Showing papers on "Complex adaptive system published in 2018"

When complexity science meets implementation science: a theoretical and empirical analysis of systems change

Abstract: Implementation science has a core aim – to get evidence into practice. Early in the evidence-based medicine movement, this task was construed in linear terms, wherein the knowledge pipeline moved from evidence created in the laboratory through to clinical trials and, finally, via new tests, drugs, equipment, or procedures, into clinical practice. We now know that this straight-line thinking was naive at best, and little more than an idealization, with multiple fractures appearing in the pipeline. The knowledge pipeline derives from a mechanistic and linear approach to science, which, while delivering huge advances in medicine over the last two centuries, is limited in its application to complex social systems such as healthcare. Instead, complexity science, a theoretical approach to understanding interconnections among agents and how they give rise to emergent, dynamic, systems-level behaviors, represents an increasingly useful conceptual framework for change. Herein, we discuss what implementation science can learn from complexity science, and tease out some of the properties of healthcare systems that enable or constrain the goals we have for better, more effective, more evidence-based care. Two Australian examples, one largely top-down, predicated on applying new standards across the country, and the other largely bottom-up, adopting medical emergency teams in over 200 hospitals, provide empirical support for a complexity-informed approach to implementation. The key lessons are that change can be stimulated in many ways, but a triggering mechanism is needed, such as legislation or widespread stakeholder agreement; that feedback loops are crucial to continue change momentum; that extended sweeps of time are involved, typically much longer than believed at the outset; and that taking a systems-informed, complexity approach, having regard for existing networks and socio-technical characteristics, is beneficial. Construing healthcare as a complex adaptive system implies that getting evidence into routine practice through a step-by-step model is not feasible. Complexity science forces us to consider the dynamic properties of systems and the varying characteristics that are deeply enmeshed in social practices, whilst indicating that multiple forces, variables, and influences must be factored into any change process, and that unpredictability and uncertainty are normal properties of multi-part, intricate systems.

Social-ecological systems as complex adaptive systems: organizing principles for advancing research methods and approaches

Abstract: CITATION: Preise, R., et al. 2018. Social-ecological systems as complex adaptive systems : organizing principles for advancing research methods and approaches. Ecology and Society, 23(4):46, doi:10.5751/ES-10558-230446.

Public health emergency preparedness: a framework to promote resilience

Abstract: Emergencies and disasters impact population health. Despite the importance of upstream readiness, a persistent challenge for public health practitioners is defining what it means to be prepared. There is a knowledge gap in that existing frameworks lack consideration for complexity relevant to health systems and the emergency context. The objective of this study is to describe the essential elements of a resilient public health system and how the elements interact as a complex adaptive system. This study used a qualitative design employing the Structured Interview Matrix facilitation technique in six focus groups across Canada. Focus group participants were practitioners from public health and related sectors. Data collection generated qualitative data on the essential elements, and interactions between elements, for a resilient public health system. Data analysis employed qualitative content analysis and the lens of complexity theory to account for the complex nature of public health emergency preparedness (PHEP). The unit of study was the local/regional public health agency. Ethics and values were considered in the development of the framework. A total of 130 participants attended the six focus groups. Urban, urban-rural and rural regions from across Canada participated and focus group size ranged from 15 to 33 across the six sites. Eleven elements emerged from the data; these included one cross-cutting element (Governance and leadership) and 10 distinct but interlinked elements. The essential elements define a conceptual framework for PHEP. The framework was refined to ensure practice and policy relevance for local/regional public health agencies; the framework has ethics and values at its core. This framework describes the complexity of the system yet moves beyond description to use tenets of complexity to support building resilience. This applied public health framework for local/regional public health agencies is empirically-derived and theoretically-informed and represents a complex adaptive systems approach to upstream readiness for PHEP.

