Distortions, belief and sense making in complex adaptive systems for health

It should be clear that the many different problems facing health services reside in different knowledge domains and thus will require different strategies to synthesize practical knowledge for decision making. Different streams of knowledge flow across the different domains, yet they remain a part of the dynamic whole system. Moreover, many problems generally cannot be neatly separated into one or the other domain with specific issues and different questions requiring diverse approaches to knowledge generation and service implementation. Diversity, which has been long recognized as a key to successful evolution and adaptation in complex systems, is something to be fostered and valued. Looking at issues through different lenses can lead to the identification of gaps and distortions in our knowledge base. Moreover, information, ideas or evidence that inform particular knowledge systems are never ‘innocent’, without tacit and explicit assumptions 1. Greenberg draws our attention to the distortions that occur in our everyday knowledge generation within the scientific community, which can be analysed and made better sense of, by using social network analysis 2. His article provides an extended conceptual and methodological analysis to accompany his recent publication 3 using social network analysis demonstrating citation distortions regarding scientific claims. Published statements achieve higher levels of ‘believability’ when followed by citations. Yet, citations really only reflect the connections among authors' ideas and claims to existing literature, not ‘truth’. The scientific method has adopted the use of bibliometrics – rates of citation to publications of empirical research as the basis for scientific knowledge or ‘belief’. Citation metrics in health systems are used, not only to judge the success of publications, journals and individual careers, but through translational research to influence the well-being of recipients of clinical care. Emerging findings that citation distortion is taking place make it essential to not only question how we know what we believe, but have mechanisms that are scientifically valid to address flaws in our current belief systems. Greenberg's paper makes the case that social network analysis moves us from linear Newtonian principles to the application of non-linear scientific analysis that challenges many widely held beliefs. In contrast to network theory modelling that exposes flaws in our sense making in health, Glouberman 4 writes a philosophical paper that exposes a series of paradoxes and distortions in our thinking of birth and death, left in the wake of scientific progress. These ‘grey zones’ involve the processes of and timing of foetal viability and dying, during which it is not clear that irreversible death will occur or has occurred. Currently, we cannot universally identify the moment when foetuses become viable or the moment of death. Why is this? ‘We explain nature, humans we must understand,’ said Dilthey translated by Betanzos, a leading exponent of human science, which predates complexity science and theory. According to Dilthey, we can grasp the fullness of lived experience by reconstructing or reproducing the meanings of life's expressions found in the products of human effort, work and creativity 5. Glouberman articulates the case that more scientific knowledge does not and cannot address the human issue of ‘grey zones’. Increased survival in birth and death brought about by scientific endeavours will increase and complicate our human ability to address ethical and moral issues around ‘grey zones’. Decisions will have less to do with our science than with our values. Glouberman argues that richer understanding and acceptance of what it is to be human on an ongoing basis is required to humanize the processes of birthing and dying. Taking advantage of the achievements of science, we should have more time and freedom to explore our human qualities as individuals and as a society. In the second part of her work on primary health care (PHC), Felix-Bortolotti 6 conducts a theoretical analysis on ‘Primary Health Care Workforce Policy Intricacies with a Multidisciplinary Team Case Analysis’. This is an area that is popular in the health care literature with 1227 publications identified in Pub Med with 68% between 2000 and 2010. The implementation of multidisciplinary primary care (PC) or PHC11 PHC and PC are used interchangeably in the literature according to jurisdictional preferences, although historically the terms have different meanings. teams has been an endeavour of most Western governments over the past 10 years. Many research papers have been written, 385 reviews, 58 systematic reviews and 18 papers that included theory in any field. Five papers in the PHC and multidisciplinary team literature identified a theoretical framework; only two papers referred to complex adaptive systems theory and no papers included political economy in any field. Could there be a distortion in this literature? Could there be a citation distortion, based on beliefs and funding biases, as identified by Greenberg in this field? Could there be a lack of reference to understanding teams as humans seeking to work with other humans to achieve social effects, strongly influenced by the political economy of place and time? Has the implementation of primary care teams driven by reductionist static formulae addressed diverse individual and local needs? Should one dare to ask these questions? Building on the conceptual and empirical ramifications of PHC and PC and a theoretical framework for analysis of complex phenomenon, Bortolotti further examines the PHC/PC workforce policy issues and their consequences. She demonstrates how a theoretical framework for analysis can both challenge existing beliefs and actually guide policy in what superficially appears to be straightforward PHC human resources questions – for any given population. This can be achieved by understanding that these questions in reality pertain to very complex policy and systems issues. In the final paper of this forum 7, Boutellier and Zoller, both senior scientists and technologists make the case for a role of the general practitioner as a future intermediary between science and human concerns and values with their patients. This would entail addressing new successes and innovation, as well as distortions and gaps left in the wake of the progress of science and technology. Technological changes in information technology, dramatic successes in molecular biology and other rapid shifts in knowledge and communication will change medical services profoundly. General practitioners are well placed to act as intermediaries between patients, specialists and the research world. Without continuing education, general practitioners would rapidly lack the scientific information that requires humanizing for individual patients to enable them to make shared informed decisions about their care. The emphasis of Dilthey 5 in relation to his vision of human science was based on the ‘lived experience’, which is expressed by humans. Dilthey's formula was lived experience: the starting point and focus of human science; expression: the text or artefact as objectification of lived experience; and understanding: not a cognitive act but the moment when ‘life understands itself’. Many leading thinkers and researchers in complexity science see complex systems as being purely related to understanding by mathematical modelling. Others see mathematical dominance of complex systems understanding as a form of cultural imperialism 8. Nevertheless, there is a strong historical tradition of an alternative stream of complexity theory and social ‘science’ more closely aligned with the critical–hermeneutic rationality of the humanities and philosophy than with the more positivist rationality of empirical–analytical or behavioural cognitive science. Complexity science approaches, presented in this Forum ranging from social network analysis to hermeneutics, arguably provide a better way to map from the real world of ‘lived experience’ to the research model and analytics and back to ‘lived practice’. Complexity is the property of a real world system that is manifest in the inability of any particular formalism to be adequate to capture all its properties. It requires that we find distinctly different ways of interacting with systems. Distinctly different in the sense that when we make successful models, the formal systems needed to describe each distinct aspect are not derivable from each other 9, but together provide a gestalt of human knowledge and information. Moving beyond accepted wisdom is threatening to existing power structures, yet emergent knowledge from user-driven movements will increasingly disrupt beliefs and practices, even if the establishment is resistant to change. Complex systems science and theory thus aim to provide a broad framework, for not only questioning current frameworks and assumptions, but also implementing ways of analysis, sense making and practice 10, 11.

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