injury severity.

The purpose of this paper is to examine emergency medical service (EMS) personnel’s perceptions and experiences of managing underground mining injury incidents.

In total, 13 EMS personnel were interviewed according to a semi-structured interview guide. The interviews were transcribed verbatim and analyzed using qualitative content analysis.

An underground mining environment was described as unfamiliar and unsafe and, with no guidelines for operational actions in an extreme environment, such as underground mines, the EMS personnel were uncertain of their role. They therefore became passive and relied on the rescue service and mining company during a major incident. However, the medical care was not considered to be different from any other prehospital care, although a mining environment would make the situation more difficult and it would take longer for the mine workers to be placed under definitive care.

This study complements earlier studies by examining the EMS personnel’s perceptions and experiences of major incidents.

This paper aims to examine the time it would take to provide medical prophylaxis for a large urban population in the wake of an airborne anthrax attack and the effect that various parameters have on the total logistical time.

A mathematical model that evaluates key parameters and suggests alternatives for improvement is formulated. The objective of the model is to minimize the total logistical time required for prophylaxis by balancing three cycles as follows: the loading cycle, the shipping cycle and the service cycle.

Applying the model to two representative cases reveals the effect of various parameters on the process. For example, the number of distribution centers and the number of servers in each center are key parameters, whereas the number of central depots and the local shipping method is less important.

Various psychological factors such as mass panic are not included in the model.

There are few papers analyzing the logistical response to an anthrax attack, and most focus mainly on the strategic level. The study deals with the tactical logistical level. The authors focus on the distribution process of prophylaxis and other medical supplies during the crisis, analyze it and identify the parameters that influence the time between the detection of the attack and the provision of effective medical treatment to the exposed population.

The purpose of this paper is to examine the relevance of Cuba’s medical system, its health tourism and related diplomacy in the context of the recent COVID-19 pandemic for the global response to disease outbreaks. In addition to Cuba being a destination for leisure tourists in the Caribbean, the renowned Cuban medical system attracts thousands of health tourists seeking low-cost but high-quality treatment. This paper demonstrates how Cuba’s unique response to the pandemic, which included sending thousands of medical staff abroad, can inform structural and global issues and contribute to a more sustainable future.

The research in this study is primarily drawn from published academic and media sources that address Cuba’s medical system, its health tourism and the government’s response to the recent pandemic. The author, a political scientist and an author of many publications on Cuba, and the PI of a study focused on Cuban tourism, will also draw on her expertise.

This paper addresses the Cuban Government’s ongoing response to the COVID-19 pandemic and places this response in the context of Cuba’s medical system, its health tourism and related diplomacy. It reveals key lessons from Cuba’s response for other tourist destination states and, more broadly, for the worldwide response to global outbreaks and the management of health systems. The findings will further research in diplomacy and tourism as well as inform policy and practice.

This paper explores an ongoing topic and thus further research will be required following the pandemic.

This research note offers important implications for practice including providing accurate, research-based information that challenges misinformation about Cuba’s health system, its medical diplomacy program, health tourism and its response to COVID-19. It offers valuable lessons for public health authorities including the importance of preventative health measures, community medicine and the benefits of working globally to combat outbreaks through the sharing of medical staff and resources.

This research note reveals the health, political and social implications of Cuba’s response in this time of crisis. It shows the benefits of a robust but low-cost community-based medicine program, medical diplomacy and how a state’s response during crisis can moderate the global inequities and injustices such as unequal access to care that often accompany disease outbreaks such as COVID-19.

This research note is an early analysis of a response by an important tourist destination country to the pandemic. The author anticipates that the information provided to the international community via this open access journal will offer practical implications for the ongoing global efforts to manage this crisis and contribute to the research on tourism, diplomacy, justice and health policy.

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.