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Chimamanda Ngozi Adichie showed how a single story is limited and thereby distorts the true nature of an issue. During this COVID-19 pandemic there have been, at least, three consecutive single stories-the 'lethal threat' story, followed by the 'economic threat' story, and finally the 'vaccine miracle' story. None of these single stories can convincingly and permanently capture the dynamics of the pandemic. This is because countries experienced different morbidity and mortality patterns, different socioeconomic disadvantage, age and vulnerability of population, timing and level of lockdown with economic variability, and, despite heavy promotion, vaccines were beset with a significant and variable degree of hesitancy. Lack of transparency, coherence and consistency of pandemic management-arising from holding on to single storylines-showed the global deficiency of public health policy and planning, an underfunding of (public) health and social services, and a growing distrust in governments' ability to manage crises effectively. Indeed, the global management has increased already large inequities, and little has been learnt to address the growing crises of more infectious and potentially more lethal virus mutations. Holding onto single stories prevents the necessary learnings to understand and manage the complexities of 'wicked' problems, whereas listening to the many stories provides insights and pathways to do so effectively as well as efficiently.

Patients look to their clinicians for explanations and treatments that achieve predictable cures with certainty. Clinicians usually respond accordingly. Acknowledging uncertainty, while necessary, is difficult, anxiety-provoking and at times overwhelming for patients and clinicians alike. We here present three case studies to illustrate the uncertainties of managing patients with potentially life-threatening illnesses. Research aims to provide answers to clinical problems. But, conducting research almost inevitably entails a reduction of real-world complexities. Research ultimately can only provide 'partial or in general answers' mostly revealing new questions. Due to the complexity of clinical care, research cannot really achieve certainty and predictability for an individual within his specific living context and values. In an unavoidably uncertain environment, instead of oversimplifying, clinicians like patients-as far as possible-ought to better embrace a complexity thinking frame. This provides a deeper understanding how living bodies function as-a-whole within their living contexts. Uncertainty and unpredictability, being inherent elements of complexity thinking, cannot be overcome. However, it may be made easier to cope with uncertainty by at least adopting the thinking in probabilities for benefits and harms of patient related outcomes as introduced in Sackett's Evidence-Based Medicine framework. Through the lenses of evidence-based medicine and complexity sciences this paper critically explores the clinical management of three patients diagnosed as having coronary artery disease. They all received the same treatment even though they presented with very different clinical complaints arising from different disease manifestations. Looking at these case studies the authors reflect on the reasons behind this astonishing, but widely seen medical behaviour of 'one size fits all'. They critically reflect the importance of research and evidence in view of a person-centred solution.

Background: Public outrage about the treatment of aged care residents in some nursing homes has its origins in a failure in each facility's accountability framework. There is an overwhelming focus on documentation of organisational structures and care processes, detracting from what really matters - whether the wellbeing of residents has been achieved. Objective: This article examines process- or action-oriented versus outcomes- or interaction-oriented accountability principles and their impacts on aged care residents' care. Discussion: A 'performance outcomes approach' provides a more effective and efficient way to achieve high levels of care in aged care facilities. These findings are important in the context of potential recommendations arising from the Royal Commission into Aged Care Quality and Safety.

The recent sacking of Peter Gøtzsche from the Cochrane Collaboration Board raised strong responses and highlights the neglected issue about priorities-maintaining the reputation of the organization or vigorously debating the merits of scientific approaches to find answers to complex problems? The Cochrane approach hales the randomized trial (RCT) as the gold standard research approach and affirms that meta-analysis provides the ultimate proof (or platinum standard) to settle contentious issues confronting the clinician. However, most published medical research is wrong, and critics coined the acronym GIGO (garbage in, garbage out) as a meme to highlight the risks of blind faith in the hyped-up procedures of the EBM movement. This paper firstly explores the differences between the prevailing scientific method arising from the linear cause-and-effect assumption and the complex adaptive systems science methods arising from observations that most phenomena emerge from nonlinearity in networked systems. Most medical conditions are characterized by necessary features that by themselves are not sufficient to explain their nature and behaviour. Such nonlinear phenomena require modelling approaches rather than linear statistical and/or meta-analysis approaches to be understood. These considerations also highlight that research is largely stuck at the data and information levels of understanding which fails clinicians who depend on knowledge-the synthesis of information-to apply in an adaptive way in the clinical encounter. Clinicians are constantly confronted with the linked challenges of doing things right and doing the right thing for their patients. EBM and Cochrane with their restrictive approaches are the antithesis to a practice of medicine that is responsive to constantly changing patient needs. As such, the EBM/Cochrane crisis opens a window of opportunity to re-examine the nature of health, illness and disease, and the nature of health care and its systems for the benefits of its professionals and their patients. We are at the cusp of a paradigmatic shift towards an understanding a praxis of health care that takes account of its complexities.

