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The aim of this chapter is to understand the nature of business collaboration between healthcare service providers and tourism agencies in Malaysia. Interviews with 17 healthcare service providers in Malaysia reveal that most of the collaboration between healthcare service providers and tourism agencies in Malaysia is informal or loose, despite their intention to leverage on medical tourism for business expansion. Close and tight collaborations are rare. The findings point towards the main reasons behind the rare collaboration which are the high customer orientation of healthcare service providers, the strategic move of business and support for government agenda.

Digital transformation is one of the key concepts attached to the smart cities’ domain. The requirement to enhance strategically the way that business is delivered around different areas is a critical milestone for the digital transformation agenda and also for business performance management. In this short position chapter, we are focusing on the area of healthcare and we are providing key insights and lessons learned from Saudi Arabia. The main contribution of the chapter is a structured discussion on a digital healthcare strategy in the context of smart cities.

COVID-19 has profoundly shaped human interactions, and, within public healthcare systems, care relations. Through the lens of social suffering, this study explores how employee innovation is shaped by the pandemic crisis and different managerial approaches in the context of public geriatric care in Northeast Italy.

This study adopts a qualitative methodology. A total of 29 semi-structured, open-ended interviews were conducted with 23 healthcare professionals involved in geriatric care, with managerial and without managerial positions. Observation was integrated as auxiliary research to further capture on an operational level the interactions among the actors involved.

The COVID-19 crisis significantly shaped employee innovation for healthcare professionals, as the suffering it provoked in the system motivated and urged them to engage in innovative initiatives. Where employees’ engagement in innovation was recognized by the management, it was found that the suffering was mitigated, and creativity and solidarity emerged in the innovation process. Where top-down approaches did not recognize employees’ efforts and innovative initiatives, need-driven innovation and greater tensions came forward, enhancing the overall suffering in care relations and resulting in some employees considering leaving their profession.

This study is based on a single case study.

This study further highlights the employee participation in innovation as a crucial practical implication for sustaining the quality of public care and assistance. A practical implication emerging from this study suggests that “ordinary” healthcare professionals’ engagement in innovative initiatives and in their operationalization should be encouraged by the organization. In a system as complex as the public healthcare one, valuing the bottom-up, clinical inputs appears fundamental if innovation is to move away from mere technological adaptation to embrace a more comprehensive process, involving the professionals who are engaging in innovative endeavors. From a managerial point of view, adopting an approach that recognizes, supports and provides coordination to employee innovation seems instrumental to nurture an environment where employee voices feel heard, and creativity, solidarity and overall positive collaboration can occur. Thus, another significant practical implication includes the retention of healthcare professionals in the public sector in times of crisis.

With the outbreak of the COVID-19 pandemic, the necessity to explore the “human side” of innovation and its connection to emerging human needs during a crisis is growing. This study focuses on employee participation in innovation processes due to COVID-19, thus contributing to the employee-driven innovation (EDI) literature. Through the lens of social suffering, it scrutinizes the interactions between bottom-up perceptions and responses and top-down strategies in a public healthcare setting. Hence, this study addresses two major gaps present in EDI literature, for the most part focused on the private sector and on the managerial structures, tools and interventions.

Quality improvement has developed and spread, and today, all Swedish Regions emphasize that their strategies are based on systematic improvement. This paper aims to describe and illuminate the development of Quality Improvement (QI) in Swedish healthcare and welfare organizations by using publications in a Swedish context.

The overview synthesis is inspired by a scoping literature review approach of relevant literature. All publications relevant to Swedish healthcare and welfare settings between 1992 until 2020 were included.

In all, 213 papers, 29 books and chapters and 34 dissertations related to QI and research in Swedish healthcare and welfare context were identified. From 2011 to 2020, the publication rate increased rapidly. Six different focus areas emerged: systematic and value-creating improvement work; collaboration between organizations and healthcare providers; use of improvement methods and (theoretical) models; leadership and learning; measurements, quality registers and follow-up; and involvement and patient safety. Further QI development in Swedish healthcare and welfare points to an increased importance of collaboration between organizations and coproduction with beneficiaries for the healthcare and welfare services.