Simple rules for evidence translation in complex systems: A qualitative study

Abstract: Ensuring patients benefit from the latest medical and technical advances remains a major challenge, with rational-linear and reductionist approaches to translating evidence into practice proving inefficient and ineffective. Complexity thinking, which emphasises interconnectedness and unpredictability, offers insights to inform evidence translation theories and strategies. Drawing on detailed insights into complex micro-systems, this research aimed to advance empirical and theoretical understanding of the reality of making and sustaining improvements in complex healthcare systems. Using analytical auto-ethnography, including documentary analysis and literature review, we assimilated learning from 5 years of observation of 22 evidence translation projects (UK). We used a grounded theory approach to develop substantive theory and a conceptual framework. Results were interpreted using complexity theory and ‘simple rules’ were identified reflecting the practical strategies that enhanced project progress. The framework for Successful Healthcare Improvement From Translating Evidence in complex systems (SHIFT-Evidence) positions the challenge of evidence translation within the dynamic context of the health system. SHIFT-Evidence is summarised by three strategic principles, namely (1) ‘act scientifically and pragmatically’ – knowledge of existing evidence needs to be combined with knowledge of the unique initial conditions of a system, and interventions need to adapt as the complex system responds and learning emerges about unpredictable effects; (2) ‘embrace complexity’ – evidence-based interventions only work if related practices and processes of care within the complex system are functional, and evidence-translation efforts need to identify and address any problems with usual care, recognising that this typically includes a range of interdependent parts of the system; and (3) ‘engage and empower’ – evidence translation and system navigation requires commitment and insights from staff and patients with experience of the local system, and changes need to align with their motivations and concerns. Twelve associated ‘simple rules’ are presented to provide actionable guidance to support evidence translation and improvement in complex systems. By recognising how agency, interconnectedness and unpredictability influences evidence translation in complex systems, SHIFT-Evidence provides a tool to guide practice and research. The ‘simple rules’ have potential to provide a common platform for academics, practitioners, patients and policymakers to collaborate when intervening to achieve improvements in healthcare.

Embracing uncertainty, managing complexity: Applying complexity thinking principles to transformation efforts in healthcare systems

Abstract: Complexity thinking is increasingly being embraced in healthcare, which is often described as a complex adaptive system (CAS). Applying CAS to healthcare as an explanatory model for understanding the nature of the system, and to stimulate changes and transformations within the system, is valuable. A seminar series on systems and complexity thinking hosted at the University of Toronto in 2016 offered a number of insights on applications of CAS perspectives to healthcare that we explore here. We synthesized topics from this series into a set of six insights on how complexity thinking fosters a deeper understanding of accepted ideas in healthcare, applications of CAS to actors within the system, and paradoxes in applications of complexity thinking that may require further debate: 1) a complexity lens helps us better understand the nebulous term “context”; 2) concepts of CAS may be applied differently when actors are cognizant of the system in which they operate; 3) actor responses to uncertainty within a CAS is a mechanism for emergent and intentional adaptation; 4) acknowledging complexity supports patient-centred intersectional approaches to patient care; 5) complexity perspectives can support ways that leaders manage change (and transformation) in healthcare; and 6) complexity demands different ways of implementing ideas and assessing the system. To enhance our exploration of key insights, we augmented the knowledge gleaned from the series with key articles on complexity in the literature. Ultimately, complexity thinking acknowledges the “messiness” that we seek to control in healthcare and encourages us to embrace it. This means seeing challenges as opportunities for adaptation, stimulating innovative solutions to ensure positive adaptation, leveraging the social system to enable ideas to emerge and spread across the system, and even more important, acknowledging that these adaptive actions are part of system behaviour just as much as periods of stability are. By embracing uncertainty and adapting innovatively, complexity thinking enables system actors to engage meaningfully and comfortably in healthcare system transformation.

Teams as Complex Adaptive Systems: Reviewing 17 Years of Research

Abstract: At the turn of the century, Arrow, McGrath, and Berdahl portrayed teams as complex adaptive systems (CAS). And yet, despite broad agreement that this approach facilitates a better understanding of ...

Complex adaptive systems: a new approach for understanding health practices

Abstract: This article explores the potential of complex adaptive systems (CAS) theory to inform behaviour change research. A CAS describes a collection of heterogeneous agents interacting within a particular context, adapting to each other's actions. In practical terms, this implies that behaviour change is (1) socially and culturally situated; (2) highly sensitive to small baseline differences in individuals, groups, and intervention components; and (3) determined by multiple components interacting 'chaotically'. Two approaches to studying CAS are briefly reviewed. Agent-based modelling is a computer simulation technique that allows researchers to investigate 'what if' questions in a virtual environment. Applied qualitative research techniques, on the other hand, offer a way to examine what happens when an intervention is pursued in real-time, and to identify the sorts of rules and assumptions governing social action. Although these represent very different approaches to complexity, there may be scope for mixing these methods - for example, by grounding models in insights derived from qualitative fieldwork. Finally, I will argue that the concept of CAS offers one opportunity to gain a deepened understanding of health-related practices, and to examine the social psychological processes that produce health-promoting or damaging actions.

