Joachim P. Sturmberg

Fractals in physiology and medicine

Nonlinear dynamics, a branch of the basic sciences that studies complex physical systems, offers novel approaches to long-standing problems of physiological form and function. The nonlinear concept of fractals, introduced and developed over the last decade, provides insights into the organization of complex structures such as the tracheobronchial tree and heart, as well as into the dynamics of healthy physiological variability. Alterations in fractal scaling may underlie a number of pathophysiological disturbances, including sudden cardiac death syndromes. ImagesFIG. 2FIG. 4

Knowing – in Medicine

In this paper we argue that knowledge in health care is a multidimensional dynamic construct, in contrast to the prevailing idea of knowledge being an objective state. Polanyi demonstrated that knowledge is personal, that knowledge is discovered, and that knowledge has explicit and tacit dimensions. Complex adaptive systems science views knowledge simultaneously as a thing and a flow, constructed as well as in constant flux. The Cynefin framework is one model to help our understanding of knowledge as a personal construct achieved through sense making. Specific knowledge aspects temporarily reside in either one of four domains - the known, knowable, complex or chaotic, but new knowledge can only be created by challenging the known by moving it in and looping it through the other domains. Medical knowledge is simultaneously explicit and implicit with certain aspects already well known and easily transferable, and others that are not yet fully known and must still be learned. At the same time certain knowledge aspects are predominantly concerned with content, whereas others deal with context. Though in clinical care we may operate predominately in one knowledge domain, we also will operate some of the time in the others. Medical knowledge is inherently uncertain, and we require a context-driven flexible approach to knowledge discovery and application, in clinical practice as well as in health service planning.

Complexity and health – yesterday's traditions, tomorrow's future

‘If it is complex it means we don’t really understand it,and the way forward is to break the problem down into its partsto make sense of it’. This thought reflects the way we havebeen taught, and the way we largely practise in clinical care everyday.But are we really functioning on this basis? Or is it the only waywe know how to live? We all experience situations every daywhere the evidence does not really fit our understanding of aproblem – the familiar reductionist approach limits our ability tofully explore new problems and to gain new insight. An increas-ingly persistent question has emerged in relation to what consti-tutes the knowledge we need for effective and efficient clinicalcare, an issue taken up by this new

Generalist solutions to complex problems: generating practice-based evidence - the example of managing multi-morbidity.

BackgroundA growing proportion of people are living with long term conditions. The majority have more than one. Dealing with multi-morbidity is a complex problem for health systems: for those designing and implementing healthcare as well as for those providing the evidence informing practice. Yet the concept of multi-morbidity (the presence of >2 diseases) is a product of the design of health care systems which define health care need on the basis of disease status. So does the solution lie in an alternative model of healthcare?DiscussionStrengthening generalist practice has been proposed as part of the solution to tackling multi-morbidity. Generalism is a professional philosophy of practice, deeply known to many practitioners, and described as expertise in whole person medicine. But generalism lacks the evidence base needed by policy makers and planners to support service redesign. The challenge is to fill this practice-research gap in order to critically explore if and when generalist care offers a robust alternative to management of this complex problem.We need practice-based evidence to fill this gap. By recognising generalist practice as a ‘complex intervention’ (intervening in a complex system), we outline an approach to evaluate impact using action-research principles. We highlight the implications for those who both commission and undertake research in order to tackle this problem.SummaryAnswers to the complex problem of multi-morbidity won’t come from doing more of the same. We need to change systems of care, and so the systems for generating evidence to support that care. This paper contributes to that work through outlining a process for generating practice-based evidence of generalist solutions to the complex problem of person-centred care for people with multi-morbidity.