Multimorbidity - the occurrence of two or more long-term conditions in an individual - is a major global concern, placing a huge burden on healthcare systems, physicians, and patients. It challenges the current biomedical paradigm, in particular conventional evidence-based medicine's dominant focus on single-conditions. Patients' heterogeneous range of clinical presentations tend to escape characterization by traditional means of classification, and optimal management cannot be deduced from clinical practice guidelines. In this article, we argue that person-focused care based in complexity science may be a transformational lens through which to view multimorbidity, to complement the specialism focus on each particular disease. The approach offers an integrated and coherent perspective on the person's living environment, relationships, somatic, emotional and cognitive experiences and physiological function. The underlying principles include non-linearity, tipping points, emergence, importance of initial conditions, contextual factors and co-evolution, and the presence of patterned outcomes. From a clinical perspective, complexity science has important implications at the theoretical, practice and policy levels. Three essential questions emerge: (1) What matters to patients? (2) How can we integrate, personalize and prioritize care for whole people, given the constraints of their socio-ecological circumstances? (3) What needs to change at the practice and policy levels to deliver what matters to patients? These questions have no simple answers, but complexity science principles suggest a way to integrate understanding of biological, biographical and contextual factors, to guide an integrated approach to the care of people with multimorbidity.

info:eu-repo/semantics/published

Coronavirus disease 2019 (COVID-19) dramatically unveiled the fragile state of the world’s health and social systems – the lack of emergency health crisis preparedness (under-resourced, weak leadership, strategic plans without clear lines of authority), siloed policy frameworks (focus on individual diseases and the lack of integration of health into the whole of societal activity and its impact on individual as well as community well-being and prosperity), and unclear communication (misguided rationale of policies, inconsistent interpretation of data). The net result is fear – about the disease, about risks and survival, and about economic security. We discuss the interdependencies among these domains and their emergent dynamics and emphasise the need for a robust distributed health system and for transparent communication as the basis for trust in the system. We conclude that systems thinking and complexity sciences should inform the redesign of strong health systems urgently to respond to the current health crisis and over time to build healthy, resilient, and productive communities.

The bureaucracy’s goal is to maintain uniformity and control within discrete areas of activity and relies on hierarchical processes and procedural correctness as means to suppress autonomous decision making. That worldview, however, is unsuited for problem solving of real world VUCA (Volatility, uncertainty, complexity and ambiguity) problems. Solving wicked problems in the VUCA world requires curiosity, creativity and collaboration, and a willingness to deeply engage and an ability to painstakingly work through their seemingly contradictory and chaotic pathways. In addition, it necessitates leadership. Leaders require a deep – indeed academic – understanding of the nature of the problems and the veracity of various problem-solving approaches. Leadership after all means "[facilitating] the necessary adaptive work that needs to be done by the people connected to the problem." That are the people at the coalface who understand and have to manage the complexities relating to problems unique to their local environment for which of the shelf solutions never work. Systems and complexity thinking is more than a tool, it is – in a sense – a way of being, namely deeply interested in understanding the highly interconnected and interdependent nature of the issues affecting our life and work. Hence, system and complexity thinking is, contrary to what Haynes and colleagues state in their "summation for the public reader," neither "overwhelming and hard [nor difficult] to use practically." Such a view is as much misleading as selfdefeating.

There is a significant need for reforming healthcare systems in most contexts worldwide, and radical proposals based on complexity science and systems thinking are necessary. Health systems around the world are failing on three fronts – they fail to meet the needs of people/patients, they are disease-focused rather than health centered, and they are economically unsustainable. Failed/failing systems cannot be reformed by incremental cost-management or policy changes; they need to be redesigned based on peoples/patients’ needs – these are far broader than disease-specific management and include social, community, work, and environmental domains. Embracing these insights is a major challenge for policy makers, not only do they have to convey the direction, they also have to facilitate the necessary adaptive work required by a large and diverse workforce within the health system and its institutions. Health system redesign, while not easy, is possible. The organizational change management literature provides the foundations to lead the process, and the complex adaptive systems literature provides the conceptual understanding of the dynamic interdependencies within and across the organizational scales of the health system. And finally, there are a number of examples that can guide the redesign process toward effective, efficient, and sustainable health systems.