Thinking about complexity in health: A systematic review of the key systems thinking and complexity ideas in health.

Abstract: Rationale, aims, and objectives As the Sustainable Development Goals are rolled out worldwide, development leaders will be looking to the experiences of the past to improve implementation in the future. Systems thinking and complexity science (ST/CS) propose that health and the health system are composed of dynamic actors constantly evolving in response to each other and their context. While offering practical guidance for steering the next development agenda, there is no consensus as to how these important ideas are discussed in relation to health. This systematic review sought to identify and describe some of the key terms, concepts, and methods in recent ST/CS literature. Method Using the search terms “systems thinkin * AND health OR complexity theor* AND health OR complex adaptive system* AND health,” we identified 516 relevant full texts out of 3982 titles across the search period (2002-2015). Results The peak number of articles were published in 2014 (83) with journals specifically focused on medicine/healthcare (265) and particularly the Journal of Evaluation in Clinical Practice (37) representing the largest number by volume. Dynamic/dynamical systems (n = 332), emergence (n = 294), complex adaptive system(s) (n = 270), and interdependent/interconnected (n = 263) were the most common terms with systems dynamic modelling (58) and agent-based modelling (43) as the most common methods. Conclusions The review offered several important conclusions. First, while there was no core ST/CS “canon,” certain terms appeared frequently across the reviewed texts. Second, even as these ideas are gaining traction in academic and practitioner communities, most are concentrated in a few journals. Finally, articles on ST/CS remain largely theoretical illustrating the need for further study and practical application. Given the challenge posed by the next phase of development, gaining a better understanding of ST/CS ideas and their use may lead to improvements in the implementation and practice of the Sustainable Development Goals.

The theory of graceful extensibility: basic rules that govern adaptive systems

Abstract: The paper introduces the theory of graceful extensibility which expresses fundamental characteristics of the adaptive universe that constrain the search for sustained adaptability The theory explains the contrast between successful and unsuccessful cases of sustained adaptability for systems that serve human purposes Sustained adaptability refers to the ability to continue to adapt to changing environments, stakeholders, demands, contexts, and constraints (in effect, to adapt how the system in question adapts) The key new concept at the heart of the theory is graceful extensibility Graceful extensibility is the opposite of brittleness, where brittleness is a sudden collapse or failure when events push the system up to and beyond its boundaries for handling changing disturbances and variations As the opposite of brittleness, graceful extensibility is the ability of a system to extend its capacity to adapt when surprise events challenge its boundaries The theory is presented in the form of a set of 10 proto-theorems derived from just two assumptions—in the adaptive universe, resources are always finite and change continues The theory contains three subsets of fundamentals: managing the risk of saturation, networks of adaptive units, and outmaneuvering constraints The theory attempts to provide a formal base and common language that characterizes how complex systems sustain and fail to sustain adaptability as demands change

The System Thinking Perspective in the Open-Innovation Research: A Systematic Review

Abstract: The new logics of competitions are mostly based on exploiting relationships to implement new mechanisms in managing Knowledge. Today, a successful company should be, lean, modular, and with a smart approach to new products development. In this context, the source of competitive advantage cannot be found into a static heterogeneity of resources, but companies must be able to create and manage a dynamic competitive process to continuously reinvent their products/services and to re-combine their resources with their partners’ ones. A paradigm for this behavior is the Open Innovation one, as created by Chesbrough. According to the rules of this paradigm, companies have to acknowledge that they operate in a network of relationships, they must be open to cooperate with their external partners, and they must not try to limit their actions in reaching only for some pre-defined result. So, Open Innovation Networks appear to be similar to those described by the scholars in the Complex Adaptive Systems field where the actions of the system, and of its parts, are the result of the various actors’ interactions in an emergent way. In this paper, we use a Systematic Literature Review approach to explore how the main topics in the System Thinking Perspective, and in particular, those related to Complex Systems, are linked to the Open Innovation studies.

