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Is General System Mode A Good Approach For Health Service Administration

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The application of systems thinking in health: why use systems thinking?

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Abstract

This paper explores the question of what systems thinking adds to the field of global wellness. Observing that elements of systems thinking are already common in public wellness research, the article discusses which of the large trunk of theories, methods, and tools associated with systems thinking are more than useful. The newspaper reviews the origins of systems thinking, describing a range of the theories, methods, and tools. A common thread is the idea that the behavior of systems is governed past common principles that can be discovered and expressed. They each address problems of complexity, which is a frequent claiming in global health. The different methods and tools are suited to different types of enquiry and involve both qualitative and quantitative techniques. The paper concludes by emphasizing that explicit models used in systems thinking provide new opportunities to sympathise and continuously test and revise our agreement of the nature of things, including how to intervene to amend people's health.

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Background

In the speedily changing field of global health, it is hard to know whether the contempo attending to systems thinking is just some other fad, or something more durable that offers usable insights for agreement and action. Some encounter systems thinking equally providing a powerful language to communicate and investigate complex issues, while others are confused by the sizable and baggy body of theories, methods, and tools involved. Time volition tell, of form, but in the meantime, information technology is helpful to consider why nosotros would utilise systems thinking in a field that already draws upon a rich collection of theories, methods, and tools from the health sciences, social sciences, engineering, mathematics, and other disciplines.

From mental models to explicit ones

At its cadre, systems thinking is an enterprise aimed at seeing how things are continued to each other within some notion of a whole entity. We often make connections when conducting and interpreting research, or in our professional do when we make an intervention with an expectation of a consequence. Anytime we talk most how some event will plow out, whether the event is an epidemic, a war, or other social, biological, or physical process, we are invoking some mental model well-nigh how things fit together. However, rather than relying on implicit models, with hidden assumptions and no clear link to data, systems thinking deploys explicit models, with assumptions laid out that can exist calibrated to data and repeated by others. The word system is derived from the Greek sunistánai, pregnant "to cause to stand together." If we consider that a organisation is a perceived whole, made up of parts that interact toward a mutual purpose, we recognize that the ability to perceive, and the quality of that perception, is also function of what causes a system to stand together. Systems thinking is intended to improve the quality of those perceptions of the whole, its parts, and the interactions inside and between levels.

Every interpretation of a research result involves a model, whether information technology is a physical model used for experimentation, a statistical model used to estimate the relationships between variables, or a conceptual model nigh how elements are connected. A model is but a way nosotros compactly represent and understand an object, phenomenon, or organisation. Equally much every bit research involves observation and experimentation, I would fence that skillful enquiry is also about building and using explicit models rather than implicit ones. The existent question is non whether we should be using systems thinking, as broadly described hither, but rather, which of the many theories, methods, and tools currently associated with the field of systems thinking are most useful in particular settings.

For example, where private people collaborate directly with i another (eastward.k., transmitting illness) while moving about in an explicit space such equally a city, amanuensis-based modeling [1, ii] may be especially powerful. In modeling how different agencies within a large public health system interact, social network theory [3] could be more directly relevant.

Origins

Systems thinking has largely adult as a field of research and practice in the 20th century, and has multiple origins in disciplines as varied as biology, anthropology, physics, psychology, mathematics, management, and information science. The term is associated with a broad diversity of scientists, including the biologist Ludwig von Bertalanffy who developed Full general System Theory; psychiatrist Ross Ashby and anthropologist Gregory Bateson who pioneered the field of cybernetics; Jay Forrester, a estimator engineer who launched the field of systems dynamics; scientists at the Santa Fe Institute, such as Noble Laureates Murray Gell-Isle of mann and Kenneth Arrow, who accept helped define circuitous adaptive systems [4]; and a broad variety of management thinkers, including Russell Ackoff, a pioneer in operations enquiry, and Peter Senge, who has popularized the learning organization. Much of the work in systems thinking has involved bringing together scientists from many disciplinary traditions, in many cases allowing them to transfer methods from ane discipline to another (inter-disciplinarity), or to work across and between disciplinary boundaries, creating learning through a wide multifariousness of stakeholders, including researchers and those affected past the research (trans-disciplinarity).

