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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.

This chapter integrates organization design and sustainability concepts to describe an accelerated transformational change at the Fairview Medical Group (United States).

A case study of the transformation at Fairview Medical Group’s primary care clinics was developed from interviews and first-person accounts of the change. Objective data regarding outcomes was used to evaluate the effectiveness of the redesign process.

The Fairview Medical Group developed an innovation and change capability to transform 35 primary care clinics in six months. All of the clinics were certified by the state of Minnesota as complying with their healthcare standards. Clinical outcomes, costs, and employee and physician engagement also increased. All of the improved measures are sustained.

Healthcare reform in the United States struggles because the organization design challenges are great and the change difficulties even greater. Fairview’s experience provides important evidence and lessons that can help advance our understanding of effective healthcare and create more sustainable healthcare systems. This chapter provides healthcare system administrators evidence and alternatives in the pursuit of implementation.

At the beginning of the 21st century, multiple and diverse social entities, including the public (consumers), private and nonprofit healthcare institutions, government (public health) and other industry sectors, began to recognize the limitations of the current fragmented healthcare system paradigm. Primary stakeholders, including employers, insurance companies, and healthcare professional organizations, also voiced dissatisfaction with unacceptable health outcomes and rising costs. Grand challenges and wicked problems threatened the viability of the health sector. American health systems responded with innovations and advances in healthcare delivery frameworks that encouraged shifts from intra- and inter-sector arrangements to multi-sector, lasting relationships that emphasized patient centrality along with long-term commitments to sustainability and accountability. This pathway, leading to a population health approach, also generated the need for transformative business models. The coproduction of health framework, with its emphasis on cross-sector alignments, nontraditional partner relationships, sustainable missions, and accountability capable of yielding return on investments, has emerged as a unique strategy for facing disruptive threats and challenges from nonhealth sector corporations. This chapter presents a coproduction of health framework, goals and criteria, examples of boundary spanning network alliance models, and operational (integrator, convener, aggregator) strategies. A comparison of important organizational science theories, including institutional theory, network/network analysis theory, and resource dependency theory, provides suggestions for future research directions necessary to validate the utility of the coproduction of health framework as a precursor for paradigm change.

The utilization of artificial intelligence (AI) in the solution of many problems encountered in healthcare in recent years is rapidly becoming widespread. Understanding of the use and importance of efficiency, security and accessible healthcare to everyone and providing value-based services for healthcare decision-makers is essential. The special uses of machine learning, natural language processing and smart voice assistants, which have developed as sub-branches of AI, for healthcare services, the contributions of these techniques to the digital transformation of healthcare services and how all these will help decision-making processes in healthcare services, will be discussed in this chapter. And also, FDA-approved algorithms that are a kind of AI tool will be explained.

We argue that in order to address the contemporary challenges that organizations and societies are facing, the field of organization development (OD) requires frameworks and skills to focus on the eco-system as the level of analysis. In a world that has become economically, socially, and technologically highly connected, approaches that foster the optimization of specific actors in the eco-system, such as individual corporations, result in sub-optimization of the sustainability of the natural and social system because there is insufficient offset to the ego-centric purposes of the focal organization. We discuss the need for OD to broaden focus to deal with technological advances that enable new ways of organizing at the eco-system level, and to deal with the challenges to sustainable development. Case examples from healthcare and the agri-foods industry illustrate the kinds of development approaches that are required for the development of healthy eco-systems. We do not suggest fundamental changes in the identity of the field of organizational development. In fact, we demonstrate the need to dig deeply into the open systems and socio-technical roots of the field, and to translate the traditional values and approaches of OD to continue to be relevant in today’s dynamic interdependent world.

Tremendous measure of data lakes with the exponential mounting rate is produced by the present healthcare sector. The information from differing sources like electronic wellbeing record, clinical information, streaming information from sensors, biomedical image data, biomedical signal information, lab data, and so on brand it substantial as well as mind-boggling as far as changing information positions, which have stressed the abilities of prevailing regular database frameworks in terms of scalability, storage of unstructured data, concurrency, and cost. Big data solutions step in the picture by harnessing these colossal, assorted, and multipart data indexes to accomplish progressively important and learned patterns. The reconciliation of multimodal information seeking after removing the relationship among the unstructured information types is a hotly debated issue these days. Big data energizes in triumphing the bits of knowledge from these immense expanses of information. Big data is a term which is required to take care of the issues of volume, velocity, and variety generally seated in the medicinal services data. This work plans to exhibit a survey of the writing of big data arrangements in the medicinal services part, the potential changes, challenges, and accessible stages and philosophies to execute enormous information investigation in the healthcare sector. The work categories the big healthcare data (BHD) applications in five broad categories, followed by a prolific review of each sphere, and also offers some practical available real-life applications of BHD solutions.

Performance metrics have become widely used and much lamented – about tools for measuring healthcare quality. In this paper, the authors reflect on the development and use of performance metrics in healthcare regulation and clinical practice. Studying multi-actor settings of performance measurement systems in healthcare in Sweden and the Netherlands, the authors show how regulatory agencies (i.e., the inspectorate and national registries), patients, hospitals, and practitioners engage in the constitution of healthcare practices through developing performance indicators that form the input for ranking, ensuing intensive dialogues on what should be measured and accounted for, and to what effects. The authors analyze this process as caring for numbers. The authors discern two practices of caring for numbers: validating and contexting. Validating refers to the practices of making numbers reflect those practices they intend to depict; contexting is about how with the use of numbers specific contexts of healthcare are built. These processes together emphasize the performative character of numbers as well as the reflexive uses of performativity. The paper shows how collaborative and rather pragmatic practices of caring for numbers co-construct specific practices of healthcare. Though this reflexive entanglement of production and use of numbers actors not only constitute specific performance metrics and ranking practices but also perform healthcare.