Systems Approaches in Public Health - News

Book Review: Unsimple Truths: Science, Complexity and Policy by Sandra Mitchell

Tue, 23 Jan 2018 22:24:00 +0000

Unsimple Truths: Science, Complexity and Policy by Sandra Mitchell
Chicago. University of Chicago Press Paperback $20.00 ISBN: 9780226006628 December 2012

In this book, Sandra Mitchell argues for the importance of understanding complexity when thinking about evidence in policy [1]. Her argument has far reaching consequences for evidence and policy in public health.

We are used to thinking about public health challenges as multi-level problems. Take depression: we know that some people have genes that make them more vulnerable to depression [2]. We also know that childhood experiences, unemployment, poor working conditions, low incomes, domestic violence, substance misuse, recessions and national welfare policies all play a role too [3].

The multi-layered nature of public health problems can lead to confusion if these different influences are seen as somehow competing with one another. Different disciplines have their favoured explanations: economists might see unhealthy lifestyles as evidence of different discounting rates; psychologists might see the same phenomena as evidence of cognitive biases or social norms; sociologists might see them as manifestations of structural influences. These differences include disagreements about what things can count as legitimate ‘causes’ of public health phenomena.

Mitchell argues that, while features at one level of analysis are the product of interacting units at a lower level, these features cannot be predicted from the properties of those individuals. Mitchell uses flocking starlings as an example. The intricate forms taken by a flock of starlings is the product of individual starlings following simple rules about proximity to others in the flock. But the fact that the individual’s behaviour is both influenced by and influences their neighbours means that it is not possible to predict the forms that the flock takes. Results from chaos theory suggest that in complex systems like these, no amount of knowledge about the behaviour and starting points of the individuals would ever be precise enough to predict the overall forms that the flock takes. Mitchell takes the argument further, pointing out that the system-level feature (the pattern of the flock as a whole) could influence the genes of the members of the flock, if it protects the individuals within it from predators.

To take a more public health example, no matter how detailed our knowledge of individual psychology (or genetics, or neuroscience), we cannot expect to accurately predict social patterns of health and illness. Social phenomena cannot be reduced to individual behaviour, and causation flows in both directions. The study of social phenomena complements, rather than competes with, behavioural or genetic explanations of patterns of health and illness.

While Mitchell’s argument may not convince from a pure scientific viewpoint, it has huge practical appeal for making decisions in the real world, with an absence of perfect information or evidence.

Mitchell argues that not all causal factors are equally amenable to experimental analysis. Some genes make a person more likely to get cancer if they are exposed to environmental risks factors but not otherwise [4]. So does the gene (or the environment) only ‘cause’ cancer in some circumstances? Mitchell points out that this idea of causation is quite different from the one we have inherited from physics, where forces like gravity and friction can be separated, and their effects estimated independently.

This has implications for the role of randomised controlled trials, which often aim to isolate the effects of an intervention from its context. Mitchell’s argument suggests that this may not be possible (or desirable) in a complex system like public health. It also suggests that, as Harry Rutter argued in a recent webinar on complex systems and public health, instead of focusing on getting the best possible sandbag, we should focus on building the whole wall.

Mitchell also argues that in systems made of many interacting causes, the effect of changing one factor might not be visible in the overall behaviour of the system. She points out that when genes associated with particular illnesses are inactivated in mice, for around a third of genes the animals appear completely normal. This can happen because the networks of genes involved adjust their activity to preserve the physiological function. This robustness can be seen in health inequalities, which are stubbornly resistant to change. Such stable features are unlikely to be the product of one or two causes: if they were, we might expect to have found and changed them by now.

Finally, Mitchell considers the implications of complexity for policy. She argues that these systems display uncertainties that cannot be quantified. This makes the familiar project of calculating expected outcomes of various policy options impossible. Instead of trying to predict the outcome of each policy option and picking the best, Mitchell argues that we should judge our policies by how well they are likely to achieve a minimum set of outcomes across a range of possible scenarios. And rather than identifying the ‘best’ policy and implementing it wholesale, we should take an incremental and iterative approaches to policy development using feedback to see what is actually happening as a result. This approach has been developed under the name Robust Adaptive Planning [5]. My own view is that this would require much more timely and fine-grained data on public health outcomes than is currently available.

Altogether, Mitchell’s short book is a valuable attempt to produce a philosophy of science that is relevant to current research practice in the biological and social sciences, as well as to the kinds of policy problems that confront decision makers in public health and broader public policy.