This paper is one of the first to describe and illuminate the QI development in the healthcare and welfare sector in a country. The trajectory also points to a need for coproduction to handle future challenges.

The primary objective of this study is to investigate the ethical implications of deploying AI-enabled chatbots in the healthcare sector. In addition, the research underscores trust and reliability as critical factors in addressing the ethical challenges associated with these chatbots.

This study takes a qualitative approach, conducting 13 semi-structured interviews with a diverse range of participants, including patients, healthcare professionals, academic researchers, ethicists, and legal experts. This broad spectrum of perspectives ensures a comprehensive understanding of the ethical implications of AI-enabled chatbots in healthcare. The rich exploratory data gathered from these interviews is then analysed using thematic analysis.

The findings of this study are highly significant in the context of AI-enabled healthcare chatbots. They highlight four major themes: developing trust, ensuring reliability, ethical considerations, and potential ethical implications. The interconnectedness of these themes forms a coherent narrative, highlighting the pivotal role of trust and reliability in mitigating ethical issues.

This study contributes to the existing literature on AI-enabled healthcare chatbots. It not only reveals potential ethical concerns associated with these technologies, such as data security, patient privacy, bias, and accountability, but it also places a significant emphasis on trust and reliability as critical elements that can boost user confidence and engagement in using AI-enabled chatbots for healthcare advice.

This study aims to investigate the role of information normalization in online healthcare consultation, a typical complex human-to-human communication requiring both effectiveness and efficiency. The globalization and digitization trend calls for high-quality information, and normalization is considered an effective method for improving information quality. Meanwhile, some researchers argued that excessive normalization (standardized answers) may be perceived as impersonal, repetitive, and cold. Thus, it is not appreciated for human-to-human communication, for instance, when patients are anxious about their health condition (e.g. with high-risk disease) in online healthcare consultation. Therefore, the role of information normalization in human communication is worthy to be explored.

Data were collected from one of the largest online healthcare consultation platforms (Dxy.com). This study expanded the existing information quality model by introducing information normalization as a new dimension. Information normalization was assessed using medical templates, extracted through natural language processing methods such as Bidirectional Encoder Representations from Transformers (BERT) and Latent Dirichlet Allocation (LDA). Patient decision-making behaviors, namely, consultant selection and satisfaction, were chosen to evaluate communication performance.

The results confirmed the positive impact of information normalization on communication performance. Additionally, a negative moderating effect of disease risk on the relationship between information normalization and patient decision-making was identified. Furthermore, the study demonstrated that information normalization can be enhanced through experiential learning.

These findings highlighted the significance of information normalization in online healthcare communication and extended the existing information quality model. It also facilitated patient decision-making on online healthcare platforms by providing a comprehensive information quality measurement. In addition, the moderating effects indicated the contradiction between informational support and emotional support, enriching the social support theory.

The coronavirus disease 2019 (COVID-19) pandemic represents one of the most significant disruptions to supply chains (SCs), stimulating both practitioners and scholars to seek ways to enhance supply chain performance (SCP). Recent advancements in technology, particularly supply chain analytics (SCA) technologies, offer promising avenues for mitigating risks associated with SC disruptions like those posed by the COVID-19 pandemic. However, the existing literature lacks a comprehensive analysis of the connection between SCA and healthcare SC (HSC) performance. To address this research gap, we employed the dynamic capability perspective to investigate the mediating roles of supply chain innovation (SCI), resilience (SCR) and flexibility (SCF) in the relationship between SCA and HSC performance. The study further examined the moderating role of a data-driven culture (DDC).

The proposed model was tested using survey data from 374 managers of healthcare facilities in Ghana. SPSS and Amos were used to analyze the data gathered.

The results showed that while SCA may drive HSC performance, the presence of SCI, SCR and SCF may serve as channels to drive enhanced HSC performance. Additionally, we also found that different levels of a DDC induce varying effects of SCA on SCI, SCR and SCF.