Resilience has become a popular term, and its meaning varies widely depending on the context of its use. Its Latin origin, resilire, means "bouncing back"-should bouncing back be understood literally or rather metaphorically in the context of health, illness, dis-ease, and disease? This essay examines ecological, physiological, personal, and health system perspectives inherent in the concept of resilience. It emerges that regardless of the level of aggregation, resilience is a systems property-it is as much a property of each of the subsystems of network physiology, the person, and the health care delivery system as it is a property of the health system as a whole. Given the interdependencies between people, their internal and external environments, and the health service system, strengthening resilience, ie, the ability to positively adapt to challenges and changing circumstances, will require a broad-based public discourse: "How can we strengthen resilience and health for the benefit of people and society at large".

Background: General practice is regarded as central to the Australian health system. However, issues affecting the general practitioner (GP) workforce have been focused mainly on remuneration, numbers and distribution. The focus is shifting to how best to enable GPs to deliver effective, efficient and equitable care. Objectives: The aim of this paper is to identify important elements, dynamics and interdependencies that influence GPs' work and their ability to continually improve outcomes for individuals and communities. Discussion: Most important problems are multifaceted and cannot be reduced to a simple, single solution. Influence diagrams capture the interdependent domains that affect general practice, such as the variations in patients' needs in the community and the impact of disadvantage and care expectations on outcomes. Identifying interrelationships between key domains should capture the dynamics that 'feed the problem'. Finding 'best possible solutions' to improve interdependent system problems and avoid the inherent risk of unintended failures requires an ongoing mix of qualitative and quantitative modelling.

This commentary argues that to fully appreciate the complexities of knowledge transfer one firstly has to distinguish between the notions of "data, information, knowledge and wisdom," and that the latter two are highly context sensitive. In particular one has to understand knowledge as being personal rather than objective, and hence there is no form of knowledge that a-priori is more authoritative than another. Secondly, knowledge transfer in organisations can only be successful if the organisation is organised and managed as a "complex adaptive organisation" – its key characteristics arising from it’s a-priori defined common "purpose, goals and values." Knowledge transfer, seen as "whole of system/organisation learning," is highly context sensitive; while the principles may apply to many organisations, knowledge as such is not transferable from one context to another, it always will be a unique learning exercise at this particular point in time in this particular organisation.

> “Today, the need for people-centered primary health care is greater than at any time in history”[1][1] The challenges facing our health systems are immense. International efforts strive to meet the needs of aging populations, the rising prevalence of chronic disease and illness, and the

Introduction: Multiple dynamics of internal and external network interactions result in the emergent observable state of a person’s health and care. A tsunami of Big Data predictions are developing to identify specific interventions to improve health. Anticipatory care on the other hand, can be understood, using Rosen's model – to recognize our innate nature to anticipate health journeys with multiple ways of knowing including biopsychosocial domains. Theory/Methods: Monash Health is the largest public hospital and community care system in Victoria. Over 12,000 patients have a Big Data prediction of 3+ admission per year, with >30% potentially avoidable. The challenge for Monash Health remains how to improve their readmission. rates. Monash Health implemented the Patient Journey Record System (PaJR), a biopsychosocial telehealth tool to understand and manage potentially avoidable hospitalizations in a pilot service of 300 patients. Telecare guides regularly converse with “at risk” individuals to track their concerns and self-perceived health. The main journey characteristics of 3 randomly selected cases from PaJR, were descriptively analysed to examine the interface between prediction and anticipation. Results: Three cases, monitored for >25 calls over 6/12, were 1 male with gastrointestinal, alcohol, mild frailty and family problems, 1 male with moderate frailty, COPD and social isolation and 1 female with COPD, social isolation and moderated frailty. All had lower socioeconomic status. ANOVA (analysis of variance) demonstrated statistically significant differences among trajectories of ’Self Rated Health (SRH)’, ’Health/Care Change’, ’Medication/Drug/Alcohol Change’ and ’Support Structure Change’ within each and among all cases. Only ’Health/Care Change’ was consistently high and not statistically significantly different across all journeys (p>0.5). Only 2 patients had an admission. On examination of each trajectory, no admission was definitely predicted with both false negatives and positives. Admission rates reduced over time. Care responses fluctuations were continual. Discussion: Prediction would seem to be an imprecise activity in a patient with multiple unstable trajectories. It was not clear how, when and what root causes triggered each admission where they occurred, from the PaJR data, although Big Data analytics predicted the occurrence of >1 admission in the time period. Each person’s health and biopsychosocial circumstances were unique. Admission rates reduced over time and high levels of healthcare change suggested anticipatory care was enacted in response to the monitoring data. Conclusion: Three case studies of patients, with predicted high readmission risk, demonstrated journeys with fluctuating — ’SRH’, ’Medication/Drug/Alcohol Change’ and ’Support Structure Change’ and admission rates. All reported fluctuating ’Health/Care Change’. Anticipatory care may be informed, but not replaced by Big Data and journey analytics. Lessons learned: Close monitoring of highly variable journeys identified by Big Data predictions should enable anticipatory care. each trajectory in each setting Limitations: Case studies are not externally generalisable. Disease management was not a focus of the monitoring activity. Suggestions for future research: Research into the improvement in the nexus of Big Data predictive analytics and anticipatory care in the quest to intervene in the emergent observable state of a person’s health to improve health and better utilize health care resources.

