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The purpose of this paper is to analyze the main global transformations of the healthcare sector and their underlying causes and effects.

The study focuses on several important trends including the increasing life expectancy and aging, the rise of non-communicable diseases, the risks of pandemics, medication expenditure, the globalization of healthcare and technological innovations such as digitization, robotic and nanomedicine.

The analysis indicates that the world populations will be much older in the near future and the healthcare sector will witness significant growth opportunities. The aging populations will put more pressure on healthcare systems and increase the incidence of non-communicable diseases. In a globalized world, the risks of global pandemics are expected to increase. The surge in the medication expenditure will put much pressure on healthcare systems, insurers, patients, employers and providers. The healthcare sector is characterized by its above-average growth in the USA and much of the developed world. Therefore, the share of healthcare in gross domestic product will continue to rise. The digitization and globalization of healthcare may involve major disruptions in the location and the type of care. New materials particularly nanoparticles will be used to enhance the precision, quality and efficacy of diagnostics, medications and treatments.

The paper touches on several areas including demographic, clinical, financial, managerial and technological transformations and examines their implications for the healthcare sector.

This paper proposes the adoption of Industry 4.0 (I4) technologies and lean techniques for improving operational performance in the healthcare sector.

The research adopted a systematic literature review and feedback of healthcare professionals to identify the inefficiencies in the current healthcare system. A questionnaire was used to get feedback from the patients and the hospital staff about the current practices and issues, and the expected impact of technology on existing practices. Data were analysed using descriptive statistics, correlation analysis and multiple regression analysis.

The results indicate that I4 technologies lead to the improvement of the operational performance, and the perceptions about I4 technologies are made through the pre-medical diagnosis. However, a weak correlation between lean practices and healthcare operational performance compared to that of I4 technologies and operational performance indicate that lean practices are not fully implemented in the Sri Lankan healthcare sector to their full potential.

This study is limited to two government hospitals, with insights from only the doctors and nurses in Sri Lanka. Furthermore, the study is limited to only selected aspects of I4 technologies (big data, cloud computing and IoT) and lean concepts (value stream mapping and 5S). Therefore, recommendations on the adoption of I4 technologies in the healthcare sector need to be made within the scope of the study investigation.

The implementation of I4 technologies needs careful consideration of process improvement as part of the overall plan for achieving the maximum benefits of technology adoption.

The findings of the research can be used as a benchmark/guide for other hospitals to explore the adoption of I4 technologies, and how process improvement from lean concepts could influence the overall operational performance.

This study aims to evaluate the dynamics between healthcare resource capacity expansion and disease spread. Further, the study estimates the resources required to respond to a pandemic appropriately.

This study adopts a system dynamics simulation and scenario analysis to experiment with the modification of the susceptible exposed infected and recovered (SEIR) model. The experiments evaluate diagnostic capacity expansion to identify suitable expansion plans and timelines. Afterwards, two popularly used forecasting tools, artificial neural network (ANN) and auto-regressive integrated moving average (ARIMA), are used to estimate the requirement of beds for a period when infection data became available.

The results from the study reflect that aggressive testing with isolation and integration of quarantine can be effective strategies to prevent disease outbreaks. The findings demonstrate that decision-makers must rapidly expand the diagnostic capacity during the first two weeks of the outbreak to support aggressive testing and isolation. Further, results confirm a healthcare resource deficit of at least two months for Delhi in the absence of these strategies. Also, the study findings highlight the importance of capacity expansion timelines by simulating a range of contact rates and disease infectivity in the early phase of the outbreak when various parameters are unknown. Further, it has been reflected that forecasting tools can effectively estimate healthcare resource requirements when pandemic data is available.

The models developed in the present study can be utilised by policymakers to suitably design the response plan. The decisions regarding how much diagnostics capacity is needed and when to expand capacity to minimise infection spread have been demonstrated for Delhi city. Also, the study proposed a decision support system (DSS) to assist the decision-maker in short- and long-term planning during the disease outbreak.

The study estimated the resources required for adopting an aggressive testing strategy. Several experiments were performed to successfully validate the robustness of the simulation model. The modification of SEIR model with diagnostic capacity increment, quarantine and testing block has been attempted to provide a distinct perspective on the testing strategy. The prevention of outbreaks has been addressed systematically.

A direct correlation exists between waste disposal, disease spread and public health. This article systematically reviewed healthcare waste and its implication for public health. This review identified and described the associations and impact of waste disposal on public health.

This paper systematically reviewed the literature on waste disposal and its implications for public health by searching Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA), PubMed, Web of Science, Scopus and ScienceDirect databases. Of a total of 1,583 studies, 59 articles were selected and reviewed.