Steve Senior is a specialty registrar in public health in Greater Manchester. In previous lives he worked as a policy adviser for the UK Government, and completed a doctorate in neuroscience.

References

1. Mitchell SD. Unsimple Truths: Science, Complexity, and Policy. University of Chicago Press; 2009.

2. Levinson DF. The genetics of depression: a review. Biol Psychiatry. 2006;60: 84–92.

3. Dobson KS, Dozois DJA. Risk Factors in Depression. Elsevier; 2011.

Book Review: Agent Zero by Joshua Epstein

Tue, 14 Nov 2017 20:37:00 +0000

Agent Zero

Steve Senior is a specialty registrar in public health in Greater Manchester. In previous lives he worked as a policy adviser for the UK Government, and completed a doctorate in neuroscience. In this review he assesses the applicability of the insights in Joshua Epstein's Agent Zero to systems approaches.

In this book, Joshua Epstein sets out a simple but compelling framework that shows how simulated people (agents) following some basic rules can generate surprising social phenomena that are relevant to public health.

Agent_Zero is published by Princeton University Press. The preface and first chapter are available as a free download from the Princeton University Press website. The website also features all the code and models used in the book, so you can play with the model settings for yourself.

Epstein has argued that agent-based modelling represents a new model of ‘generative’ social science [1], in which theories about behaviour are embodied in agents, representing people (or sometimes organisations). These agents are allowed to interact freely in a computer simulation, following some basic rules. If the outcome of the system as a whole resembles the social phenomenon that you are interested in, then you can say that the rules are sufficient to explain the social phenomena. This contrasts with the usual epidemiological approach of studying patterns in the real world and using regression models to tease out the causal variables.

An early and well-known example of agent-based modelling is Thomas Schelling’s model of racial segregation [2]. Shelling’s model has agents of two colours that ‘live’ on a two-dimensional grid like a chess board that might represent a city. Schelling’s agents can move to empty squares if they are not ‘satisfied’. Agents are satisfied when a certain proportion of neighbouring agents are the same colour. Schelling’s model showed that even when agents are happy to be in the minority, the model can still generate segregation resembling the racial segregation in some cities.

Schelling’s model was designed to study a specific social phenomena. In Agent_Zero, Joshua Epstein offers a general framework for agent based modelling that is based on evidence from psychology and neuroscience. Epstein’s agents have three components: a cognitive component; an emotional component; and a social component. These components together are referred to as an agent’s ‘disposition’, and determine whether an agent carries out some action. Epstein bases his emotional component on psychological studies of fear conditioning. His cognitive component, although simple, reflects some of the better known cognitive biases [3]. These two added together make up an agent’s ‘solo disposition’ towards some action. To this, Epstein adds a weighted sum of the agent’s contact’s solo dispositions, reflecting a form of emotional contagion. Epstein’s agents move randomly around a two-dimensional grid. These squares change at random from benign to aversive, reflecting some adverse experience, and this informs the agents’ emotional and cognitive values.

Epstein’s central interpretation is about violence - his agents might represent peace-keeping soldiers moving around a terrain occupied by locals that may or may not be hostile. But there are numerous other interpretations throughout the book. One example that is relevant to public health is about vaccine refusal. In this interpretation, the yellow squares represent benign experiences with vaccines, and orange squares may represent adverse experiences (perhaps some diagnosis that coincides with vaccination).

One of Epstein’s early results is to show that an agent with no personal adverse experience can act (in our example, this would be someone with no personal reason to be concerned about a vaccine but who nevertheless refuses a vaccine). More surprising still, an agent that is more susceptible to emotional contagion than others (that is, puts more weight on its neighbours dispositions), but which has no adverse experience may even act before those with direct adverse experiences. Epstein suggests that history’s great leaders might just be those people who are most sensitive to others’ dispositions, rather than those with a distinct vision of the world.

Although very simple - most of the examples feature only three agents - Epstein shows that simple agents, if connected in a social network, can generate surprisingly social behaviour. His book makes a convincing case for the importance of psychology and behavioural science in public health, even in understanding apparently complex phenomena.

Overall, Epstein’s model provides a versatile framework that captures some important behavioural phenomena. Some of the specifics, such as the use of learned fear might not be as useful in a public health context. For example, we generally don’t have to learn much to like high calorie foods. Missing features from a public health perspective also include discounting - the way that we tend to undervalue costs and benefits in the future, leading to behaviours like smoking despite overwhelming negative consequences later. But the general approach of modelling competing cognitive components could be adapted to include these features.

