Systems archetypes to investigate the unintended consequences of telehealth in rural Australia: A systems thinking approach to telehealth evaluation and policymaking.

As an alternative model of delivery to standard care, telehealth offers a promising solution to health access issues faced by rural and remote communities in Australia and worldwide. However, research typically focuses on its expected benefits and pitfalls, with little to no consideration of its unintended consequences and factors influencing its better utilisation. Drawing on systems thinking and informed by complexity science, we propose using systems archetypes-systems thinking tools - as a magnifying lens to investigate potential telehealth unintended consequences or outcomes. We conceptualise telehealth implementation in rural and remote Australia as a sociotechnical system whereby the interactions between its various agents shape telehealth implementation and, in turn, are shaped by it. When introducing new policies or interventions to any system, these interactions often lead to outcomes other than those initially planned or intended. Although systems archetypes cannot necessarily predict these outcomes, they are valuable for helping anticipate unintended, unforeseen outcomes and facilitating discussions about them to mitigate their negative impact and maximise their benefits. Outcomes are not necessarily adverse; they can also be positive. So, investigating such outcomes will minimise their negative impact and maximise their benefit. Our method was to review existing research and a selection of complexity and systems informed frameworks. Then, we assessed systems archetypes. And how they can be utilised to investigate unintended consequences. A worked example of what an unintended consequence in the implementation of telehealth in rural and remote Australia is presented.

How exposure to chronic stress contributes to the development of type 2 diabetes: A complexity science approach.

Chronic stress contributes to the onset of type 2 diabetes (T2D), yet the underlying etiological mechanisms are not fully understood. Responses to stress are influenced by earlier experiences, sex, emotions and cognition, and involve a complex network of neurotransmitters and hormones, that affect multiple biological systems. In addition, the systems activated by stress can be altered by behavioral, metabolic and environmental factors. The impact of stress on metabolic health can thus be considered an emergent process, involving different types of interactions between multiple variables, that are driven by non-linear dynamics at different spatiotemporal scales. To obtain a more comprehensive picture of the links between chronic stress and T2D, we followed a complexity science approach to build a causal loop diagram (CLD) connecting the various mediators and processes involved in stress responses relevant for T2D pathogenesis. This CLD could help develop novel computational models and formulate new hypotheses regarding disease etiology.

The challenges facing residential aged care homes to participate in quality food and nutrition research.

BACKGROUND: There is a clear need for food and nutrition research to lead to pragmatic and sustainable solutions to the ongoing problems in residential aged care, particularly within foodservices. The present study aimed to identify systemic challenges for residential aged care homes in Australia to participate in quality food and nutrition research, using a complexity science lens. METHODS: Qualitative data from three studies in residential aged care were gathered, which included 28 participants across 21 aged care homes. Qualitative data consisted of in-depth interviews, field notes and email communications with aged care staff. Thematic analysis was undertaken using both inductive and deductive approaches. RESULTS: Four themes were identified: (1) complex staffing issues deter or impede participation in research; (2) external pressure on the aged care system leads to research not being a priority; (3) funding issues are variable and pose a barrier for some aged care homes; and (4) research processes and requirements can lead to biased samples. CONCLUSIONS: Several challenges to undertaking quality empirical research in residential aged care in Australia were identified. Research needs to be part of usual business, similar to hospitals, and operate independently of staffing and funding issues. Issues within foodservices are system issues and there is a need for quality empirical research to determine solutions.

Resilience in advanced cancer caregiving promoted by an intimate partner's support network: insights through the lens of complexity science. A framework analysis.

