This is part 2 of a blog series based on a Health Foundation seminar.
Part 2 tries to describe actions to take & responses to complex problems
thanks to John Soady for some excellent thoughts, in the below, and to Harry Rutter for a lot of inspiration.
1. Getting started. Chapman suggests five key questions that will help engage with a system approach
1. How would my perspective change if I regarded this organisation/agency/department as a complex adaptive system?
2. What approach would I adopt if I accepted that this system cannot be controlled nor its behaviour predicted?
3. What other perspectives are there on this issue and how can I understand them?
4. How can I learn what is most effective here? How would I know?
5. What relationships are key in moving forward and how can I nurture them?
All worth asking and reflecting on as you ponder the problem and a response
2. What would an alternative complexity informed framework look like. 20 generic suggestions & ingredients for systems practice (Cairney, Chapman, Rutter)
- Define your starting point and vision. What’s wrong, what needs to change.
- provide a minimum specification that creates an environment in which innovative, complex behaviours can emerge.
- Clearly establish the direction of change. Maybe don’t worry if you can’t yet articulate the mechanism to change. Get your narrative straight.
- Develop wider logic models. Mapping systems is a gateway drug to getting into this space.
- Take a wider feeds of “what works”. Tricky one this,see my other blogs on evidence in public health
- Set boundaries that cannot be crossed by any implementation strategy
- Consider the merit of both short term v long term actions for the system as a whole rather than specific interventions in discrete parts of a system. What is it that you REALLY want to achieve. Be very clear on what metrics are
- Interventions would introduce learning processes rather than specifying outcomes or targets.
- Consider the competencies, capacity, motivations of all the actors in the system. Do you have what you need to achieve the desired goal.
- What about externalities– the side effects of actions of some actors in the system. How are they counteracted or addressed.
- Ensure learning was along the way, rapid feedback loops, get started, do something, adapt along the way, don’t be afraid of getting it wrong. Ensure you have a process for obtaining feedback about the effects of initial interventions and using this to make modifications as appropriate. A key part of the evaluation and reflection process will involve the selection of successful approaches and, equally importantly, the demise of those that have not succeeded.
- Little efforts in discreet places, with active evaluation and consideration to scale up.
- Don’t think binary, but steps along the way. What is the momentum that we need to build.
- Complex systems are particularly sensitive to initial conditions which produce a long-term momentum or ‘path dependence’.
- adopt an increased tolerance of failure, continuous feedback on effectiveness and a willingness to foster diversity and innovation.
- emphasise improving general system effectiveness, as judged by the clients or users of the system. What you think will work at the start just won play out.
- Go upstream at every and all opportunities. Upstream in terms of age and types of interventions delivered.
- Base your approach on learning what works & improving system performance, rather than control & specifying specific discreet interventions targets to be met. Base the approach on co design and listening to service users and agencies that deliver services. responsibility for innovation and improvement would be widely distributed across the whole network.
- Allocate resources, but without specifying how they should be used; these should include statements of timescale and potential further funding
Braithwaite sets out a number of ideas for different intervention
The key table – Twenty complexity oriented enablers and insights – gives some excellent solutions.
Initiatives to change the system’s hardware
Financial models and targets
Enhancing organisational and workplace culture
Implementation science and improvement studies
problems on adopting & sustaining change in this context.
1. implementing and securing acceptance of new solutions is difficult, even when armed with persuasive evidence—the take-up problem. Frontline staff in complex adaptive systems accept new ideas based on their own logic.
2. disseminating knowledge of an intervention’s benefits across the entire system is hard—this is the diffusion problem.
4. even if a new model of service, technology, or practice is successfully taken up and widely spread, its shelf life will be short—this is the sustainability problem.
six principles on which a new approach to change might be built.
1. pay much more attention to how services are delivered at the coalface
2. all meaningful improvement is local, centred on natural networks of service deliverers and users or citizens
3. acknowledge that staff doing complex everyday work get things right far more than they get them wrong. We focus on the 10% of adverse events while mostly overlooking the 90% of excellent delivery.
4. build on success, its everywhere. 4 common factors: 1) begin with small scale initiatives & build up; 2) convert data and information into intelligence & give this openly to the appropriate decision makers; 3) the lone hero model does not work and that collaboration underpins all productive change; 4) always start with the user or citizens at the centre of any reform measure.
5. be more humble in aspirations. Putting the myth of inevitable progress aside, we should recognise that big, at-scale interventions some times have little or no effects and that small initiative can sometime yield unanticipated outcomes
6. Most importantly, adopt a new mental model that appreciates the complexity of care systems and understands that change is always unpredictable, hard won, takes time, & it is often tortuous, & always needs to be tailored to the setting.