A further criticism might be that some of Epstein’s results depend on specific values, such as the weights applied to other agents’ dispositions. These values don’t appear to have any particular basis in evidence. But these results suggest that the phenomena can at least in principle be generated by agents acting in a network.

For some, Epstein’s approach might feel too reductive. There is no room for culture and little for meaning in Epstein’s agents’ simplified world. But I think the point is that we should be cautious about appealing to higher-level concepts like culture to explain things like health inequalities if we can generate something that looks very similar using individual-level effects drawn from the psychological literature.

Personally, I found Agent Zero deeply satisfying. The approach of cognitively plausible agents acting in social networks seems to have a lot of potential for understanding complex problems in public health. Agent based models are under-used for non-communicable diseases [4]. I can imagine an approach drawing on the types of findings presented in Mullainathan and Sharfir’s ‘Scarcity’ [5], or some of the models by Daniel Nettle (who has argued that people who face many risks that they can’t control shouldn’t spend as much time or effort controlling the ones that they can [6]), to develop agent-based models of health inequalities.

Agent_Zero is a fairly technical book: Epstein uses mathematical formulae and formal logic in places. However it is not necessary to follow all the mathematical logic to get a lot from the book. The basic model is simple enough that it should be accessible to readers who are comfortable with regression models (and is considerably less complex than some health economic models).

References

1. Epstein JM. Agent-based computational models and generative social science. Complexity. 1999;4: 41–60.

2. Schelling TC. Dynamic models of segregation†. J Math Sociol. 1971;1: 143–186.

3. Tversky A, Kahneman D. Judgment under uncertainty: Heuristics and biases. Judgment under uncertainty. pp. 3–20.

4. Nianogo RA, Arah OA. Agent-based modeling of noncommunicable diseases: a systematic review. Am J Public Health. 2015;105: e20–31.

5. Mullainathan S, Shafir E. Scarcity: The New Science of Having Less and How It Defines Our Lives. Picador; 2014.

6. Nettle D. Why Are There Social Gradients in Preventative Health Behavior? A Perspective from Behavioral Ecology. PLoS One. Public Library of Science; 2010;5: e13371.

Systems 101: Practical reading

Mon, 06 Nov 2017 08:31:00 +0000

We've been posting some tools and reading. Various people have been asking for reading which is practical. The book on Applied Systems Thinking for Health Research is good, but perhaps more designed to researchers.

Some basic solid reads

So, a couple of basic solid reads? Well, here goes. I wouldn't start with books on systems theory alone. While nothing, ultimately, replaces doing some reading on systems theory it is a complex area and if, like me, you weren't or aren't sure where to go, you can do wrong.

If like most busy people you only read one book on systems

My best advice here is read widely, because unfortunately there is no really good book on practice yet. But a good and useful guide if like most busy people you only have time for one, is Adulrahman et al's Systems Science and Population Health. It tries to bridge systems science and public health science but while it is still methodological in focus it does give some good applications from the literature.

The first section, “Simplicity, Complexity, and Population Health” is probably the best part for practitioners, with a quick boot camp on systems science and links.

The third section, “Systems Science Toward a Consequential Population Health,” is an attempt to synthesize what we know in the emerging field of systems and public health approaches. We still have some way to go!

Moving into practice: must reads

Another good read is a series of very thought provoking papers online at https://medium.com/disruptive-design . From tools for thinking to how to lead, this is a great resource to help you get your head round how you start applying and journeying into doing, thinking and applying systems theory and insights, and integrate it with what else you know and find useful.

Systems 101: Network Analysis for the scared and uninitiated

Fri, 03 Nov 2017 09:29:00 +0000

One of the basis tools of using systems approaches is doing network analysis. This is the kind of thing where you produce diagrams that show relationships, influences or connections.

The Social Network diagram from Hell

The classic diagram here, and actually the wrong one to start with, is the Government's Foresight network diagram on Obesity, reproduced below.

Why do I say this is the wrong diagram to start with? There are many good things about this diagram. Not least it is an attempt to be comprehensive. Well, first it's so complex it may well prevent you taking action rather than starting it. Second, this diagram is clearly the result of repeated refinement and improvement, so it's a more or less end product not a starting one, and a key thing about network diagrams is you need to live with them as they grow and refine in order to understand them. If you haven't "grown up with" this diagram, you can hardly expect it to fill you with joy. Third, it's only one type of diagram, and there are many.