Infrastructure as a Complex Adaptive System

Abstract: National infrastructure systems spanning energy, transport, digital, waste, and water are well recognised as complex and interdependent. While some policy makers have been keen to adopt the narrative of complexity, the application of complexity-based methods in public policy decision-making has been restricted by the lack of innovation in associated methodologies and tools. In this paper we firstly evaluate the application of complex adaptive systems theory to infrastructure systems, comparing and contrasting this approach with traditional systems theory. We secondly identify five key theoretical properties of complex adaptive systems including adaptive agents, diverse agents, dynamics, irreversibility, and emergence, which are exhibited across three hierarchical levels ranging from agents, to networks, to systems. With these properties in mind, we then present a case study on the development of a system-of-systems modelling approach based on complex adaptive systems theory capable of modelling an emergent national infrastructure system, driven by agent-level decisions with explicitly modelled interdependencies between energy, transport, digital, waste, and water. Indeed, the novel contribution of the paper is the articulation of the case study describing a decade of research which applies complex adaptive systems properties to the development of a national infrastructure system-of-systems model. This approach has been used by the UK National Infrastructure Commission to produce a National Infrastructure Assessment which is capable of coordinating infrastructure policy across a historically fragmented governance landscape spanning eight government departments. The application will continue to be pertinent moving forward due to the continuing complexity of interdependent infrastructure systems, particularly the challenges of increased electrification and the proliferation of the Internet of Things.

Innovation, cooperation, and the structure of three regional sustainable agriculture networks in California

Abstract: Regional agroecological systems are examples of complex adaptive systems, where sustainability is promoted by social networks that facilitate information sharing, cooperation, and connectivity among specialized components of the system. Much of the existing literature on social capital fails to recognize how networks support multiple social processes. Our paper overcomes this problem by analyzing how the social networks of wine grape growers exhibit structural features related to multiple social processes: ties to central actors that build bridging social capital and facilitate the diffusion of innovations, ties that close triangles and build bonding social capital to solve cooperation dilemmas, and ties to individuals that span community boundaries to connect specialized components of the system. We use survey data to measure the communication networks of growers in three viticulture regions in California. A combination of descriptive statistics, conditional uniform random graph tests, and exponential random graph models provides empirical support for our hypotheses. The findings reflect regional differences in geography and institutional histories, which may influence the capacity to respond to regional environmental change.

Boundary‐spanning actors in complex adaptive governance systems: The case of multisectoral nutrition

Abstract: A growing literature highlights complexity of policy implementation and governance in global health and argues that the processes and outcomes of policies could be improved by explicitly taking this complexity into account. Yet there is a paucity of studies exploring how this can be achieved in everyday practice. This study documents the strategies, tactics, and challenges of boundary-spanning actors working in 4 Sub-Saharan Africa countries who supported the implementation of multisectoral nutrition as part of the African Nutrition Security Partnership in Burkina Faso, Mali, Ethiopia, and Uganda. Three action researchers were posted to these countries during the final 2 years of the project to help the government and its partners implement multisectoral nutrition and document the lessons. Prospective data were collected through participant observation, end-line semistructured interviews, and document analysis. All 4 countries made significant progress despite a wide range of challenges at the individual, organizational, and system levels. The boundary-spanning actors and their collaborators deployed a wide range of strategies but faced significant challenges in playing these unconventional roles. The study concludes that, under the right conditions, intentional boundary spanning can be a feasible and acceptable practice within a multisectoral, complex adaptive system in low- and middle-income countries.

Using flawed, uncertain, proximate and sparse (FUPS) data in the context of complexity: learning from the case of child mental health.

Abstract: The use of routinely collected data that are flawed and limited to inform service development in healthcare systems needs to be considered, both theoretically and practically, given the reality in many areas of healthcare that only poor-quality data are available for use in complex adaptive systems. Data may be compromised in a range of ways. They may be flawed, due to missing or erroneously recorded entries; uncertain, due to differences in how data items are rated or conceptualised; proximate, in that data items are a proxy for key issues of concern; and sparse, in that a low volume of cases within key subgroups may limit the possibility of statistical inference. The term ‘FUPS’ is proposed to describe these flawed, uncertain, proximate and sparse datasets. Many of the systems that seek to use FUPS data may be characterised as dynamic and complex, involving a wide range of agents whose actions impact on each other in reverberating ways, leading to feedback and adaptation. The literature on the use of routinely collected data in healthcare is often implicitly premised on the availability of high-quality data to be used in complicated but not necessarily complex systems. This paper presents an example of the use of a FUPS dataset in the complex system of child mental healthcare. The dataset comprised routinely collected data from services that were part of a national service transformation initiative in child mental health from 2011 to 2015. The paper explores the use of this FUPS dataset to support meaningful dialogue between key stakeholders, including service providers, funders and users, in relation to outcomes of services. There is a particular focus on the potential for service improvement and learning. The issues raised and principles for practice suggested have relevance for other health communities that similarly face the dilemma of how to address the gap between the ideal of comprehensive clear data used in complicated, but not complex, contexts, and the reality of FUPS data in the context of complexity.