BACKGROUND: The tremendous physical and mental burden that comes with caregiving puts the intimate partners of patients diagnosed with advanced cancer at risk for mental disorders. However, most partners seem to be protected by resilience. Such a resilience process is promoted by certain individual characteristics (e.g., flexibility, positive attitude, internal strength, capacity to balance incoming and outgoing information, and ability to ask for and accept support and advice) and by the availability of a support network, consisting of family, friends, and healthcare professionals. Such a heterogeneous group striving towards the same goals can be considered a complex adaptive system (CAS), a concept stemming from complexity science. AIMS: To study the behavior of the support network through the lens of complexity science and to provide insights to the means by which an available network may promote resilience. METHODS: Nineteen interviews with members from the support networks of eight intimate partners were analyzed deductively using the CAS principles as a coding framework. Subsequently, the quotes under each principle were coded inductively to concretize patterns in the behavior of the support networks. Eventually, the codes were charted into a matrix to identify intra- and inter-CAS similarities, differences, and patterns. FINDINGS: The network's behavior adapts dynamically to the changing circumstances as the patient's prognosis worsens. Furthermore, the behavior is based on internalized basic rules (such as reassuring availability and maintaining communication without being intrusive), attractors (e.g., feeling meaningful, appreciated, or connected), and the history of the support network. However, the interactions are non-linear and often unpredictable due to the context member's own concerns, needs, or emotions. CONCLUSIONS: Applying the lens of complexity science to the behavior of an intimate partner's support network gives us insight into the network's behavioral patterns. Indeed, a support network is a dynamic system that behaves according to the principles of a CAS and adapts resiliently to the changing circumstances as the patient's prognosis worsens. Moreover, the behavior of the support network appears to promote the intimate partner's resilience process throughout the patient's care period.

Examining the nexus between medical education and complexity: a systematic review to inform practice and research.

BACKGROUND: Medical education is a multifarious endeavour integrating a range of pedagogies and philosophies. Complexity as a science or theory ('complexity') signals a move away from a reductionist paradigm to one which appreciates that interactions in multi-component systems, such as healthcare systems, can result in adaptive and emergent outcomes. This examination of the nexus between medical education and complexity theory aims to discover ways that complexity theory can inform medical education and medical education research. METHODS: A structured literature review was conducted to examine the nexus between medical education and complexity; 5 databases were searched using relevant terms. Papers were included if they engaged fully with complexity as a science or theory and were significantly focused on medical education. All types of papers were included, including conceptual papers (e.g. opinion and theoretical discussions), case studies, program evaluations and empirical research. A narrative and thematic synthesis was undertaken to create a deep understanding of the use of complexity in medical education. RESULTS: Eighty-three papers were included; the majority were conceptual papers. The context and theoretical underpinnings of complexity as a relevant theory for medical education were identified. Bibliographic and temporal observations were noted regarding the entry of complexity into medical education. Complexity was relied upon as a theoretical framework for empirical studies covering a variety of elements within medical education including: knowledge and learning theories; curricular, program and faculty development; program evaluation and medical education research; assessment and admissions; professionalism and leadership; and learning for systems, about systems and in systems. DISCUSSION: There is a call for greater use of theory by medical educators. Complexity within medical education is established, although not widespread. Individualistic cultures of medicine and comfort with reductionist epistemologies challenges its introduction. However, complexity was found to be a useful theory across a range of areas by a limited number of authors and is increasingly used by medical educators and medical education researchers. This review has further conceptualized how complexity is being used to support medical education and medical education research. CONCLUSION: This literature review can assist in understanding how complexity can be useful in medical educationalists' practice.

Measuring fundamental care using complexity science: A descriptive case study of a methodological innovation.

AIMS AND OBJECTIVES: This paper presents an exploratory account of an innovative methodology to record and evaluate fundamental care. Fundamental care is defined as the care required by everyone for survival, health and welfare. BACKGROUND: Fundamental care has been informed by the development and testing of the Fundamentals of Care Framework, which describes how fundamental care is complex and multidimensional, and consists of three interrelated dimensions and 38 elements. This accords with a broader re-examination of care provision as part of a complex adaptive system in which existing linear models of cause and effect are inadequate to describe the totality of activity. DESIGN: Informed by graph theory and complexity science, this paper presents a novel methodological innovation. It uses the Fundamentals of Care Framework to create a Matrix to quantify the relationships between different elements within the Framework. METHODS: We use a Matrix methodology to process care recipient narratives to generate three outputs: a heat map, a summary table and a network analysis. CONCLUSIONS: The three outputs serve to quantify and evaluate fundamental care in a multidimensional manner. They capture different perspectives (care recipients and their families, direct care providers and care managers) to improve care outcomes. The future aim is to advance this exploration into digitalising and operationalising the Matrix in a user-friendly manner for it to become a real-time mechanism to evaluate and potentially predict patterns of fundamental care.

Self-Organization of Interprofessional Staff to Improve Mobility of Hospitalized Patients with STRIDE: a Complexity Science-Informed Qualitative Study.

