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There are two main objectives in this study. First, we aim to develop a set of constructs for health task management support (HTMS) features to evaluate which health-related tasks are supported by mobile health application (mHealth app) functions. Second, drawing on innovation resistance theory (IRT), we examine the impacts of the newly developed HTMS dimensions on perceived usefulness, alongside other barrier factors contributing to technology anxiety.

Using a mixed-method research design, this research seeks to develop new measurement scales that reflect how mHealth apps support older adults’ health-related needs based on interviews. Subsequently, data were collected from older adults and exploratory factor analysis was used to confirm the validity of the new scales. Partial least squares structural equation modeling (PLS-SEM) was used to analyze survey data from 602 older adults.

The PLS-SEM results indicated that medical management task support, dietary task support, and exercise task support were positively associated with perceived usefulness, while perceived complexity and dispositional resistance to change were identified as antecedents of technology anxiety. Perceived usefulness and technology anxiety were found to positively and negatively influence adoption intention, respectively.

This study enriches the information systems literature by developing a multidimensional construct that delineates how older adults’ health-related needs can be supported by features of mHealth apps. Drawing on IRT, we complement the existing literature on resistance to innovation by systematically examining the impact of five types of barriers on technology anxiety.

The study aims to examine the extent of the corporate social responsibility (CSR) disclosure of Canadian cannabis firms and how they view responsibility. It also explores how cannabis firms build their CSR-based organizational identity through Twitter.

Deductive and inductive content analyses were carried through on tweets for a sample of 18 firms listed on the Canadian marijuana index during the legalization period of the recreational use of cannabis.

The results of this study show that cannabis firms approach responsibility by focusing on consumer and community/local development and by raising awareness and providing product information. The findings also highlight that the firms build their organizational identity mainly around their products’ medical benefits, the scientific efforts behind product development and the continual stigmatization they experience. At the industry level, cannabis firms attempt to build a harmonized identity to neutralize stigma.

This study allowed for a comprehensive understanding on how cannabis firms position themselves within an emergent sin industry and how they create their CSR identity through Twitter. It advances our understanding on the meaning of responsibility about the specific and distinctive features of the cannabis industry. From the methodology side, this study developed two content analysis tools: a coding instrument and a dictionary. These tools could be useful for conducting future studies related to the CSR disclosure of cannabis firms worldwide.

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.

This study aims to investigate the adoption and use of electronic health record systems (EHRS) in Tanzanian public primary healthcare institutions. The study’s objectives include understanding the factors that affect EHRS adoption, identifying implementation challenges and evaluating the effect of EHRS usage on healthcare delivery. By addressing these research goals, the study aims to contribute insightful information on the current level of EHRS adoption in Tanzanian primary healthcare facilities and contribute to developing strategies to improve EHRS deployment and healthcare in the nation.

This study combined quantitative and qualitative data using a mixed-methods methodology. Both data types were collected and analysed concurrently using a concurrent triangulation approach. The study aimed to comprehend the variables that affect the adoption and use of EHRS in Tanzanian public primary healthcare institutions. Eleven regions spanning various geographic locations and urban–rural dynamics were chosen as research sites. A survey of 122 healthcare employees was conducted with a sample of 31 healthcare facilities. The questionnaire had closed-ended and open-ended questions to gather quantitative and qualitative data. Descriptive statistics and thematic analysis were used in data analysis. Throughout the investigation, ethical standards and confidentiality precautions were observed.

Several factors affect the adoption and use of EHRS. Perceived usefulness and use, support and training, interoperability, data security and privacy, business culture and leadership are all factors. Inadequate infrastructure, power interruptions, duplication of effort and a lack of data analytic expertise were among the difficulties. Among the effects were improvements in data management, service delivery and coordination, productivity and efficiency, medical supply inventory control, billing and revenue collection.

This study, which complements earlier research that has concentrated chiefly on specialised healthcare settings, gives new insights by investigating the adoption and utilisation of EHRS, especially in primary healthcare institutions. The findings give policymakers and healthcare professionals in Tanzania and other nations vital information to help them decide whether to embrace and use EHRS in primary healthcare.