Unraveling the Complexity of the Jevons Paradox: The Link Between Innovation, Efficiency, and Sustainability

Abstract: The term ‘Jevons Paradox’ flags the need to consider the different hierarchical scales at which a system under analysis changes its identity in response to an innovation. Accordingly, an analysis of the implications of the Jevons Paradox must abandon the realm of reductionism and deal with the complexity inherent in the issue of sustainability: When studying evolution and real change how can we define “what has to be sustained” in a system that continuously becomes something else? In an attempt to address this question this paper presents three theoretical concepts foreign to conventional scientific analysis: (i) complex adaptive systems—to address the peculiar characteristics of learning and self-producing systems; (ii) holons and holarchy—to explain the implications of the ambiguity found when observing the relation between functional and structural elements across different scales (steady-state versus evolution); and (iii) Holling’s adaptive cycle—to illustrate the existence of different phases in the evolutionary trajectory of a complex adaptive system interacting with its context in which either external or internal constraints can become limiting. These concepts are used to explain systemic drivers of the Jevons Paradox. Looking at society’s thermodynamic foundations, sustainability is based on a dynamic balance of two contrasting principles regulating the evolution of complex adaptive systems: the minimum entropy production and the maximum energy flux. The co-existence of these two principles explains why in different situations innovation has to play a different role in the ‘sustainable development’ of society: (i) when society is not subject to external biophysical constraints improvements in efficiency serve to increase the final consumption of society and expand its diversity of functions and structures; (ii) when the expansion of society is limited by external constraints improvements in efficiency should be used to avoid as much as possible the loss of the existing diversity. It is concluded that sustainability cannot be achieved by technological innovations alone, but requires a continuous process of institutional and behavioral adjustment.

Smallholder Value Chains as Complex Adaptive Systems: A Conceptual Framework

Abstract: Purpose Smallholder value chains are dynamic, changing over time in sudden, unpredictable ways as they adapt to shocks. Understanding these dynamics and adaptation is essential for these chains to remain competitive in turbulent markets. Many guides to value chain development, though they focus welcome attention on snapshots of current structure and performance, pay limited attention to the dynamic forces affecting these chains or to adaptation. The paper aims to discuss these issues. Design/methodology/approach This paper develops an expanded conceptual framework to understand value chain performance based on the theory of complex adaptive systems. The framework combines seven common properties of complex systems: time, uncertainty, sensitivity to initial conditions, endogenous shocks, sudden change, interacting agents and adaptation. Findings The authors outline how the framework can be used to ask new research questions and analyze case studies in order to improve our understanding of the development of smallholder value chains and their capacity for adaptation. Research limitations/implications The framework highlights the need for greater attention to value chain dynamics. Originality/value The framework offers a new perspective on the dynamics of smallholder value chains.

Advancing Complexity Theory as a Qualitative Research Methodology

Abstract: Although complexity theory is increasingly used to explain and understand complex health-system behavior, little is known about utilizing complexity theory to augment qualitative research methods. ...

Regional Innovation Systems as Complex Adaptive Systems: The Case of Lagging European Regions

Abstract: This article proposes an agent-based model to support the development of self-sustaining regional innovation systems (RIS). The model is the base of a computational laboratory, CARIS (Complex Adaptive Regional Innovation System), which aims at evaluating the self-sustainability of RIS and at investigating what are the resources, competencies and mechanisms able to trigger powerful innovation and economic growth processes. Such a topic is particularly interesting for the so-called lagging regions, which, notwithstanding noticeable policy interventions, have been unable to significantly improve their innovation performances. Results of this study show that the exploration capacity, the propensity to cooperation, and the endowed competencies of actors belonging to a region could be considered as key aspects in affecting the regional innovation performance. This means that policy-makers should (i) incentivize investments in research and development activities both at the public and private levels; (ii) support public-private partnerships; (iii) enhance national and regional university systems; and (iv) increase the number of researchers employed both in the public and private sectors. In the next future, the CARIS laboratory could be adopted as policy support instrument to evaluate how much effective are current innovation policies and what are the most effective ones to reassess the current patterns.