BACKGROUND: Inpatient mobility programs can help older adults maintain function during hospitalization. Changing hospital practice can be complex and require engagement of various staff levels and disciplines; however, we know little about how interprofessional teams organize around implementing such interventions. Complexity science can inform approaches to understanding and improving multidisciplinary collaboration to implement clinical programs. OBJECTIVE: To examine, through a complexity science lens, how clinical staff's understanding about roles in promoting inpatient mobility evolved during implementation of the STRIDE (assiSTed eaRly mobIlity for hospitalizeD older vEterans) hospital mobility program. DESIGN: Qualitative study using semi-structured interviews. PARTICIPANTS: Ninety-two clinical staff at eight Veterans Affairs hospitals. INTERVENTIONS: STRIDE is a supervised walking program for hospitalized older adults designed to maintain patients' mobility and function. APPROACH: We interviewed key staff involved in inpatient mobility efforts at each STRIDE site in pre- and post-implementation periods. Interviews elicited staff's perception of complexity-science aspects of inpatient mobility teams (e.g., roles over time, team composition). We analyzed data using complexity science-informed qualitative content analysis. KEY RESULTS: We identified three key themes related to patterns of self-organization: (1) individuals outside of the "core" STRIDE team voluntarily assumed roles as STRIDE advocates, (2) leader-champions adapted their engagement level to match local implementation team needs during implementation, and (3) continued leadership support and physical therapy involvement were key factors for sustainment. CONCLUSIONS: Staff self-organized around implementation of a new clinical program in ways that were responsive to changing program and contextual needs. These findings demonstrate the importance of effective self-organization for clinical program implementation. Researchers and practitioners implementing clinical programs should allow for, and encourage, flexibility in staff roles in planning for implementation of a new clinical program, encourage the development of advocates, and engage leaders in program planning and sustainment efforts.

The role of implementation science in improving epilepsy surgery utilization.

Randomized controlled studies demonstrated that patients with intractable epilepsy could benefit significantly more from epilepsy surgery than from continuing medical therapy. Unfortunately, robust efforts over the last few decades, including the formation and dissemination of guidelines and practice parameters, did not improve the utilization of epilepsy surgery. Epilepsy surgery remains one of the most underutilized evidence-based interventions in modern medicine. A new scientific study of methods has emerged to improve uptake of evidence-based practices, named implementation science (IS). Despite its tremendous rise in popularity in various domains, its usage to mitigate epilepsy surgery underutilization is very limited. In fact, the application of principles and methods of IS are somewhat restricted in the entire neuroscience field, where quality improvement (QI) efforts primarily drive the provision of high-quality health care. Although both QI efforts and IS have a similar goal of improving healthcare quality, they differ significantly in associated terminologies, concepts, and approaches. For implementing high-quality, evidence-based practices in routine clinical settings, we need a better understanding of IS methods and closer integration between QI and IS fields. Recognizing a dearth of awareness of IS in the neuroscience community, the first part of the review addresses the fundamentals of IS, focusing on multifaceted implementation strategies that neurologists can apply in their clinical practice. In the second part of the review, an entire illustrative case is presented to familiarize neurologists with the practical application of diverse implementation strategies to mitigate the underutilization of epilepsy surgery.

Introducing the 21st Century's New Four Horsemen of the Coronapocalypse.

As the world struggles through the COVID-19 pandemic, we should also be asking what systems-level measures will be needed to prevent this or even worse disasters from happening in the future. We argue that the pandemic is merely one of potentially myriad and pleiomorphic future global disasters generated by the same underlying dynamical system. We explain that there are four broad but easily identifiable systemic, pathologically networked conditions that are hurtling civilization toward potential self-destruction. As long as these conditions are not resolved, we should consider catastrophe as an inevitable emergent endpoint from the dynamics. All four conditions can be reversed with collective action to begin creating an enduring and thriving post- COVID-19 world. This will require maximal application of the precautionary principle.

Building engagement to support adoption of community-based substance use prevention initiatives.