Systems and Complexity Thinking in the General Practice Literature: An Integrative, Historical Narrative Review

PURPOSE Over the past 7 decades, theories in the systems and complexity sciences have had a major influence on academic thinking and research. We assessed the impact of complexity science on general practice/family medicine. METHODS We performed a historical integrative review using the following systematic search strategy: medical subject heading [humans] combined in turn with the terms complex adaptive systems, nonlinear dynamics, systems biology, and systems theory, limited to general practice/family medicine and published before December 2010. A total of 16,242 articles were retrieved, of which 49 were published in general practice/family medicine journals. Hand searches and snowballing retrieved another 35. After a full-text review, we included 56 articles dealing specifically with systems sciences and general/family practice. RESULTS General practice/family medicine engaged with the emerging systems and complexity theories in 4 stages. Before 1995, articles tended to explore common phenomenologic general practice/family medicine experiences. Between 1995 and 2000, articles described the complex adaptive nature of this discipline. Those published between 2000 and 2005 focused on describing the system dynamics of medical practice. After 2005, articles increasingly applied the breadth of complex science theories to health care, health care reform, and the future of medicine. CONCLUSIONS This historical review describes the development of general practice/family medicine in relation to complex adaptive systems theories, and shows how systems sciences more accurately reflect the discipline’s philosophy and identity. Analysis suggests that general practice/family medicine first embraced systems theories through conscious reorganization of its boundaries and scope, before applying empirical tools. Future research should concentrate on applying nonlinear dynamics and empirical modeling to patient care, and to organizing and developing local practices, engaging in community development, and influencing health care reform.

Health at the Center of Health Systems Reform: How Philosophy Can Inform Policy

Contemporary views hold that health and disease can be defined as objective states and thus should determine the design and delivery of health services. Yet health concepts are elusive and contestable. Health is neither an individual construction, a reflection of societal expectations, nor only the absence of pathologies. Based on philosophical and sociological theory, empirical evidence, and clinical experience, we argue that health has simultaneously objective and subjective features that converge into a dynamic complex-adaptive health model. Health (or its dysfunction, illness) is a dynamic state representing complex patterns of adaptation to body, mind, social, and environmental challenges, resulting in bodily homeostasis and personal internal coherence. The “balance of health” model—emergent, self-organizing, dynamic, and adaptive—underpins the very essence of medicine. This model should be the foundation for health systems design and also should inform therapeutic approaches, policy decision-making, and the development of emerging health service models. A complex adaptive health system focused on achieving the best possible “personal” health outcomes must provide the broad policy frameworks and resources required to implement people-centered health care. People-centered health systems are emergent in nature, resulting in locally different but mutually compatible solutions across the whole health system.

User-driven health care: answering multidimensional information needs in individual patients utilizing post-EBM approaches: an operational model

The hypothesis in the conceptual model was that a user-driven innovation in presently available information and communication technology infrastructure would be able to meet patient and health professional users information needs and help them attain better health outcomes. An operational model was created to plan a trial on a sample diabetic population utilizing a randomized control trial design, assigning one randomly selected group of diabetics to receive electronic information intervention and analyse if it would improve their health outcomes in comparison with a matched diabetic population who would only receive regular medical intervention. Diabetes was chosen for this particular trial, as it is a major chronic illness in Malaysia as elsewhere in the world. It is in essence a position paper for how the study concept should be organized to stimulate wider discussion prior to beginning the study.

Evidence-based medicine: is it a bridge too far?

AimsThis paper aims to describe the contextual factors that gave rise to evidence-based medicine (EBM), as well as its controversies and limitations in the current health context. Our analysis utilizes two frameworks: (1) a complex adaptive view of health that sees both health and healthcare as non-linear phenomena emerging from their different components; and (2) the unified approach to the philosophy of science that provides a new background for understanding the differences between the phases of discovery, corroboration, and implementation in science.ResultsThe need for standardization, the development of clinical epidemiology, concerns about the economic sustainability of health systems and increasing numbers of clinical trials, together with the increase in the computer’s ability to handle large amounts of data, have paved the way for the development of the EBM movement. It was quickly adopted on the basis of authoritative knowledge rather than evidence of its own capacity to improve the efficiency and equity of health systems. The main problem with the EBM approach is the restricted and simplistic approach to scientific knowledge, which prioritizes internal validity as the major quality of the studies to be included in clinical guidelines. As a corollary, the preferred method for generating evidence is the explanatory randomized controlled trial. This method can be useful in the phase of discovery but is inadequate in the field of implementation, which needs to incorporate additional information including expert knowledge, patients’ values and the context.ConclusionEBM needs to move forward and perceive health and healthcare as a complex interaction, i.e. an interconnected, non-linear phenomenon that may be better analysed using a variety of complexity science techniques.