Collaboration, Adaptation, and Scaling: Perspectives on Environmental Governance for Sustainability

Abstract: In preview of the special issue on “Environmental Governance for Sustainability”, this manuscript examines three key themes on governance and sustainability. Governance for sustainability, by its nature, requires long-enduring institutional arrangements. Given the complex adaptive systems in which governance decision-making takes place, we explore three key characteristics of successful, long-term governance. The first of these is working across scale. This includes nested institutions as well as communication and coordination both horizontally and vertically between diverse governance groups. Second, we highlight the importance of collaboration. Building on the previous point, we draw on literature from collaborative governance and co-management to emphasize how collaboration can help to build more enduring governance structures. Third, we examine the importance of adaptation and evolution in the resolution of collective action dilemmas in complex systems filled with nonlinearities, unclear causal chains, and environments in which we have less than a full understanding of the ramifications of governance actions.

Explaining the emergence of team agility: a complex adaptive systems perspective

Abstract: Agile software development helps software producing organizations to respond to manifold challenges. While prior research focused on agility as a project or process phenomenon, the authors suggest that agility is an emergent phenomenon on the team level. The paper aims to discuss this issue.,Using the theory of complex adaptive systems (CASs), the study captures the multiple influencing levels of software development teams (SDTs) and their interplay with self-organization and emergence. The authors investigate three agile SDTs in different contextual environments that participate with four or more different roles each.,The results suggest self-organization as a central process when understanding team agility. While contextual factors often provide restriction on self-organization, they can help the team to enhance its autonomy.,The theoretical contributions result from the development and test of theory grounded propositions and the investigation of mature agile development teams.,The findings help practitioners to improve the cost-effectiveness ratio of their team’s operations.,The study provides empirical evidence for the emergence of team agility in agile SDTs. Using the lens of CAS, the study suggests the importance of the team’s autonomy.

Implementation of Integrated Care in Singapore: A Complex Adaptive System Perspective.

Abstract: Background: Integrated care that focuses on organising healthcare services around people and their communities rather than their diseases is promoted as the strategy to overcome the challenges associated with growing complexity in healthcare needs, demand for healthcare services and inadequate supply of services due to fragmentation in the provision of services. While conceptually appears to be simple, integrated care is made up of multicomponent delivery strategies targeting various levels of the healthcare system while engaging various stakeholders in their execution. Methods: We applied the complex adaptive system (CAS) perspective to two different initiatives that exemplify approaches towards integrating care in Singapore: the Regional Health System (RHS) model, implemented across healthcare institutions at the national level, and CARITAS Integrated Dementia Care implemented in the northern region of Singapore. We adopted an inductive approach in our analysis in which we studied the RHS and CARITAS Integrated Dementia Care according to the components of the CAS. We applied the typical characteristics of CAS: (i) diverse, interdependent and semi-autonomous actors (ii) self-organizing capacity and simple rules (iii) relationship with the bigger system, emergent behaviour and non-linearity in our analysis of key drivers behind the implementation of both the RHS and CARITAS integrated dementia care. Results: By considering the RHS and CARITAS as whole networks each comprising of interacting and adaptive components instead of separate entities within a bigger system, the CAS provided a new mind-set in surfacing issues associated to the implementation of these integrated care networks. In addition to important actors, systems, it informed understanding of relationships and dependencies between different parts of the network – revealing the lack of homogeneity, conformity and difficulties in designing any optimal system in advance given the many moving parts. Conclusions: Drawing on the two examples of integrated care networks, this paper highlights the significance of effective collaboration built on a common focus, responsiveness to emergent behaviours, simple rules, the ability to self-organize and adapt in response to unexpected situations in further development of integrated care in the Singapore context and beyond.