BACKGROUND: System-level approaches that target social determinants of health are promising strategies to support substance use prevention, holistic youth development and wellbeing. Yet, the youth services system is largely based on individual-focused programs that do not adequately account for social determinants of health and place the responsibility for wellness on the individual. There is a need to understand how to enhance adoption of complex system-level approaches that support comprehensive youth development. The Icelandic Prevention Model (IPM) represents a collaborative initiative that takes an ecological, system-level approach to prevent substance use and promote wellness in youth. This research was designed to examine key stakeholder perceptions to better understand social motivations and contextual complexities that influence stakeholder support to garner community-level adoption of the IPM in a rural Canadian community. METHODS: This research applies a case study approach using qualitative interviews to explore strategies to support uptake in the early stages of IPM adoption associated with developing community buy-in and acceptance. A thematic analysis was applied using QSR NVivo. RESULTS: Nine interviews were conducted with community partners leading the implementation of the IPM. Three over-arching themes emerged from the data: 1) Motivating influences 2) Strategies to develop buy-in, and 3) Resistance to the adoption of the IPM. Findings reflect issues that affect behaviour change in system transformation in general as well as upstream prevention and the IPM, in particular. CONCLUSIONS: The findings from this research describe critical insight derived from implementing community-driven initiatives that are designed to support health promotion. It contributes new scientific knowledge related to implementation of complex system-level innovations and practical information that is useful for communities interested in implementing the IPM or following similar approaches to prevent substance use.

Adapting to CONNECT: modifying a nursing home-based team-building intervention to improve hospital care team interactions, functioning, and implementation readiness.

BACKGROUND: Clinical interventions often need to be adapted from their original design when they are applied to new settings. There is a growing literature describing frameworks and approaches to deploying and documenting adaptations of evidence-based practices in healthcare. Still, intervention modifications are often limited in detail and justification, which may prevent rigorous evaluation of interventions and intervention adaptation effectiveness in new contexts. We describe our approach in a case study, combining two complementary intervention adaptation frameworks to modify CONNECT for Quality, a provider-facing team building and communication intervention designed to facilitate implementation of a new clinical program. METHODS: This process of intervention adaptation involved the use of the Planned Adaptation Framework and the Framework for Reporting Adaptations and Modifications, for systematically identifying key drivers, core and non-core components of interventions for documenting planned and unplanned changes to intervention design. RESULTS: The CONNECT intervention's original context and setting is first described and then compared with its new application. This lays the groundwork for the intentional modifications to intervention design, which are developed before intervention delivery to participating providers. The unpredictable nature of implementation in real-world practice required unplanned adaptations, which were also considered and documented. Attendance and participation rates were examined and qualitative assessment of reported participant experience supported the feasibility and acceptability of adaptations of the original CONNECT intervention in a new clinical context. CONCLUSION: This approach may serve as a useful guide for intervention implementation efforts applied in diverse clinical contexts and subsequent evaluations of intervention effectiveness. TRIAL REGISTRATION: The study was registered at ClinicalTrials.gov ( NCT03300336 ) on September 28, 2017.

Newtonian science, complexity science and suicide-critically analysing the philosophical basis for suicide research: A discussion paper.

AIM: A critical discussion comparing Newtonian science and complexity science as the philosophical basis for suicide research and its impact on suicide knowledge development and clinical practice. DESIGN: Discussion paper. DATA SOURCES: A review of literature on suicide research and complexity science ranging from 2000 to 2022. IMPLICATIONS FOR NURSING: Suicide research based on a Newtonian worldview can have negative consequences for suicide knowledge development and can permeate nursing practice in ways that take away from addressing the complex needs of patients, their families and healthcare teams. CONCLUSION: A Newtonian worldview as a philosophical basis for research is insufficient for the study of a phenomenon as complex as suicide. A complexity science approach is better suited to the study of suicide given the multiple, interrelated, emerging factors that can contribute to a person's decision to end their own life. IMPACT: Suggestions are provided as to how a complexity science approach to the research of suicide can inform useful knowledge development that better meets the needs of individuals facing suicidality and their families. Researchers, healthcare administrators and nurses providing care to those struggling with suicidality can benefit from adopting a complexity science worldview in addressing this multifaceted phenomenon.

Scar formation from the perspective of complexity science: a new look at the biological system as a whole.

A burn wound is a complex systemic disease at multiple levels. Current knowledge of scar formation after burn injury has come from traditional biological and clinical studies. These are normally focused on just a small part of the entire process, which has limited our ability to sufficiently understand the underlying mechanisms and to predict systems behaviour. Scar formation after burn injury is a result of a complex biological system-wound healing. It is a part of a larger whole. In this self-organising system, many components form networks of interactions with each other. These networks of interactions are typically non-linear and change their states dynamically, responding to the environment and showing emergent long-term behaviour. How molecular and cellular data relate to clinical phenomena, especially regarding effective therapies of burn wounds to achieve minimal scarring, is difficult to unravel and comprehend. Complexity science can help bridge this gap by integrating small parts into a larger whole, such that relevant biological mechanisms and data are combined in a computational model to better understand the complexity of the entire biological system. A better understanding of the complex biological system of post-burn scar formation could bring research and treatment regimens to the next level. The aim of this review/position paper is to create more awareness of complexity in scar formation after burn injury by describing the basic principles of complexity science and its potential for burn care professionals.

