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We discuss the impact of complexity science on the design and management of health care organizations over the past decade. We provide an overview of complexity science issues and their impact on thinking about health care systems, particularly with the rising importance of information systems. We also present a complexity science perspective on current issues in today’s health care organizations and suggest ways that this perspective might help in approaching these issues.

We review selected research, focusing on work in which we participated, to identify specific examples of applications of complexity science. We then take a look at information systems in health care organizations from a complexity viewpoint.

Complexity science is a fundamentally different way of understanding nature and has influenced the thinking of scholars and practitioners as they have attempted to understand health care organizations. Many scholars study health care organizations as complex adaptive systems and through this perspective develop new management strategies. Most important, perhaps, is the understanding that attention to relationships and interdependencies is critical for developing effective management strategies.

Increased understanding of complexity science can enhance the ability of researchers and practitioners to develop new ways of understanding and improving health care organizations.

This analysis opens new vistas for scholars and practitioners attempting to understand health care organizations as complex adaptive systems. The analysis holds value for those already familiar with this approach as well as those who may not be as familiar.

This chapter uses the theory of complex systems as a conceptual lens through which to compare the work of Friedrich Hayek with that of Vincent and Elinor Ostrom. It is well known that, from the 1950s onwards, Hayek conceptualised the market as a complex adaptive system. It is argued in this chapter that, while the Ostroms began explicitly to describe polycentric systems as a class of complex adaptive system from the mid-to-late 1990s onwards, they had in fact developed an account of polycentricity as displaying most if not all of the hallmarks of organised complexity long before that time. The Ostromian and Hayekian approaches can thus be seen to share a good deal in common, with both portraying important aspects of society – the market economy in the case of Hayek, and public economies, legal and political systems, and environment resources in the case of the Ostroms – as complex rather than simple systems. Aside from helping to bring out this aspect of the Ostroms’ work, using the theory of complex systems as a framework for comparing the Hayekian and Ostromian approaches serves two other purposes. First, it can be used to show how one widely criticised aspect of Hayek’s theory of society as a complex system, namely his account of cultural evolution via group selection, can be strengthened by an appeal to the work of Elinor Ostrom. Second, it also helps to resolve a tension – ultimately acknowledged by the Ostroms themselves – between some of their explicit methodological pronouncements and the actual, substantive approach they adopted in their analysis of polycentric systems.

This chapter introduces readers to a complex adaptive systems approach for integrating research on genes, behavior, and social structures/institutions. Until recently, scientists have resorted to reductionism as a decoding and epistemological strategy for understanding human health. The complex bonds among health’s biological, behavioral, and social dimensions, however, cannot be fully grasped with reductionist schemas. Moreover, because reducing and simplifying can lead to incomplete understanding of phenomena, the resulting deficient knowledge has the potential to be harmful.

To achieve its purpose, this primer will: (1) introduce fundamental notions from complexity science, useful for inquiry and practice integrating research on genes, behavior, and social structures; (2) outline selected methodological strategies employed in studying complex adaptive/dynamic systems; (3) address the question, “Specifically, how can a dynamic systems approach be helpful for integrating research on genes, behavior, and social structures/institutions, to improve the public’s health?”; and (4) provide examples of studies currently deploying a complexity perspective.

The originality/value of this primer rests in its critique of the research status quo and the proposition of an alternative lens for integrating genomic, biomedical, and sociological research to improve the public’s health. The topic of complex adaptive/dynamic systems has begun to flourish within sociology, medicine, and public health, but many researchers lack exposure to the topic’s basic notions and applications.

This chapter addresses two identified weaknesses in entrepreneurial ecosystem studies: there is a lack of focus on the relationships between the components of entrepreneurial ecosystems and little understanding of the underlying processes that determine how entrepreneurial ecosystems change over time. Both entrepreneurial ecosystems and solutions ecosystems from social entrepreneurship studies are place-based complex adaptive systems that are emergent in nature. While neither of these ecosystem types can be controlled, they can be influenced and guided to follow a direction by designing conditions for emergence and transitions. In this chapter, the proposition that an online tool, that is used to strengthen solution ecosystems and support their emergence and transition, could also be used to strengthen entrepreneurial ecosystems and guide their emergence and transition is examined. Two cases are used to investigate this proposition: a food security solution ecosystem case study that demonstrates how the online tool is used for solution ecosystems, and an impact economy entrepreneurial ecosystem case study that highlights how the online tool could be used for an entrepreneurial ecosystem. It is demonstrated in this chapter that the online tool can be used to address the current weaknesses of entrepreneurial ecosystem studies. In addition, it is suggested that by combining solution ecosystems with an impact economy entrepreneurial ecosystem, the online tool can be used to support the creation of conditions for social entrepreneurial places to emerge that are capable of addressing the most pressing problems that places face including the sustainable development goals.