Scaling up ART adherence clubs in the public sector health system in the Western Cape, South Africa: a study of the institutionalisation of a pilot innovation

Abstract: In 2011, a decision was made to scale up a pilot innovation involving ‘adherence clubs’ as a form of differentiated care for HIV positive people in the public sector antiretroviral therapy programme in the Western Cape Province of South Africa. In 2016 we were involved in the qualitative aspect of an evaluation of the adherence club model, the overall objective of which was to assess the health outcomes for patients accessing clubs through epidemiological analysis, and to conduct a health systems analysis to evaluate how the model of care performed at scale. In this paper we adopt a complex adaptive systems lens to analyse planned organisational change through intervention in a state health system. We explore the challenges associated with taking to scale a pilot that began as a relatively simple innovation by a non-governmental organisation. Our analysis reveals how a programme initially representing a simple, unitary system in terms of management and clinical governance had evolved into a complex, differentiated care system. An innovation that was assessed as an excellent idea and received political backing, worked well whilst supported on a small scale. However, as scaling up progressed, challenges have emerged at the same time as support has waned. We identified a ‘tipping point’ at which the system was more likely to fail, as vulnerabilities magnified and the capacity for adaptation was exceeded. Yet the study also revealed the impressive capacity that a health system can have for catalysing novel approaches. We argue that innovation in largescale, complex programmes in health systems is a continuous process that requires ongoing support and attention to new innovation as challenges emerge. Rapid scaling up is also likely to require recourse to further resources, and a culture of iterative learning to address emerging challenges and mitigate complex system errors. These are necessary steps to the future success of adherence clubs as a cornerstone of differentiated care. Further research is needed to assess the equity and quality outcomes of a differentiated care model and to ensure the inclusive distribution of the benefits to all categories of people living with HIV.

Moving alcohol prevention research forward-Part I: introducing a complex systems paradigm.

Abstract: Background and aims The drinking environment is a complex system consisting of a number of heterogeneous, evolving, and interacting components, which exhibit circular causality and emergent properties. These characteristics reduce the efficacy of commonly used research approaches, which typically do not account for the underlying dynamic complexity of alcohol consumption and the interdependent nature of diverse factors influencing misuse over time. We use alcohol misuse among college students in the United States as an example for framing our argument for a complex systems paradigm. Methods A complex systems paradigm, grounded in socioecological and complex systems theories and computational modeling and simulation, is introduced. Theoretical, conceptual, methodological, and analytical underpinnings of this paradigm are described in the context of college drinking prevention research. Results The proposed complex systems paradigm can transcend limitations of traditional approaches, thereby fostering new directions in alcohol prevention research. By conceptualizing student alcohol misuse as a complex adaptive system, computational modeling and simulation methodologies and analytical techniques can be used. Moreover, use of participatory model-building approaches to generate simulation models, can further increase stakeholder buy-in, understanding, and policymaking. Conclusions A complex systems paradigm for research into alcohol misuse can provide a holistic understanding of the underlying drinking environment and its long-term trajectory, which can elucidate high-leverage preventive interventions.

Portfolios of Agile Projects: A Complex Adaptive Systems’ Agent Perspective

Abstract: While agile approaches can be extremely effective at a project level, they can impose significant complexity and a need for adaptiveness at the project portfolio level. While this has proven to be ...

On the road to carbon reduction in a food supply network: a complex adaptive systems perspective

Abstract: Purpose: In acknowledging the reality of climate change, large firms have set internal and external (supplier oriented) targets to reduce their greenhouse gas (GHG) emissions. This study explores the complex processes behind the evolution and diffusion of carbon reduction strategies in supply networks. Design/methodology/approach: The research uses complex adaptive systems (CAS) as a theoretical framework and presents a single case study of a focal buying firm and its supply network in the food sector. A longitudinal and multilevel analysis is used to discuss the dynamics between the focal firm, the supply network and external environment. Findings: Rather than being a linear and controlled process of adoption-implementation-outcomes, the transition to reduce carbon in a supply network is much more dynamic, emerging as a result of a number of factors at the individual, organizational, supply network and environmental levels. Research limitations/implications: The research considers the emergence of a carbon reduction strategy in the food sector, driven by a dominant buying firm. Future research should seek to investigate the diffusion of environmental strategies more broadly and in other contexts. Practical implications: Findings from the research reveal the limits of the control that a buying firm can exert over behaviours in its network and show the positive influence of consortia initiatives on transitioning to sustainability in supply networks. Originality: CAS is a fairly novel theoretical lens for researching environmental supply network dynamics. The paper offers fresh multilevel insights into the emergent and systemic nature of the diffusion of environmental practices in supply networks.