So, where do you start with social network analysis if you don't have much time and money? Well here are my top tips of things that reward an hour's reading, and then encourage you to have a go.

The best starting quick guide

The International rescue committee produced a short handbook on this. Read this first. Its short and succinct. https://www.rescue.org/sites/default/files/document/1263/socialnetworkanalysise-handbook.pdf

Starting Network Analysis - some easy tools

My suggested two best starting places are the Home Office free how to guide on social network analysis produced in 2016 which can be found here https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/491572/socnet_howto.pdf

Pair this with watching this video

https://www.youtube.com/watch?v=PT99WF1VEws

This is a really good read

https://academic.oup.com/heapol/article/27/5/438/752411/How-to-do-or-not-to-do-a-social-network-analysis

And finally, this is a useful overview too

https://www.slideshare.net/JeromyAnglim/how-to-conduct-a-social-network-analysis-a-tool-for-empowering-teams-and-work-groups

A revision tool

I find this a useful revision tool or a handy how to reminder to keep with me

https://cphss.wustl.edu/Products/ProductsDocuments/Carothers_2014_NAStartToFinishFinal.pdf

Using Excel

Some folk buy specific programmes or use R for Network ANalysis. But actually pen and paper or Excel for many purposes works for me. A good video on using excel can be found here https://www.youtube.com/watch?v=P33xa4l4GTM

Buying books

For really good books it's hard to beat John Scott's Handbook of Social Network Analysis here https://uk.sagepub.com/en-gb/eur/social-network-analysis/book249668 . But unless you're going to do lots and lots of this, you probably won't need it.

Tips for Systems Working in Service Transformation

Thu, 02 Nov 2017 19:18:00 +0000

Earlier this year I had the privilege of participating in two sessions at the Public Health England 2017 Conference. I took part in a Behavioural Sciences in public health session and in a Public Mental Health session. At both sessions the discussion, comments and questions from the audience were stimulating and deeply thoughtful. In the public mental health session I came face to face with the strong realisation that I was in a – packed – room full of people all of whom were thinking about systems approaches. I even asked if that was what we were doing and got enthusiastic nods and responses. What an experience! Seriously, it was brilliant.

Anyway, lots of conversations ensued afterwards with people asking about systems. Now I have blogged before about whole systems approaches to mental health and about some of the leadership issues in leading across systems, and some of the problem solving approaches public health can use in a systems world. You can’t do systems work on your own. And you need to be structured, purposeful but also opportunistic. We should, as Public Health types, find a natural bent to this.

Top tips for system working

For me the key thing about a system is that every system is perfectly designed to produce what it produces. So if it’s dysfunctional, in what it produces, you are going to have to disrupt it. And that takes planning, effort, and a coalition

This is an art not a science, so my top tips for systems working start with doing some reading on systems and then work with people who like working on system change. Some resources you could use for systems thinking are:

There is also an online course in Systems Thinking for Public Health from Johns Hopkins. This will give you one take on systems thinking, because there are several takes on this concept.

The thing about a system is that systems science is not a complete explanation

Recognise though, that systems approaches often come from an engineering or management paradigm (many business schools grew out of engineering schools historically) that see systems as machines. I think some of that is true, but for the most part systems are made up of humans so there are ALWAYS complex social processes and cultural issues at heart, and they explain behaviour of the system and the people AT LEAST as much as the processes in that system. So, if you don’t understand a system at least in part as a complex set of social processes, you are doomed to fail. So go beyond systems science before you go rushing in, because systems are actually not machines but complex social networks and processes.

Understanding complex social processes

You could do a lot worse that do some reading on changing cultures and complex social processes. My top reads would be:

Wiggins & Hunter. (2016). Relational Change: The Art and Practice of Changing Organizations. Bloomsbury
Shaw (2002). Changing Conversations in Organizations: a complexity approach to change. Routledge.
Ralph Stacey (2012) Tools and Techniques of Leadership and Management. Routledge
Social Network Approaches to Leadership

A first key step is to try to understand the system, map it, understand it. Conceptualise it somehow. Then it’s vital to recognise that the system is made up of complex social processes, and you need to understand those to intervene, and you need to intervene in multiple places and do so purposively. Sometimes you just need to be opportunistic.