Perturbing ongoing conversations about systems and complexity in health services and systems

The term ‘unintended consequences’ [1] has become ubiquitous [2] in health policy and delivery circles. We argue that this is a sign of the growing unease arising from the realization of the limitations of the still dominant reductionist research approaches, ‘evidence’ and linear thinking in relation to health system and health services policy redesigning. Complexity theorists argue that many of the problems of health services and systems will not be solved through the application of more reductionism [3]. The most revered tool in reductionist research is the randomized controlled trial (RCT). However, as Cartwright has pointed out RCTs have very significant limitations for real world problems. ‘The claims of . . . RCTs to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. . . . the benefit that the RCT conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. . . . (in order) to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain’ [4]. Health services researchers, decision makers and practitioners are now faced with at least two challenges: how to respond to the limitations of current research and decision-making models that have taken us ‘just so far’; and how to integrate other sources of evidence into policy and practice in the real world [5]. What matters is making sense of what is relevant, i.e. how a particular intervention works in the dynamics of particular settings and contexts. It is not very useful to change a system based on deductive, in Cartwright’s words – average explanations. As Stengers [3] pointed out – the most useful questions addressing complex problems must imply an open situation: ‘What will the intervention be able to produce?’ and ‘What kind of behaviour will emerge? What are our frames of reference? What are our ideas and values in relation to success?’ In relation to policy development Glouberman, an applied philosopher adds: ‘Frameworks for understanding policy development do not merely describe the process. They invariably indicate what a “well-functioning” process is like. And so they place a value on certain structures and behaviour. As our theories change, so do our views of what is good’ [6]. Responses to the challenges to our contemporary frameworks are many and varied. They include the rise of translational research [7], narrative evidence-based medicine [8], the quest for utility in patient-reported outcome measures, together with new statements about trials and multifaceted interventions [9–12]. Acknowledging these challenges is not only a sign of understanding the crisis of scientific knowledge [13], but also evidence that new conversations have started [7,14,15]. Common to complex systems are two fundamental themes – the universal interconnectedness and interdependence of all phenomena, and the intrinsically dynamic nature of reality [16]. ‘At each level of complexity we encounter systems that are integrated, self-organizing wholes consisting of smaller parts and, at the same time, acting as parts of larger wholes’ [17]. Notable international examples of an emerging and evolving discourse about complex systems in health services research and quality improvement include the Institute of Medicine’s report ‘Crossing the Quality Chasm’ [18] with a resultant series of US quality initiatives, and Glouberman and Zimmerman’s report to the Romanow Commission in Canada [19]. Approaches to 1 A health system incorporates health services and broad social systems that influence human wellbeing and survival. 2 Health services are specific entities responsible for conducting activities to directly improve health. Examples include a doctor’s office, cancer care centres, emergency departments. Health services are subsystems of a broader health system. Journal of Evaluation in Clinical Practice ISSN 1356-1294

Health: A Personal Complex-Adaptive State

Defining health has been a long-term endeavour, each attempt taking a particular perspective that emphasises one aspect of the experience of health over others. It is notable that only the WHO definition mentions disease—the “enemy” that needs to be wiped out—as part of the health definition; all others emphasise personal aspects that result in the experience ofpersonal health(Table 15.1). The experience of health is essentially personal and has been equated to well-being and happiness. The dynamics between personal internal and external factors determine theexperience of health, be it good health or poor health, or be it in the presence or the absence of discrete diseases. People can report poor health in terms of illness or disease rather than their specific conditions (diseases).