The study’s results have theoretical and practical implications, offering valuable insights for the advancement of SCA in healthcare literature. They also deepen SC managers’ comprehension of how and when SCA can boost HSC performance. However, as the study was limited to healthcare facilities in Ghana, its findings may not be universally applicable.

This study contributes to the literature by demonstrating that SCI, SCR, SCF and a DDC could serve as transformative mechanisms to reap superior HSC outcomes. This study also offers contemporary guidance to managers regarding SCA investment decisions.

The primary objective of this study is to investigate the cognitive aspects of spatial experiences of paediatric inpatients who receive long-term treatment in a healthcare setting in relation to the syntactic parameters of healthcare environment. It is aimed to investigate how the change in the child’s cognition caused by the environmental stress experienced by the child during his/her stay in the hospital is related to the physical parameters of the treatment space.

The methodology of the study is based on a correlational analysis to identify the cognitive and syntactic factors of the healthcare environment that contribute to changes in the perceptual processes of a sample group of thirty children. The study examined the relationships between the graph and isovist variables, and the cognitive parameters of paediatric inpatients. The two datasets were subjected to regression analyses in order to identify any significant findings, which allowed for a discussion of how the patients’ changing perceptual processes are influenced by the syntactic measures of the healthcare setting.

The study showed that a syntactically intelligible floor plan contributes significantly to reducing environmental stress among paediatric inpatients. The presence of shared spaces within the healthcare environment, where social interaction with peers is possible, emerges as a crucial factor influencing children’s spatial perception. Additionally, the visibility characteristics of shared spaces may also play a key role in enhancing children’s perceptions of safety.

The limitations of the study include the fact that the study was conducted in an oncology and haematology inpatient unit with challenging conditions in terms of the mobility potentials of the children, which might have affected their perceptual processes. A further limitation is that the sample size comprised only 30 children, and the spatial configuration of the healthcare environment was linear and not particularly complex.

By identifying the impact of spatial design on children’s well-being, the study informs the creation and improvement of healthcare environments. Enhanced understanding of factors like intelligible floor plans, shared spaces and isovist values can lead to more child-friendly facilities, potentially alleviating stress for young patients. Consequently, this research may contribute to improved healthcare outcomes, increased comfort for paediatric inpatients, and a more supportive environment for their families, fostering a holistic approach to paediatric care and positively influencing the overall quality of life for children undergoing long-term treatment.

This study contributes to the theoretical discourse on how the constrained physical conditions of a paediatric healthcare environment may influence the perceptual processes of paediatric inpatients. The results of this evidence-based study have the potential to inform the evaluation of design guidelines for healthcare settings, with the ultimate aim of enhancing therapeutic environments.

Efficiency standards, similar to industrial measures like overall equipment effectiveness (OEE), are being used in healthcare systems more and more. Performance indicator models applied to machines assume a constant completion time. However, for human resources, the completion time of a task may vary depending on the stress experienced. This study seeks to bridge this gap by integrating the human behavior of the physician into the performance evaluation.

The paper presents a new algorithm called PerfoBalance that is intended to distribute waiting-patient values among doctors. By maximizing each physician’s stress zones, this method helps to improve their performance as a whole. A thorough case study with medical professionals is carried out to confirm the effectiveness of the suggested methodology. The PerfoBalance algorithm is used in a variety of contexts to divide waiting-patient values among doctors and optimize stress zones.

Experimental results demonstrate a significant improvement in physician efficiency when implementing the PerfoBalance algorithm. The algorithm strategically selects stress zones that contribute to higher performance rates for physicians by optimizing waiting-patient values.

By addressing the undervaluation of human performance difficulties in current efficiency models used in the healthcare industry, this research constitutes a significant contribution to the field. With its launch, the PerfoBalance algorithm offers a fresh viewpoint on waiting-patient value allocation and stress zone management in healthcare settings, hence representing a powerful method for increasing physician productivity.