Marshall and colleagues’ call to “rethink medicine” is welcome, but it only half-heartedly tackles the fundamental problems dogging health services around the world.1 We need to rethink health, an emergent state resulting from adaptive dynamics between our social and biological …

Big data provide the hope of major health innovation and improvement. However, there is a risk of precision medicine based on predictive biometrics and service metrics overwhelming anticipatory human centered sense-making, in the fuzzy emergence of personalized (big data) medicine. This is a pressing issue, given the paucity of individual sense-making data approaches. A human-centric model is described to address the gap in personal particulars and experiences in individual health journeys. The Patient Journey Record System (PaJR) was developed to improve human-centric healthcare by harnessing the power of person-centred data analytics using complexity theory, iterative health services and information systems applications over a 10 year period. PaJR is a web-based service supporting usually bi-weekly telephone calls by care guides to individuals at risk of readmissions.

Max Planck observed that ‘If you change the way you look at things, things you look at change’. It is high time for healthcare professionals to embrace the challenge—the linear reductionist view of health and disease is failing our patients, our profession and our societies. These insights are not really new, Osler has coined many aphorisms to emphasise the need to understand the person with an illness over and above the diseases that might be responsible for his predicament.

We argue that 'multimorbidity' is the manifestation of interconnected physiological network processes within an individual in his or her socio-cultural environment. Networks include genomic, metabolomic, proteomic, neuroendocrine, immune and mitochondrial bioenergetic elements, as well as social, environmental and health care networks. Stress systems and other physiological mechanisms create feedback loops that integrate and regulate internal networks within the individual. Minor (e.g. daily hassles) and major (e.g. trauma) stressful life experiences perturb internal and social networks resulting in physiological instability with changes ranging from improved resilience to unhealthy adaptation and 'clinical disease'. Understanding 'multimorbidity' as a complex adaptive systems response to biobehavioural and socio-environmental networks is essential. Thus, designing integrative care delivery approaches that more adequately address the underlying disease processes as the manifestation of a state of physiological dysregulation is essential. This framework can shape care delivery approaches to meet the individual's care needs in the context of his or her underlying illness experience. It recognizes 'multimorbidity' and its symptoms as the end product of complex physiological processes, namely, stress activation and mitochondrial energetics, and suggests new opportunities for treatment and prevention. The future of 'multimorbidity' management might become much more discerning by combining the balancing of physiological dysregulation with targeted personalized biotechnology interventions such as small molecule therapeutics targeting specific cellular components of the stress response, with community-embedded interventions that involve addressing psycho-socio-cultural impediments that would aim to strengthen personal/social resilience and enhance social capital.

Terminology matters - as Lakoff emphasised, words and phrases evoke powerful images and frames of understanding. It is for that reason that we need to discern and use appropriately the term complex/complexity in the health science/professional/policy domain. Complex is the fashionable term used when in reality one means 'complicated', 'difficult to understand' or 'multiple simultaneous actions'. However, this is not what complex means. The Latin term means 'entwined/interwoven' - a structural characteristic describing systems. Complexity arises from the interactions between structurally connected entities - a functional characteristic of a system. The basis of scientific rigor is a clear understanding of a discipline's epistemology. Complexity refers to the emergence of outcomes from the interactions of a system's constituent components (and thus has nothing in common with the colloquial meaning of complicatedness).