To intervene, you often need to disrupt the system, and that means getting a bunch of people to join you. Set some sensible system goals so you know how you’ll get there and when. Start somewhere, more or less anywhere, and start where you think you might get most output. No, it’s not scientific in a positivistic way. Most systems don’t work and can’t be understood like that anyway.

Changing systems is a journey, expect it to take time.

Understand the failure points

We need to understand the lessons of failure of transformation. One of the best papers I ever read is John Kotter’s “Leading Change: Why Transformation Efforts Fail” listed above. Kotter talks about eight steps to transforming an organisation, and if you don’t do these, they are very strong predictors of failure.

I seriously recommend getting hold of this paper. It was published in the Harvard Business Review, originally January 1995 then reprinted in 2007 in BEST OF HBR. This paper is so popular online that HBR doesn’t let you download or print it. I tracked down a paper copy through the British Library which is now much dog-eared and annotated. But it’s been worth every penny for me. If you only ever read one paper on transformation, read this.

Kotter gives eight golden rules of what you need to do for successful transformation. For me, these have been an excellent guide to any successful change exercise I have ever done. Not doing these are the eight reasons why transformations fail . These eight reasons are:

Establishing a sense of urgency – you must identify potential crises and opportunities
Form a powerful guiding coalition with enough power to lead change efforts and get them working together well
Create a vision and develop strategies to achieve it
Communicate the vision using every vehicle you can, use your guiding coalition to model the behaviours you want in the new world
Empower others to act – get rid of obstacles and change this that undermine your vision
Plan for , create and welcome Short-Term Wins and CELEBRATE them! They are important milestones on the journey for morale, convincing people you can do it and get there and checking you’re still heading for target
Consolidate your improvements and keep reinvigorating them. Do not declare victory too soon!
Embed the new approaches and make sure people “get” the connections between them and success

This is not an exact science. But it is a combined exercise in conceptualising, designing interventions, problem solving and leading which will stretch, challenge, dismay and reward.

Book Review: Applied Systems Thinking for Health Systems Research: A Methodological Handbook

Wed, 01 Nov 2017 20:45:00 +0000

Don de Savigny and colleagues published this book, with McGrawHill, in mid October 2017. http://www.mheducation.co.uk/9780335261321-emea-applied-systems-thinking-for-health-systems-research-a-methodological-handbook

While written for and aimed at a research audience, especially those who want to research systems, this book has much to offer public health professionals who want to understand how they can get their heads round and apply systems approaches.

The chapters provide an introduction to a range of systems issues and provide the lens of a research project or application for each tool.

A useful handbook. For my money, the first chapter on how to use it could have been a bit more user friendly, but as a way of moving from understanding systems theory to apply it, this is a good and useful read.

Health Foundation Webinar on Complexity and Complex Systems Approach in local Public Health

Wed, 01 Nov 2017 20:41:00 +0000

The Health Foundation will be running a webinar on 2nd November, for which registration is free, here http://www.health.org.uk/events/webinar-complex-public-health-challenges-and-local-action-how-does-local-government-tackle

In 2017 local authorities find themselves challenged by a variety of persistent and stubborn public health problems such as obesity, air pollution and alcohol-related harm. All take place within complex systems, with multiple factors operating over many decades in contexts that adapt and change over time.

This webinar explores why we need to think about these public health challenges in terms of complex systems and therefore use different evidence and develop new, more effective approaches to tackling them. We will bring together practice and research perspectives to discuss how we use this thinking to design and evaluate population-level interventions differently to improve health.

This webinar will give those working in public health and local government the chance to:

hear the latest thinking about how to approach population-level interventions to improve public health in local areas
improve their understanding of complex systems approaches and build practical applications of that knowledge
interact with the presenters by asking questions and discussing different approaches.

Speakers

Dr Harry Rutter, Senior Clinical Research Fellow at London School of Hygiene and Tropical Medicine
Jim McManus, Director of Public Health, Hertfordshire County Council
Jane Landon, Strategy Advisor, The Health Foundation

Complex Public Health Problems

Tue, 03 Oct 2017 21:46:00 +0000

On 2nd November 2017 the Health Foundation will be hosting a webinar on how local government tackles complex public health challenges.