Certain elements of Hayek’s work are prominent precursors to the modern field of complex adaptive systems, including his ideas on spontaneous order, his focus on market processes, his contrast between designing and gardening, and his own framing of complex systems. Conceptually, he was well ahead of his time, prescient in his formulation of novel ways to think about economies and societies. Technically, the fact that he did not mathematically formalize most of the notions he developed makes his insights hard to incorporate unambiguously into models. However, because so much of his work is divorced from the simplistic models proffered by early mathematical economics, it stands as fertile ground for complex systems researchers today. I suggest that Austrian economists can create a progressive research program by building models of these Hayekian ideas, and thereby gain traction within the economics profession. Instead of mathematical models the suite of techniques and tools known as agent-based computing seems particularly well-suited to addressing traditional Austrian topics like money, business cycles, coordination, market processes, and so on, while staying faithful to the methodological individualism and bottom-up perspective that underpin the entire school of thought.

As the demand for new services strains library resources, directors of research libraries must practice efficient cost management and demonstrate alignment with institutional objectives. For technical services, this requires managing the effective cost of metadata services, assessing core functions, and evaluating operational performance. This paper uses Complex Adaptive Systems (CASs) as a framework to expose the network of local and global dependencies that currently define the field of operation for technical services. Comparative analyses using a CASs framework were conducted on reports by the Library of Congress, the Heads of Technical Services in Large Research Libraries Interest Group, and the British Library. Each report addresses financial pressures placed on bibliographic control services in response to the 2008 recession. Statements within the reports were assigned to one of three dominant systems: bibliographic control, institutional identification, and distributive networks. The statements were then mapped to the CASs characteristics to determine environmental pressures and areas of adaptation. The reports exposed long-standing dependencies that tie local bibliographic control to a complex network of external agencies. Institutional shifts toward user-centered services coupled with growing fiscal restraint has disrupted the stability of these networks. The analyses found that in all cases network instability led to localized institutional adaptation to existing economic pressures. The paper recommends applying a CASs model to assess the alignment of distributed metadata standards and systems development to local institutional objectives.

In this chapter, the author delves deeper into adaptive and sustainability challenges, specifically discussing the roles of management and leadership in addressing these problems. Both responsible leadership and management are essential for tackling sustainability challenges. Leadership focuses on establishing a vision and inspiring others to attain it, while management is concerned with devising and executing strategies to realize that vision. Addressing wicked problems necessitates collaboration, engagement and innovative solutions, involving both leadership and management. To effectively conquer sustainability challenges, organizations must embrace a more holistic and sustainable approach to management and leadership. This might include collaborating with stakeholders to discover innovative solutions that prioritize sustainability and social responsibility. Resolving wicked problems calls for a distinct management and leadership approach that is cooperative, systemic, and sustainable.

As the cognitive sciences – particularly neuroscience, cognitive psychology, and a rejuvenated artificial intelligence movement that has largely abandoned the model of the mind as a formal machine – have seen major development over the past quarter-century, it is inevitable that the findings thrown up by this ‘cognitive revolution’ should be examined for their relevance to the understanding of economic behavior. This ongoing examination has tended to emphasize those characteristics of human cognitive capabilities that call into question the descriptive adequacy of the rational-choice model, focusing on departures from individual rationality that may have economic consequences at the market level.¹ Such a move may be the obvious one for an economist confronted with this interdisciplinary challenge, but it is not the only one. The new insights into the functioning of the brain can also be deployed in the understanding of complex systems in general – and of specific social arrangements in particular – and that is the direction taken here. By critically examining the systemic similarities and differences between the social arrangements of science and market, the aim is to show how a complex systems approach, inspired by developments in cognitive psychology but applying these at the level of the system rather than of the individual, can provide a new and useful way of understanding social systems.

Although it is widely acknowledged that health care delivery systems are complex adaptive systems, there are gaps in understanding the application of systems engineering approaches to systems analysis and redesign in the health care domain. Commonly employed methods, such as statistical analysis of risk factors and outcomes, are simply not adequate to robustly characterize all system requirements and facilitate reliable design of complex care delivery systems. This is especially apparent in institutional-level systems, such as patient safety programs that must mitigate the risk of infections and other complications that can occur in virtually any setting providing direct and indirect patient care. The case example presented here illustrates the application of various system engineering methods to identify requirements and intervention candidates for a critical patient safety problem known as failure to rescue. Detailed descriptions of the analysis methods and their application are presented along with specific analysis artifacts related to the failure to rescue case study. Given the prevalence of complex systems in health care, this practical and effective approach provides an important example of how systems engineering methods can effectively address the shortcomings in current health care analysis and design, where complex systems are increasingly prevalent.

Organizations today operate in highly dynamic environments and are becoming more complex. Helping their organizations master this complexity is a major leadership challenge. To better understand how managers’ behaviors aggravate or reduce complexity, we reviewed 1,400 responses to a proprietary organizational complexity survey. Analysis identified specific managers’ behaviors that contribute to perceived complexity. We draw from these findings, literature on complex adaptive systems, and our consulting experiences to identify specific strategies managers can use to make it simpler for people to get things done, and even to “master” complexity by turning it into a source of strategic advantage.