The review revealed the spread of infectious diseases and environmental degradation as the most typical implications of improper waste disposal to public health. The impact of waste includes infectious diseases such as cholera, Hepatitis B, respiratory problems, food and metal poisoning, skin infections, and bacteremia, and environmental degradation such as land, water, and air pollution, flooding, drainage obstruction, climate change, and harm to marine and wildlife.

Infectious diseases such as cholera, hepatitis B, respiratory problems, food and metal poisoning, skin infections, bacteremia and environmental degradation such as land, water, and air pollution, flooding, drainage obstruction, climate change, and harm to marine and wildlife are some of the public impacts of improper waste disposal.

Healthcare industry waste is a significant waste that can harm the environment and public health if not properly collected, stored, treated, managed and disposed of. There is a need for knowledge and skills applicable to proper healthcare waste disposal and management. Policies must be developed to implement appropriate waste management to prevent public health threats.

According to Global Healthcare Security Index 2021, India ranked 66 out of 195 countries, indicating the need and scope for improvement. The Cooperative healthcare system which has been rendering exemplary services is yet to gain visible recognition in India. Given the need for upgrading the health infrastructure in India and providing more affordable health services to the country’s growing population, it would help appreciate the large role that cooperative healthcare can play along with others. This study explores the structure, conduct, and performance of healthcare co-operatives in India, the factors contributing to their success and failure, and the challenges they face. The Health Cooperatives have a strong presence in Kerala and Karnataka and are also coming up in other parts of the country. However, a detailed database of them for public awareness is very limited. The cooperative hospitals can meet the basic requirements of curative treatment in rural and poorly-endowed urban areas. The democratic way in which they function makes them a destination for a financially weaker section. They must retain this feature. The study covers two successful cases which reveal that India needs a more dense healthcare cooperative network. Since cooperative hospitals in tune with the spirit of service run on the principle of being ‘Not-for-Profit’ they need to be supported by the governments more liberally, without however interfering with their governance and administration.

Introduction: Coronavirus-19 (COVID-19) global outbreak poses a danger to millions of people’s health and the uncertainty and financial prudence around the world. Without a doubt, the sickness will place a tremendous strain on healthcare systems, which existing or traditional-based treatments cannot adequately handle. Only intelligence derived from diverse data sources can provide the foundation for rigorous clinical and social responses that optimise the use of constrained healthcare resources, create tailored patient treatment plans, educate policy-makers, and accelerate clinical trials

Purpose: This chapter aims to incorporate innovative practices of artificial intelligence (AI) into local, national, and global healthcare systems that can save lives of people and as well helps in human capital management ways that may be deployed rapidly and effectively with minimal errors.

Methodology: AI technologies and tools play a crucial part in COVID-19 crisis response by assisting with the virus discovery, early detection, and the development of effective medications and therapies. In this chapter, significant issues related to COVID-19 and how they may be addressed by applying HRM practices with recent advances in AI. Also, through a literature review of the recent studies implemented in a similar context, an AI solution is proposed by formulating a conceptual model.

Findings: This chapter offers that the latest AI techniques can assist policy-makers in implementing modern human capital management practices to fight against COVID-19. The goal is to remotely monitor patients utilising gadgets that are embedded with state-of-the-art medical technology. To limit hospital visits, or at least cut them down to a minimum, on the one hand, the health clinic also wants to deliver reliable health information to the doctors before or during virtual consultations.

The devastating 2014 Ebola outbreak caused human and economic loss, but it also resulted in remarkable improvement in healthcare leadership. The impact is most evident in the affected West African countries of Guinea, Liberia and Sierra Leone. In this chapter, the Ebola experience is used as a framework to explore the essential elements of healthcare leadership, with particular attention to healthcare crises in under-resourced communities. Overall, healthcare leadership presents unique challenges. In common with leaders of other industries, healthcare leaders must inspire others, create a sense of purpose, make difficult decisions and collaborate with a range of people. But, because their focus is on complex systems that aim to improve people's physical and mental well-being, expectations of healthcare leaders are especially high. Their work can be a matter of life or death. For the leader in an under-resourced area, the challenge and expectations are even higher, particularly in the face of new or emerging health threats. The key to effective healthcare leadership is systems thinking which involves looking at the entire system of care as an integrated whole, rather than discrete parts that operate in isolation. Healthcare leaders must understand that health means mobilizing multisectoral knowledge and resources and applying innovative and multiactor approaches to prevent, detect and address health problems. Since the 2014 Ebola crisis, healthcare leaders are increasingly using a systems approach by looking at the culture of health systems, the impact of diseases locally and globally, and the applicability of health interventions in different environments. In the post-Ebola era, steps to strengthen the healthcare system are described which includes the roles of healthcare leaders. These steps include deployment of field epidemiologists and community health agents, community education and fuller use of the One Health Platform, which allows actors from different sectors (human health, animal health and environmental health) to collaborate. Finally, suggestions for healthcare leadership training are offered.