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The aim of the chapter is to compare Public–Private Partnership (PPP) healthcare investments in developed countries with those in emerging economies, analysing the sustainability issues of health-led growth. Healthcare PPP best practices in developed nations represent a template that catching-up economies may follow with local adaptations. A comparison starts from the UK case and then examines the Turkish experience as an ideal bridge between advanced and developing countries. Healthcare investments are a primary social infrastructure, with a deep impact on poverty alleviation. Demand for the infrastructure necessary to provide healthcare services has increased substantially in developing and emerging economies due to rapid economic growth, industrialization and urbanization, while public supply is limited by budget constraints. PPP best practices provide a global benchmark (World bank, 2015b). Integrated supply and value chains and management of viability milestone improve healthcare PPP sustainability and bankability. Different legal frameworks and funding issues are not thoroughly investigated. Careful customization and local fine-tuning of best practices require further scrutiny. Homogenization of best practices improves comparison of different projects, fostering competition and easing cross-border investments, accompanied by knowledge transfer, sharing and consequent value co-creation. Best practices improve value for money, bankability and resilience of PPP investments, with potential benefits for healthcare services and quality of life. This chapter makes an innovative and comprehensive comparison of healthcare PPP projects worldwide, looking for a common denominator of value-enhancing rules and resilient pro-growth strategies.

This chapter summarises the role of EU actions in supporting healthcare policies in the EU Member States, both looking at implemented actions and describing current priorities for the future. It argues that these coordinated actions can be beneficial for EU Member States by helping them to avoid duplication of effort and to attain economies of scale. Moreover, data sharing with proper safeguards can unleash vast amount of ‘learning what works’ both for medical treatments and for healthcare sustainability measures. The need for this common learning appears ever more urgent while facing the health and economic consequences of the present pandemic.

Healthcare is indispensable for any civilisation to attain a good quality of life and well-being on both mental and physical levels. The healthcare domain primarily falls under pharma, medical, biotechnology, and nursing. Also, other fields may be aligned with these primary fields. Healthcare amasses the contemporary trends and knowledge of upcoming techniques to improve healthcare processes. The practitioners are primarily doctors, nurses, specialists and health professionals, hospital administrators, and health insurance.

It is a fundamental attribute needed for any society to attain good quality of life and well-being in mental and physical health. It is a fundamental right of people to receive good healthcare where drug treatment and hospitalization are available at a nominal cost, as a requirement of today’s modern era. There appears to be a significant disparity in the availability of good healthcare in rural areas compared to urban in India. Even though we enter the digital era with the facilities offered in Industry 4.0 and other advanced technologies brings about a significant change of overall processing within healthcare systems. During the pandemic of COVID-19, there has been digital transformation with success globally. Healthcare cooperatives are a new norm to support the healthcare systems globally. The chapter discusses Gampaha healthcare cooperative and reviews Ayushman Sahakar scheme in India. The reforms require time to evolve.

The twentieth century started writing the history of modern health systems. Their evolvable rate is now higher than ever. The Western Europe was the forefront of setting up the national health systems (NHS) to protect citizens and let them thrive. Successful models progressively crossed the borders and experiences became universal. Hence, this chapter tackles data to perceive the underwent radical transformations and capture intricate aspects to envision the next and get answers time ahead the patients‘needs. Health organizational structures and human resources management play crucially in improving system’s performances: managerial qualities, medical entities’ functionality, results’ forecasting are essential to build up credibility and aid strategic patterns to evolve.

Changes are welcome to better tailor performances, assure successful implementation, avoid inadequate, distressing reforms. Stable and consistent policies are also called for.

Grounded on fundamental patterns, open to applicatory innovation, countries follow specific arrangements to resound with healthcare robustness if goals are well-thought-of: keeping people healthy and safe, identifying and treating defectiveness or abnormal physiological functions affecting people, operations, circuits, and preserving health budget wisely balanced.

Activities and citizens are touched by any structural changes maneuvered. To confront them, a keen eye should be addressed to those nobody’s areas into synergistic efforts to cope with internal causes, face external forces and improve life through fair profitability on the way of full satisfaction.

This chapter discussed the role of business intelligence (BI) in healthcare twofold strategic decision making of the organization and the stakeholders. The visualization techniques of data mining are applied for the early and correct diagnosis of the disease, patient’s satisfaction quotient and also helpful for the hospital to know their best commanders.

In this chapter, the usefulness of BI is shown at two levels: at doctor level and at hospital level. As a case study, a hospital is taken which deals with three different kinds of diseases: Breast Cancer, Diabetes, and Liver disorder. BI can be applied for taking better strategic decisions in the context of hospital and its department’s growth. At the doctor level, on the basis of various symptoms of the disease, the doctor can advise the suitable treatment to the patients. At the hospital level, the best department among all can be identified. Also, a patient’s type of admission, continued their treatments with the hospital, patient’s satisfaction quotient, etc., can be calculated. The authors have used different methods like Correlation matrix, decision tree, mosaic plots, etc., to conduct this analysis.

Purpose: This chapter aims to analyse and highlight the current landscape of performance management (PM) systems, and the benefits of integrating modern technology such as smart analytics (SA) and artificial intelligence (AI) into PM systems. The chapter discusses the application of AI in PM tasks which successively simplify many offline PM tasks.

Methodology: To carry out this analysis, a systematic literature review was performed. The review covers literature detailing PM components as well as research concerned with the integration of SA and AI into PM systems.

Findings: This study uncovers the merits of using SA and AI in PM. SA technology provides organisations with a clear direction for improvement, rather than simply state failure in performance. AI can be used to automate redundant tasks while retaining the human element of decision-making. AI also helps reduce the time required to take action on feedback.

Significance: The findings of this research provide insights into the use of SA and AI to make PM tasks fast, scalable, and error-free.

Objective – This chapter assesses health equity achievements of the Thai health system before and after the introduction of the universal coverage (UC) policy. It examines five dimensions of equity: equity in financial contributions, the incidence of catastrophic health expenditure, the degree of impoverishment as a result of household out-of-pocket payments for health, equity in health service use and the incidence of public subsidies for health.

Methodology – The standard methods proposed by O’Donnell, van Doorslaer, and Wagstaff (2008b) were used to measure equity in financial contribution, healthcare utilization and public subsidies, and in assessing the incidence of catastrophic health expenditure and impoverishment. Two major national representative household survey datasets were used: Socio-Economic Surveys and Health and Welfare Surveys.

Findings – General tax was the most progressive source of finance in Thailand. Because this source dominates total financing, the overall outcome was progressive, with the rich contributing a greater share of their income than the poor. The low incidence of catastrophic health expenditure and impoverishment before UC was further reduced after UC. Use of healthcare and the distribution of government subsidies were both pro-poor: in particular, the functioning of primary healthcare (PHC) at the district level serves as a “pro-poor hub” in translating policy into practice and equity outcomes.

Policy implications – The Thai health financing reforms have been accompanied by nationwide extension of PHC coverage, mandatory rural health service by new graduates and systems redesign, especially the introduction of a contracting model and closed-ended provider payment methods. Together, these changes have led to a more equitable and more efficient health system. Institutional capacity to generate evidence and to translate it into policy decisions, effective implementation and comprehensive monitoring and evaluation are essential to successful system-level reforms.