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This paper aims to study a dynamic post-disaster emergency planning (PDEP) problem in an integrated network through the investigation of the selection of shelters, medical centers and distribution centers (DCs), and the allocation of evacuees and injured people. The resource and people assignment in multiple periods are considered.

A mathematical formulation is provided for the PDEP problem. The authors decompose the model into two sub-models as follows: the primary model is an integer programming model and the subproblem is a nonlinear programming model with continuous variables. The simulated annealing is used to solve the primary problem, and particle swarm optimization (PSO) mixed with beetle antennae search (BAS) is used to solve the subproblem.

The paper finds that BAS can increase the stability of PSO and keep the advantages of PSO’s rapid convergence. By implementing these algorithms on emergency planning after the Wenchuan earthquake that happened in China in 2008, this paper finds that the priority of different levels of injured people is influenced by several factors. Even within the same disaster, the priority of different levels of injured can be inconsistent because of the differences in resource levels.

The authors integrate the shelters, medical centers and DCs as a system, and simultaneously, consider evacuees and injured people and different resource assignments. The authors divide the injured people into three levels and use survival rate function to simulate the survival conditions of different people. The authors provide an improved PSO algorithm to solve the problem.

This paper aims to investigate how value drivers of internet medical business model affect value creation through a configurational approach. The internet medical business model (IMBM) is such a business model that integrates online and offline medical services with the driving force of internet technologies covering prediagnosis, in-diagnosis and postdiagnosis. The outbreak of COVID-19 and the support of national policies have boosted the development of internet health care. However, there are still many challenges in practice, such as the unclear innovation path, as well as difficulties in landing and profiting. Academic research has not yet provided sufficient theoretical insights. Therefore, to better explain and guide practice, it is urgent to clarify the innovation path and mechanism of value creation for IMBM.

Based on the sample of 58 internet medical firms in China, this paper adopts fuzzy-set qualitative comparative analysis (fsQCA) to explore the configurational effects of IMBM’s value drivers on value creation.

Building on the business model canvas and the characteristics of internet health care, five value drivers of IMBM are identified, namely, functional value proposition, emotional value proposition, user involvement, resource capabilities and connection properties. And the five value drivers form three configurations, which are, respectively, labeled as resource-driven configuration, user-operated configuration and product-combined configuration. From the perspective of the integration of traditional and emerging theories, such as resource-based view, internet economics and value cocreation, each configuration leads to value creation and improves value results with different mechanisms behind it.

First, combined with the business model canvas and the characteristics of internet health care, this paper identifies five value drivers of IMBM, thus improving the relevant research on internet health care. Second, based on the configurational effects, this paper discusses the mechanism behind the configurational effects of IMBM’s value drivers on value creation, thus expanding relevant research on the value creation of business models. Third, applying fsQCA and combining the advantages of qualitative research and quantitative research, this paper adds to the configurations of IMBM’s value drivers that achieve high-value results.

As international users increase rapidly, multilingual systems have become a very important service for global users. The purpose of this paper is to design and implement an ontology‐driven medical information retrieval (OMIR) system by building a medical ontology based on the Centers for Disease Control and Prevention's (CDC) medical records.

A traditional cataloging scheme is used as a navigation menu in the CDC system. This traditional cataloging scheme is transformed to a unique medical ontology for global users in the OMIR system. An experimental study was conducted on both an ontology‐driven medical information system (OMIR) and the CDC system.

The medical ontology can be used to filter out unsuitable resources based on semantic relationships. In addition, the recommended resources can be categorized and provide the patron with different languages to access resources. The OMIR system provides better relevancy and shorter search times compared with alternative systems.

The OMIR system is currently implemented for medical resources from the CDC. The developed method may also be applied to other domain areas.

This paper represents a practical method of building a multilingual medical information retrieval system and explains the functional use of ontological knowledge. This study provides insights into medical information seeking performance on the medical database systems.

This paper aims to focus on the information literacy skills and how the resources are being used by medical students of Mahatma Gandhi Medical College and Research Institute (MGMCRI), Pondicherry, India. The main aim is to determine the medical students use, purpose, search strategies and sources through which aware and literacy skills acquired. Further, this paper aims to bring out the problems faced.

A survey method was conducted through a structured questionnaire distributed among 120 medical students from first year to fourth year. Stratified random sampling was used for selection of students.

Findings of the study revealed that medical students largely used medical databases such as Bentham Sciences, ProQuest, PubMed and MedlinePlus. Further, the paper reveals that majority used health information for updating their knowledge and to acquire general information. The students’ information literacy level found minimal, which may be the reason majority of the students found difficulty in locating the desired materials followed by irrelevant information, inadequate e-resources and lack of awareness reported some extent.

The recommendations made based on the study are expected to be beneficial to the authorities and library administration of the surveyed institution to take appropriate measures for effective utilization of resources.

Medicine is heavily dependent on images and health care professionals use medical images for clinical, educational and research purposes. This paper aims to investigate the resources used by health care professionals while searching for medical images.

The research is based on a qualitative study that uses the Straussian version of grounded theory and involved 29 health care professionals from various health and biomedical departments working within Sheffield Teaching Hospitals NHS (National Health Service) Foundation Trust. Data collection was carried out using semi‐structured interviews and think‐aloud protocols.