Theories, methods, and tools

If there is a jungle of terminology used to depict scientific attempt, information technology gets even thicker in the area of systems thinking, maybe because of its various heritage. Given the varied disciplines and trans-disciplinary traditions involved, it is easy to see why people often talk about broader "approaches", "perspectives", or "lenses" when applying systems thinking. Systems thinking models and frameworks are sometimes 1000 and widely applicable, such as General System Theory, and at other times very specifically applied to item phenomena, such as the theory on disquisitional points in physics, which is used to explain the bespeak at which a material behaves as neither liquid or gas (or solid). Systems thinking tin can involve a broad range of theories, which are rational sets of ideas or principles intended to explain something. It is based on a wide diversity of scientific methods used to investigate phenomena and acquire knowledge. Information technology uses an fifty-fifty larger array of instruments or tools – the hardware and software used to conduct experiments, brand observations, or collect and analyze data. The employ of these terms is not consistent across or within scientific fields, including systems sciences, and the continuum from tool to method to theory and framework is often blurry.

Rather than attempt to sort out semantic nuances between these terms, the utility of systems thinking can be ameliorate appreciated by a cursory expect at some of its more commonly used theories, methods, and tools (Table 1). The theories and methods in systems thinking are each designed to address complex bug. They are circuitous because they involve multiple interacting agents, the context in which they operate keeps changing, because the mode in which things change do not arrange to linear or simple patterns, or considering elements inside the system are able to learn new things, sometimes creating new patterns equally they interact over time. Many of the challenges in global health are now recognized as complex issues where simple blueprint approaches have limited success [five, 6].

Table 1 Systems thinking theories, methods, and tools

Full size table

Systems thinking tools have a wide multifariousness of applications. Some tools are intended equally ways of facilitating groups of people to have a common understanding nigh an issue to prompt further inquiry and activity. For case, "systems archetypes" help teams to empathize generic patterns of interaction that tin be applicable to their "story" [24]. Rather than utilise the pre-existing templates of systems archetypes, causal loop diagrams (CLD) are created without a template, and involve drawing out people's understanding of how elements of a problem are related to each other [19]. They usually begin every bit qualitative descriptions outlining how one thing causes another in either a positive or negative direction. Typically, feedback loops are identified between the different elements. They can be reinforcing or positive feedback loops, where A produces more B which in turn produces more than A, such equally the barbarous wheel of nether-diet and infection. They can also exist balancing or negative feedback loops, where a positive change in one leads to a push back in the contrary management, such as when increasing torso temperature produces sweating, which in turn cools down the body. In this supplement, a number of studies use CLDs that depict relationships between different elements of a health system to explain phenomena such as dual do of health workers in Republic of uganda [25], provider payment systems in Ghana [26], and childhood vaccination coverage in Republic of india [27].

The elements of a CLD might also be converted into a quantitative systems dynamics model by classifying the elements every bit "stocks", "flows", or "auxiliary" variables, and using equations to describe the relationships between private variables in 1 of many available systems dynamics software environments. In this supplement, Rwashana and colleagues use systems dynamics models to examine neonatal mortality in Uganda [28], while other authors utilise systems dynamics models to examine the furnishings of policy interventions [29].

There are number of other tools that are used to map out events or how things are connected. Network mapping, social network analyses, and procedure mapping involve a range of tools to illustrate and analyze connections between people, organizations, or processes in both qualitative and quantitative ways. In this supplement, Malik et al. map out the network of actors involved in physician's seeking advice in Pakistan [30]. The menstruum chart is one of the more than common tools used to draw a process or a system. Innovation history (or change direction history) is used to compile a history of central events, outcomes, bug that have cropped upwardly forth the manner, and measures taken to address problems. In this supplement, Zhang et al. [31] look dorsum over the last 35 years of the development of the medical system in rural People's republic of china. Participatory Impact Pathways Analysis involves workshops and a combination of tools to clarify the logic of interventions and a mapping of the network [21]. It is intended to enhance agreement through participation with beneficiaries, implementers, and other stakeholders in a projection. Several papers in this supplement utilise like approaches for a variety of situations, including to build leadership capacity for health systems in South Africa [32], to develop sustainable physical rehabilitation programs in Nepal and Somaliland [33], and to build sustainable maternal and child preventive health services in Northern Bangladesh [34].