This qualitative case study aims to identify and analyse the factors influencing the implementation and effectiveness of electronic health record systems (EHRS) in primary health-care (PHC) facilities in Tanzania. This study aims to explore ways to optimize the use of EHRS for better health-care service delivery.

The study uses a qualitative case study design. Data were collected through interviews and focus groups conducted with health-care workers and information and communication technology officers at the PHC facilities in Tanzania. Purposive sampling and data source triangulation were used to address potential biases and limitations associated with the study’s small sample size.

This study identifies several key findings related to the implementation and effectiveness of EHRS in Tanzanian PHC facilities. The primary obstacles include inadequate technical infrastructure, poor internet connectivity and insufficient financial resources. The study suggests a comprehensive strategy for improving EHRS, emphasizing patient and health-care professional involvement in system design, investments in technical infrastructure and connectivity, data quality and accuracy and ongoing technical support and training.

This research contributes to the existing body of knowledge by offering a nuanced understanding of the Tanzanian health-care context. It emphasizes the need for tailored solutions and strategies specific to the region’s challenges and opportunities. The study’s originality lies in its focus on EHRS in the Tanzanian context, providing valuable insights for future initiatives. A key policy implication underscores the importance of a supportive regulatory framework, dedicated resources and consistent stakeholder communication for successful EHRS implementation.

Purpose: This study investigates the role of telemedicine in sustaining healthcare systems in Europe, during the COVID-19 pandemic. It focusses on how telemedicine serves as a strategic response to modern healthcare challenges, emphasising its efficiency, accessibility, and patient-centred nature.

Need for the study: The need for this study arises from the escalating demands on healthcare systems, especially during the COVID-19 pandemic. It aims to understand the adoption of telemedicine practices across European Union (EU) countries and their impact on healthcare sustainability.

Methodology: This study employs hierarchical and K-Means clustering to analyse EU citizens’ attitudes towards teleconsultations during COVID-19. Principal component analysis (PCA) is used for data compression and insight extraction. Data is sourced from Eurofound’s 2020 and 2021 surveys, involving extensive participant responses across the EU.

Findings: The study’s findings reveal significant shifts towards digital healthcare solutions, such as an increase in online consultations and prescriptions. It identifies different patterns of telemedicine use across EU countries, influenced by socioeconomic and geographical factors. These findings offer insights into future healthcare policy and strategy development.

Practical implications: The findings provide valuable insights into the shifts in telemedicine adoption in the EU, highlighting the significance of economic and sociological factors in healthcare trends. This study stresses the importance of customising healthcare strategies to suit the unique needs and digital capabilities of different countries.

Professional Identity Formation is the dynamic evolution to “think, act and feel” to become part of a professional community. This document presents the development and the study that aimed to assess the usability of a m-Learning Identity App (MLIA) focused on the formation of professional identity among undergraduate medical students.

MLIA development included four phases: Conceptual, prototype, pilot and implementation, before further deployment. The conceptual model was designed by eight faculty members from three Latin American universities. The prototype was developed and tested with stakeholders. The pilot was performed during 5 weeks before the implementation. Cross-sectional data collected during implementation from 138 medical students who completed a survey to assess the usability of MLIA are presented. During deployment, 977 posts were made on Professional Identity Formation, and examples of these posts are presented.

The prototype and pilot phases demanded improvements. The survey explored (1) Familiarity, (2) Perceived ease of use, (3) Perceived usefulness for Professional Identity Formation, (4) Satisfaction, (5) Intention to reuse (6) Digital aesthetics and (7) Safety. Results from the usability assessment suggest that students perceived MLIA as a secure space with positive aesthetics and ease of use.

Important limitations of the present study include, firstly, that it does not provide information on the effectiveness of the MLIA in shaping professional identity in medical students, it focuses exclusively on its development (conceptual model, prototype, pilot and implementation) and usability. Secondly, the study design did not consider a control group and, therefore, does not provide information on how the App compares with other strategies addressing self-reflection and sharing of meaningful experiences related to professional identity.

MLIA introduces a different approach to education, simulating a secure, easy-to-use, social media with a friendly interface in a safe environment to share academic and motivational moments, transitioning from being to becoming a professional.