This webinar provides an opportunity to share perspectives and approaches. The webinar is free and you can find more information here

http://www.health.org.uk/events/webinar-complex-public-health-challenges-and-local-action-how-does-local-government-tackle

Tactics for systems working: improving health through contracts

Tue, 26 Sep 2017 20:10:00 +0000

Grasping Every Opportunity to Improve Health through Contracts

The move of public health from the NHS into Local Authorities in 2013 offered many advantages and some disadvantages - which have been discussed at length elsewhere (for example see http://www.publichealthjrnl.com/#/article/S0033-3506(15)00288-7/fulltext …). But the opportunity to influence systems we couldn't while in the NHS has, for me, been one of them.

One difficult but essential journey that we have taken locally is the move away from the individualised commissioning associated with our PCT days to a greater priority being placed on tackling the wider determinants and using emerging whole systems approaches. This is challenging and sometimes you want to go back to the individual commissioning days.

But, to use my own catchphrase, "you can't commission your way out of (insert public health topic)". As our reach and interests extend further and further throughout Local Government, more and more opportunities present themselves for use to improve health, often at the last minute. Whilst these may be small opportunities, they fit within a wider systems approach and must be capitalised on. For us they've been a good way of getting our heads around systems working.

One such opportunity that is often flung across my desk (or inbox) is to add public health into random Local Authority contracts. I expand on three of these below but there are many more - what I want to do here is start a conversation where these opportunities are shared and discussed allowing for resources and templates to be created so that we can all ask the question of colleagues and be ready with the answers to their responses.

Three Examples of public health into contracts

First, Bus shelter advertising. I was challenged by a national leader at PHE to look into this in my Local Authority with a view to seeing what is currently restricted (turns out that it's tobacco, politics and religion) and what else could be added to this list in the future (and when). What I found was that the advertising is wrapped up in the long term contract for the provision of the actual bus shelters and that a new contract was due out to tender soon.

After a bit of fieldwork, a proposal to limit the advertising of food high in fat/salt/sugar and alcohol was proposed - it was a difficult balance to ensure that this would not affect the financial viability of the contract. In the end for other bigger reasons, the current contract was extended to 2020 but at least we've made a start with that one. But what about your bus stop contracts? Can you ask the question - and what are you asking for? Let's discuss.

Second, School catering - all of the provision in my area is external, with schools tendering these themselves. What support and advice can we provide here? Clearly, we want the nutritional side to be maintained even by Academies but what other added niceties could we suggest? How about the achievement of the Food for Life award? Or something around choice architecture (nudge)?

Third, what about getting workplace health into all Local Authority contracts? This is easier for us locally as we have the North East Better Health at Work award so where appropriate we've stuck this in all new contracts (including, for example, into all of the new and renewed care home contracts).

These are just three examples but the mindset to intervene in various places across systems is something we find we're getting value from. There will be many more that I am completely unaware of.

So the ask here is to share your most random opportunities to improve health so that we can learn and take action together

Scott Lloyd is a Health Improvement Specialist with Redcar and Cleveland Council, and a member of the Public Health Advisory Board of the National Institute of Health Research.

https://www.researchgate.net/profile/Scott_Lloyd2 @ScottyLloyd1979

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John Hopkins Course in Systems Approaches for Public Health

Sun, 17 Sep 2017 12:30:00 +0000

Johns Hopkins University has created an online course, costing less than £50, on Systems Approaches in Public Health through courser starting on 18th September

The course provides an introduction to systems thinking and systems models in public health.

The course information states "Problems in public health and health policy tend to be complex with many actors, institutions and risk factors involved. If an outcome depends on many interacting and adaptive parts and actors the outcome cannot be analyzed or predicted with traditional statistical methods. Systems thinking is a core skill in public health and helps health policymakers build programs and policies that are aware of and prepared for unintended consequences. An important part of systems thinking is the practice to integrate multiple perspectives and synthesize them into a framework or model that can describe and predict the various ways in which a system might react to policy change. Systems thinking and systems models devise strategies to account for real world complexities. This work was coordinated by the Alliance for Health Policy and Systems Research, the World Health Organization, with the aid of a grant from the International Development Research Centre, Ottawa, Canada. Additional support was provided by the Department for International Development (DFID) through a grant (PO5467) to Future Health Systems research consortium. "

This course is one of the first on this topic, and if the discussions which reach the ears of our editorial group are anything to go by, several other institutions are thinking about this.

This piece was carried free of charge by Systems Approaches in Public Health . We accept no liability for content, provision or agreements entered into by any reader to any site external to Systems Approaches in Public Health