Variational Embedding Multiscale Sample Entropy: A Tool for Complexity Analysis of Multichannel Systems.

Entropy-based methods have received considerable attention in the quantification of structural complexity of real-world systems. Among numerous empirical entropy algorithms, conditional entropy-based methods such as sample entropy, which are associated with amplitude distance calculation, are quite intuitive to interpret but require excessive data lengths for meaningful evaluation at large scales. To address this issue, we propose the variational embedding multiscale sample entropy (veMSE) method and conclusively demonstrate its ability to operate robustly, even with several times shorter data than the existing conditional entropy-based methods. The analysis reveals that veMSE also exhibits other desirable properties, such as the robustness to the variation in embedding dimension and noise resilience. For rigor, unlike the existing multivariate methods, the proposed veMSE assigns a different embedding dimension to every data channel, which makes its operation independent of channel permutation. The veMSE is tested on both stimulated and real world signals, and its performance is evaluated against the existing multivariate multiscale sample entropy methods. The proposed veMSE is also shown to exhibit computational advantages over the existing amplitude distance-based entropy methods.

Intersectionality on the go: The diffusion of Black feminist knowledge across disciplinary and geographical borders.

Kimberlé Crenshaw coined the term "intersectionality" in 1989 as a critique of feminist and critical race scholarship's neglect of-respectively-race and gender. Since then, the concept has been interpreted and reinterpreted to appeal to new disciplinary, geographical, and sociocultural audiences, generating heated debates over its appropriation and continued political significance. Drawing on all 3,807 publications in Scopus that contain the word "intersectionality" in the title, abstract, or keywords, we map the spread of intersectionality in academia through its citations. Network analysis reveals the contours of its diffusion among the 6,098 scholars in our data set, while automated text analysis, manual coding, and the close reading of publications reveal how the application and interpretation of intersectional thinking has evolved over time and space. We find that the diffusion network exhibits communities that are not well demarcated by either discipline or geography. Communities form around one or a few highly referenced scholars who introduce intersectionality to new audiences while reinterpreting it in a way that speaks to their research interests. By examining the microscopic interactions of publications and citations, our complex systems approach is able to identify the macroscopic patterns of a controversial concept's diffusion.

The three numbers you need to know about healthcare: the 60-30-10 Challenge.

BACKGROUND: Healthcare represents a paradox. While change is everywhere, performance has flatlined: 60% of care on average is in line with evidence- or consensus-based guidelines, 30% is some form of waste or of low value, and 10% is harm. The 60-30-10 Challenge has persisted for three decades. MAIN BODY: Current top-down or chain-logic strategies to address this problem, based essentially on linear models of change and relying on policies, hierarchies, and standardisation, have proven insufficient. Instead, we need to marry ideas drawn from complexity science and continuous improvement with proposals for creating a deep learning health system. This dynamic learning model has the potential to assemble relevant information including patients' histories, and clinical, patient, laboratory, and cost data for improved decision-making in real time, or close to real time. If we get it right, the learning health system will contribute to care being more evidence-based and less wasteful and harmful. It will need a purpose-designed digital backbone and infrastructure, apply artificial intelligence to support diagnosis and treatment options, harness genomic and other new data types, and create informed discussions of options between patients, families, and clinicians. While there will be many variants of the model, learning health systems will need to spread, and be encouraged to do so, principally through diffusion of innovation models and local adaptations. CONCLUSION: Deep learning systems can enable us to better exploit expanding health datasets including traditional and newer forms of big and smaller-scale data, e.g. genomics and cost information, and incorporate patient preferences into decision-making. As we envisage it, a deep learning system will support healthcare's desire to continually improve, and make gains on the 60-30-10 dimensions. All modern health systems are awash with data, but it is only recently that we have been able to bring this together, operationalised, and turned into useful information by which to make more intelligent, timely decisions than in the past.

A scoping review of complexity science in nursing.