BACKGROUND AND METHODS: Health systems are complex and constantly adapt to changing demands. These complex-adaptive characteristics are rarely considered in the current bureaucratic top-down approaches to health system reforms aimed to constrain demand and expenditure growth. The economic focus fails to address the needs of patients providers and communities and ultimately results in declining effectiveness and efficiency of the health care system as well as the health of the wider community. A needs-focused complex-adaptive health system can be represented by the healthcare vortex model; how to build a needs-focused complex-adaptive health system is illustrated by Eastern Deanery AIDS Relief Program approaches in the poor neighbourhoods of Nairobi Kenya. FINDINGS AND CONCLUSIONS: A small group of nurses and community health workers focused on the care of terminally ill HIV/AIDS patients. This work identified additional problems: tuberculosis (TB) was underdiagnosed and undertreated a local TB-technician was trained to run a local lab a courier services helped to reach all at need collaboration with the Ministry of Health established local TB and HIV treatment programmes and philanthropists helped to supplement treatment with nutrition support. Maternal-to-child HIV-prevention and adolescent counselling services addressed additional needs. The theory of the healthcare vortex indeed matches the empery of the real world experiences. Locally developed and delivered adaptive people-centred health systems a bottom-up community and provider initiated approach deliver highly effective and sustainable health care despite significant resource constraints. (c) 2016 John Wiley & Sons Ltd.

Background: The Australian Ecology of Medical Care indicates that 255/1,000 Australians consult a GP 1.8 times/month (466 consultations/month) resulting in 42 specialist, 1.4 ED and 1.9 hospital referrals, 478 prescriptions, 220 pathology and 48 radiology tests, costing the Government $ 72,009 (2012–13). Government believes this to be unsustainable and controllable by setting price signals. Objectives: To investigate the impact of ‘small changes’ to health service utilisation and/or resource use. Method: Modelling the impact of increases and decreases to healthcare utilisation/resource use over a 5-year period. Results: Strategies targeting only one variable had a small and linear impact on healthcare expenditure (± 0.6–7.2%); combining changes had an exponential effect, achieving an up to 15% reduction or an over 20% rise in expenditure. Discussion: Change invariably results in trade-offs; modelling is a tool that can provide a basis to engage in shared discussions about the ‘ yes, but/yes, and’ considerations of reform propositions

The epidemic of multimorbidity Policymakers regard “the epidemic of multimorbidity” as the greatest threat to the sustainability of healthcare systems. They believe the solution is “integrated care”, “ The search to connect the healthcare system (acute, primary medical and skilled) with other human service systems (e.g. long-term care, education and vocational and housing services) in order to improve outcomes (clinical, satisfaction, and efficiency)” [1]. This definition includes key characteristics of complex adaptive systems. People act as agents who evolve in their characteristics and behaviours over time. These agents constantly learn and adapt in real time to changing contexts. These systems display emergent dynamic non-linear behaviours resulting from ongoing iterative feedback amongst their agents. Emergent outcomes do not have linear “cause and effect” relationships and can best be understood in hindsight. Emergent behaviours are highly sensitive to context; consequently, the “same” approach used by different agents in different contexts will not produce the same outcomes. Agents navigate toward mutually agreed outcomes by constantly adapting to evolving changes within the context of local constraints [2]. A complex adaptive system approach overcomes many of the dysfunctions in the current health systems, in particular the fragmentation of patient care [3]. Overcoming fragmentation requires continuous adaptation to changing circumstances – a constant challenge for patients, health professionals, community service providers, and policymakers. How can the already overburdened primary healthcare services achieve these goals? To address the complex challenge, we first must reflect on three key questions: What is health? What is disease? What is multimorbidity? Journal of Comorbidity 2016;6(2):114–119

Covid-19 is more than an opportunity to reduce unnecessary care, it is an opportunity to redesign the health system as a whole. While there is no problem with Moynihan and colleagues’1 emphasis on overtreatment and overdiagnosis, these are two of the many phenotypical failings of …

Health and disease are largely seen as structural phenomena - visible changes in tissues and organs, rather than the result of complex adaptive physiological dynamics within the person, constrained by his internal structures and external environments. Health and disease are ecological phenomena; internal structures and external environments provide the landscapes in which the functions - physiological network interactions at the micro and behavioural interactions at the macro level - occur. These interactions are the functional responses in the quest for health and life.Embracing the person as a whole, that is, being person-centered, is thus an expression of a paradigm shift, a shift from the reductionist focus on disease to the complex-adaptive understandings of the person experiencing health, illness and disease.