The main purpose of this paper is to outline the antecedents of patient satisfaction in the field of medical tourism (MT) applying extant literature and to develop a conceptual model based on the review.

This paper presents a thorough review of prior studies related to the antecedents of patient satisfaction in the MT sector. Moreover, it provides the theoretical base that helped the researcher to identify significant relationship between the patient satisfaction and its antecedents.

The researchers identified the prominent antecedents of patient satisfaction and present the potential interrelationships between different antecedents of patient satisfaction such as treatment quality, cost attractiveness, destination image and service quality with patient satisfaction based on the review.

The results have momentous practical implications as they will help researchers to better understand the antecedents of patient satisfaction and their potential inter linkages with patient satisfaction in MT sector. The conceptual model derived from the review may guide the actions of researchers as well as practitioners in the MT industry as a whole. The present study provides insights for further research in the MT sector and thereby helps to further enrich the existing theoretical base of the MT.

The study brings together the scattered knowledge from the broad and extensive range of medical or health tourism and cognate literature which indicate ideological differences among various aspects of MT as well as potential factors determining patient satisfaction in MT sector (antecedents of satisfaction). The newly developed model incorporates a new construct called “treatment quality” as different from “service quality,” which is a widely used construct to explain customer satisfaction. The antecedents of patient satisfaction and their inter-linkages with patient satisfaction provide a sound theoretical foundation for the future studies.

The primary objective of this article is to examine current procurement, inventory control and management practices in modern healthcare, with a particular focus on the procurement and management of surgical supplies in a prominent public, highly specialized healthcare sector.

This study was conducted in three phases. In Phase 1, the study team interacted with various hospital management stakeholders, including the surgical hospital store, examined the current procurement process and identified challenges. Phase 2 focused on selecting items for a detailed study and collected the qualitative and quantitative details of the store department of the healthcare sector chosen. A detailed study analyzed revenue, output/demand, inventory levels, etc. In Phase 3, a decision-making framework is proposed, and inventory control systems are redesigned and demonstrated for the selected items.

It was observed that the demand for many surgical items had increased significantly over the years due to an increase in disposable/disposable items, while inventories fluctuated widely. Maximum inventory levels varied between 50 and 75%. Storage and availability were important issues for the hospital. It is assumed the hospital adopts the proposed inventory control system. In this case, the benefits can be a saving of 62% of the maximum inventory, 20% of the average stock in the system and optimal use of storage space, improving the performance and productivity of the hospital.

This study can help the healthcare sector administration to develop better systems for the procurement and delivery of common surgical items and efficient resource allocation. It can help provide adequate training to store staff. This study can help improve management/procurement policies, ordering and delivery systems, better service levels, and inventory control of items in the hospital business context. This study can serve as a pilot study to further investigate the overall hospital operations.

This study can help the healthcare sector administration develop better systems for procuring and delivering common surgical items and efficient resource allocation. It can help provide adequate training to store staff. This study can help improve management/procurement policies, ordering and delivery systems, better service levels and inventory control of items in the hospital business context. This study can serve as a pilot study to further investigate the overall hospital operations.

This study is an early attempt to develop a decision framework and inventory control system from the perspective of healthcare inventory management. The gaps identified in real hospital scenarios are investigated, and theoretically based-inventory management strategies are applied and proposed.

Artificial intelligence (AI) applications are increasingly used for day-to-day operations in healthcare. Each has a relatively limited scope or task, and several find application in managerial and organizational processes. More and more, AI and machine learning (ML) devices have received US FDA approval in the last decade. This chapter covers the main AI applications in healthcare, with a focus on organizational AI solutions (administrative AI), the main AI developers, their investment and real-world data and case studies in healthcare and other sectors. AI can be applied in resource management and procurement, resource allocation, clinical case management, staff work shift scheduling and handling of emergencies. AI applications are becoming ubiquitous in hospital (e.g. emergency room and operating theatre) and outpatient settings (e.g. ambulatory care and dentistry clinics). Their implementation is expected to bring direct benefits for patient care and satisfaction. This chapter gives a broad definition of AI in healthcare settings, with a focus on administrative applications and their use in case study data.