The findings show that health care professionals seek medical images in a variety of visual information sources, including those found online and from published medical literature. The research also identified a number of difficulties that health care professionals face when searching for medical images in various image resources.

There have been few studies that investigated the image resources used by health care professionals. Thus, this study contributes to the understanding of medical image resources and information needs of health care professionals. A clear understanding of the medical image information needs of health care professionals is also vital to the design process and development of medical image retrieval systems.

Current covid-19 pandemic challenges health-care ethics. Ones of the most important challenges are medical resources allocation and a duty to treat, often addressed to medical personnel. This paper suggests that there are good reasons to rethink our health-care ethics for future global catastrophic risks. Current pandemic shows how challenging can be an issue of resources allocation even in a relatively small kind of catastrophic event such as covid-19 pandemic. In this paper, the authors show that any future existential bigger catastrophe may require new guidelines for the allocation of medical resources. The idea of assisted dying is considered as a hypothetical scenario.

This is a conceptual work based on conceptual analysis at the intersection of risk studies, health-care ethics and future studies. This study builds the argument on the assumption that the covid-19 pandemic should be treated as a sort of global catastrophic risk. Findings show that there are no such attempts in currently published peer-reviewed academic literature. This is crucial concept for the meta-analysis. This study shows why and how current pandemic can be interpreted in terms of global catastrophic risk even if, literally, covid-19 does not meet all criteria required in the risk studies to be called a global catastrophe.

We can expect an emergence of discriminatory selection policy which will require some actions taken by future patients like, for example, genetic engineering. But even then it is inevitable that there will still be a large number of survivors who require medical assistance, which they have no chance of receiving. This is why this study has considered the concept of assisted dying understood as an official protocol for health-care ethics and resources allocation policy in the case of emergency situations. Possibly more controversial idea discussed in this paper is an idea of assisted dying for those who cannot receive required medical help. Such procedure could be applied in a mass-scale during a global catastrophic event.

Philosophers and ethicists should identify and study all possible pros and cons of this discrimination rule. As this study’s findings suggested above, a reliable point of reference is the concept of substantial human enhancement. Human enhancement as such, widely debated, should be studied in that specific context of discrimination of patients in an access to limited medical resources. Last but not least, scientific community should study the concept of assisted dying which could be applied for those survivors who have no chance of obtaining medical care. Such criteria and concepts as cost-benefit analysis, the ethics of quality of life, autonomy of patients and duty of medical personnel should be considered.

Politicians and policymakers should prepare protocols for global catastrophes where these discrimination criteria would have to be applied. The same applies to the development of medical robotics aimed at replacing human health-care personnel. We assume that this is important implication for practical policy in healthcare. Our prediction, however plausible, is not a good scenario for humanity. But given this realistic development trajectory, we should do everything possible to prevent the need for the discriminatory rules in medical care described above.

This study offers the idea of assisted dying as a health-care policy in emergency situations. The authors expect that next future global catastrophes – looking at the current pandemic only as a mild prelude – will force a radical change in moral values and medical standards. New criteria of selection and discrimination will be perceived as much more exclusivist and unfair than criteria applied today.

This paper aims to present recently published resources on library instruction and information literacy providing an introductory overview and a selected annotated bibliography of publications covering all library types.

This paper introduces and annotates English-language periodical articles, monographs, dissertations, reports and other materials on library instruction and information literacy published in 2018.

The paper provides a brief description of all 422 sources, and highlights sources that contain unique or significant scholarly contributions.

The information may be used by librarians and anyone interested as a quick reference to literature on library instruction and information literacy.

The purpose of this article is to identify enabling and inhibiting factors that influence patients during their consideration of medical tourism for their healthcare requirement. The research provides marketing and practice implications that help in promoting medical tourism service. Furthermore, the paper provides evidence from medical tourism service to establish the relationship between resource integration and adoption of the service.

The article takes a two‐pronged exploratory study approach, with study one focusing on analysing prospective medical tourists' emotional impediments in their consideration of the service, while study two analyses the factors that helped medical tourists who have already availed the service, overcome the impediments.

In this article, it is identified that resource integration, particularly social resources, has a major impact on individual's decision to adopt a service. The exploratory study indicates that perceived knowledge disadvantage, lack of perceived control, and lack of social support in the destination country lead causes emotional discomfort to medical tourists. The study also indicates that the ability to integrate social resources available to them helped prospective medical tourists in their assessment of medical tourism service prior to adopting it. The article establishes that integration of social resources enables the patients to overcome the emotional discomfort and thus pursues to adopt medical tourism service.

While previous medical tourism service research has primarily focused on cognitive factors in patients' decision making such as quality and cost of healthcare services in destination countries, this article throws light on the enabling and inhibiting factors that influence adoption of medical tourism service.

Economists seem to be studying every nook and cranny of the field of medical care, from cost‐benefit analyses of medical technology to economies of scale in hospital size, the utilisation of non‐physician personnel to render care, the effects of pre‐paid financing and care systems, and so on, across an apparently highly divergent range of concerns. Obviously, what these studies have in common is their general subject, ‘medical care financing delivery, and utilisation’, But do they represent only a patchwork approach to understanding the economic features of the ‘real’ system of producing and consuming medical care, or are they somehow systematically, if not always clearly, related to each other? It is argued here that what seems to be a random, unrelated set of studies are indeed closely unified: and together they comprise an integrated analysis of the broad sector of medical care economics.

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.