AIM: To describe how complexity science has been integrated into nursing. DESIGN: A scoping review. DATA SOURCE/REVIEW METHOD: Academic Search Elite, Scopus, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, PubMed and Web of Science were searched November 2016, updated in October 2017 and January 2020. The working process included: problem identification, literature search, data evaluation, synthesizing and presentation. RESULTS: Four categories were found in the included 89 articles: (a) how complexity science is integrated into the nursing literature in relation to nursing education and teaching; (b) patients' symptoms, illness outcome and safety as characteristics of complexity science in nursing; (c) that leaders and managers should see organizations as complex and adaptive systems, rather than as linear machines; and (d) the need for a novel approach to studying complex phenomena such as healthcare organizations. Lastly, the literature explains how complexity science has been incorporated into the discourse in nursing and its development. CONCLUSION: The review provided strong support for use in complexity science in the contemporary nursing literature. Complexity science is also highly applicable and relevant to clinical nursing practice and nursing management from an organizational perspective. The application of complexity science as a tool in the analysis of complex nursing systems could improve our understanding of effective interactions among patients, families, physicians and hospital and skilled nursing facility staff as well as of education. IMPACT: Understanding complexity science in relation to the key role of nurses in the healthcare environment can improve nursing work and nursing theory development. The use of complexity science provides nurses with a language that liberates them from the reductionist view on nursing education, practice and management.

Allometric Scaling of Mutual Information in Complex Networks: A Conceptual Framework and Empirical Approach.

Complexity and information theory are two very valuable but distinct fields of research, yet sharing the same roots. Here, we develop a complexity framework inspired by the allometric scaling laws of living biological systems in order to evaluate the structural features of networks. This is done by aligning the fundamental building blocks of information theory (entropy and mutual information) with the core concepts in network science such as the preferential attachment and degree correlations. In doing so, we are able to articulate the meaning and significance of mutual information as a comparative analysis tool for network activity. When adapting and applying the framework to the specific context of the business ecosystem of Japanese firms, we are able to highlight the key structural differences and efficiency levels of the economic activities within each prefecture in Japan. Moreover, we propose a method to quantify the distance of an economic system to its efficient free market configuration by distinguishing and quantifying two particular types of mutual information, total and structural.

Becoming fall-safe: a framework for reducing inpatient falls.

This article describes a 10-year programme of work that has reduced inpatient falls rate by 46% and how this improvement has been sustained. The methodology applied in this initiative has forced one Trust to challenge expectations about the inevitability of patient falls in hospital. This initiative has resulted in approximately 568 fewer falls each year. Based on costings from NHS Improvement, the estimated 5108 fewer falls between 2011 and 2019 have saved the Trust £13.3 million.

Building a learning community of Australian clinical genomics: a social network study of the Australian Genomic Health Alliance.

BACKGROUND: Adopting clinical genomics represents a major systems-level intervention requiring diverse expertise and collective learning. The Australian Genomic Health Alliance (Australian Genomics) is strategically linking members and partner organisations to lead the integration of genomic medicine into healthcare across Australia. This study aimed to map and analyse interconnections between members-a key feature of complexity-to capture the collaborations among the genomic community, document learning, assess Australian Genomics' influence and identify key players. METHODS: An online, whole network study collected relational data from members asking them about two time points: baseline, before Australian Genomics started operation in 2016 and current in 2018. Likert style questions assessed the influence of various sources of knowledge on the respondents' genomic practice. A secure link to the online questionnaire was distributed to all members of Australian Genomics during May 2018. Social network data was analysed and visually constructed using Gephi 0.9.2 software, and Likert questions were analysed using chi-squared computations in SPSS. The project was given ethical approval. RESULTS: Response rate was 57.81% (222/384). The genomic learning community within Australian Genomics was constructed from the responses of participants. There was a growth in ties from pre-2016 (2925 ties) to 2018 (6381 ties) and an increase in density (0.020 to 0.043) suggesting the strong influence of Australian Genomics in creating this community. Respondents nominated 355 collaborative partners from 24 different countries outside of Australia and 328 partners from within Australia but outside the alliance. Key players were the Australian Genomics Manager, two clinical geneticists and four Operational staff members. Most influential sources of learning were hands on learning, shared decision making, journal articles and conference presentations in contrast to formal courses. CONCLUSIONS: The successful implementation of clinical genomics requires the engagement of multidisciplinary teams across a range of conditions and expertise. Australian Genomics is shown to be facilitating this collaborative process by strategically building a genomic learning community. We demonstrate the importance of social processes in building complex networks as respondents name "hands on learning" and "making group decisions" the most potent influences of their genomic practice. This has implications for genomic implementation, education and work force strategies.