Agent based modeling takes advantage of a wide multifariousness of theories, methods, and tools to build computer models that simulate the interaction of agents (east.yard., individuals or organizations) to run across how existent earth phenomena "grow" and affect the organisation as a whole. The models involve multiple individual agents that piece of work at dissimilar scales, some decision-making rules (e.g., uncomplicated rules on how they reproduce, interact with others or pursue objectives), processes for adaptation, and a space in which the agents operate.

In global health, we are concerned with both theory and practice, and are in demand of models that lucifer the complex conditions in which we work. A common thread of all these theories, methods, and tools is the thought that the behavior of systems is governed past common principles that can be discovered and expressed. They are all helpful in trying to conceptualize the systems in place. Some are more focused on means to change the system to produce ameliorate outcomes. In using these theories, methods, and tools, we are reminded past the statistician George EP Box that "all models are wrong, simply some are useful" [35]. It is to these uses that we at present turn.

In much of public health and medicine, we employ research evidence on the efficacy of interventions to inform decisions with an expectation about their time to come effect. Some systems thinking methods and tools, such as scenario planning, can too be used to explicitly forecast futurity events. However, even and so, such methods are intended to be used for identifying possible outcomes to provide insights on how to prepare for them rather than fixing on whatsoever particular outcome.

In his landmark address on "Why Model?", which provided inspiration for this essay, Joshua Epstein identified sixteen reasons other than prediction on why to model [36]. Most of these reasons are applicable to systems thinking more broadly. Many of these specific reasons relate to being able to explain how things work, and systems thinking is particularly useful to explaining how circuitous systems work. Many of models can be used for testing the viability of policy interventions in a condom and inexpensive way – agent based models, systems dynamics models, and scenario planning are particularly useful for these purposes. In this periodical supplement, for example, Bishai et al. nowadays a very simple systems dynamics model to illustrate the trade-offs and unintended consequences of policy choices related to allotment to preventive and curative services [29].

Systems thinking approaches tin also provide guidance on where to collect more data, or to raise new questions and hypotheses. The methods and tools assist usa to make explicit our assumptions, identify and exam hypotheses, and calibrate our models against existent data. One of the frustrations of health planners and researchers has been the aspiration that interventions shown to be effective at pocket-sized scale or in a research setting cannot be simply replicated at large calibration or to achieve populations that are most vulnerable. Systems thinking methods and tools are increasingly being used to explicate epidemics and to inform programmatic expansion efforts [five, 6].

One of the more compelling reasons to employ systems thinking approaches is to inspire a scientific habit of mind. Beyond the contributions of any detail theory, method, or tool, the practice of systems thinking tin can reinforce what Epstein calls a "militant ignorance", or delivery to the principle that "I don't know" equally a basis for expanding scientific cognition. Systems thinking adds to the theories methods and tools nosotros otherwise utilize in global health, and provides new opportunities to empathize and continuously test and revise our understanding of the nature of things, including how to intervene to improve people's health. And for those who value thinking and doing in global wellness, that can simply be a good matter.

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Acknowledgements

This Commentary is part of the Thematic Series entitled: "Advancing the application of systems thinking in health". The Series was coordinated by the Alliance for Wellness Policy and Systems inquiry, Globe Health Arrangement with the assist of a grant from the International Development Research Centre, Ottawa, Canada. The author also gratefully acknowledges support from the Future Health Systems Research Programme Consortium through a grant provided from the Department for International Development (United Kingdom). I too appreciate the comments received from Josh Epstein.

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Correspondence to David H Peters.

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Peters, D.H. The application of systems thinking in wellness: why apply systems thinking?. Wellness Res Policy Sys 12, 51 (2014). https://doi.org/10.1186/1478-4505-12-51

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Keywords

  • Complex adaptive systems
  • Complexity
  • Methods
  • Systems thinking
  • Theory
  • Tools

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