3. Get a very broad logic model and system map.
See Friel Using systems science to understand the determinants of inequities in healthy eating – An instruction manual on creating a system map – AKA Foresight Obesity with an inequality twist
4. Don’t assume linearity – The complex adaptive system issue
We like to think in linear terms. Do A – it leads to B – then C happens.
A- B link in context of sugar tax is simply about price elasticity of demand. The evidence here is really easy and well documented. But there are intended and unintended impacts outside the causal chain, and things we can’t measure and factor in.
Penny Haw – “Think about interventions as events within a system, not as discrete definable things – hammers that you apply to a nail”. Move away from linear cause and effect but events within systems
5. Deal with the Visibility problem – “but there’s nothing going on.”
There is a strong tendency to over simplify because
1) we need something visible and emblematic
2) got to start somewhere
3) we are well versed in reductionism. Hard to unlearn some of the approaches we have been steeped in.
Remember the Mindset of 20 year vision, 5 year strategy, 1 year plan. In a chess context, what is the end game we are trying to get to. Yes of course focus on a day to day plan but don’t loose focus on bigger vision. The System map = bigger picture of longer term.
6. Broad and narrow both matter.
We expect a marginally effective intervention (say the diabetes prevention programme – optimally delivered, it often isn’t) to small numbers of individuals to have an impact on population prevalence of diabetes. It won’t.
Narrow spectrum interventions do matter, but the total system really matters a lot more. It’s so much more important to think of the system as opposed to the singular intervention outside of the context of a system.
7. What can you do about the national framework that governs how the system works
It’s critically important.
The “rules” are set, this also significantly influences the debate and the architecture and the background narrative
How resources are allocated, by what rules
How the various sets of actors think, and are trained. What motivates them to act.
What ideologies prevail.
Even if you can’t control national, influence it, and you probably DO have local control and should assert that. Bend or break the rules. Seek to change the rules
Think through the rate limiting steps and the tectonic plates stopping or enabling change. This is a very useful read – The Water of Systems Change – aims to clarify what it means to shift the conditions holding problems in place and provides an actionable model for those interested in creating systems change
Thanks to Mike Fitter from @cohesionsheff for the tip off on this one
8. Hierarchy / command & control approach to managing or complex system
Command and control vs system focused on complexity and complex problems. We can’t solve the problem by command and control.
set broad framework, build in adaptability and regular review points
Don’t try to work out every aspect up front. The System will adapt. Set system on right trajectory
Consider “in control” vs “in charge”
Set out what broadly needs to happen
•#1 — “Efficiency” is dead as the decisive advantage– “complexity” has arrived. (Frederick Taylor was great, for the problems of yesteryear; but now, things have changed…).
•#2 — The rhythm of regular meetings is essential – across “silos” and groups. But, where there is no genuine urgency, these meetings can become dreaded, and not all that productive. In the midst of genuine urgency, the meetings are welcomed as “survival” tools.
•#3 — Changing the physical work-space is essential to the kind of communication needed for an agile, adaptable, team- of-teams.
•#4 — There is no permanent fix…
•#5 — Here’s a question – how do you plan in this shape-shifting environment? (“Nobody knows anything”).
•#6 — Be brutal about discovering your LIMFACs (“limiting factors”).
9. Commissioning in this context
See Collaborate and Newcastle University Business School A Whole New World — Funding and Commissioning in Complexity. This is an excellent guide to commissioning in this space. Key messages from a presentation I saw
• People are complex
• Issues are complex
• Systems are complex
• = embrace complexity, because life is complex
The results in complex systems are emergent. Complex systems are not under our control
Systems create outcomes
Complex systems cannot be controlled –let go of the illusion of control
How can our systems work better, from the perspective of the people who need them?
Even if you downy have power to move £, or it is ethically or politically unacceptable to do so, ensure you set the right culture.
Don’t sweat hard about what might be impossible to control, or take a giant infrastructure to do so. But do sweat the ability of humans to know other humans
Complexity-friendly funding/commissioning is based on a different attitude to:
• Motivation – is intrinsic, not extrinsic
• Learning – drives improvement. Thus ensure: Positive error culture, reflection on practice, Measurement
• System health –quality of relationships. Taking responsibility for the health of the system as a whole. Build networks & positive relationships, nurturing trust
Implications for key commissioning processes
• Relational funding
• Multi-year, unrestricted funding
• Relationship Management –building networks
• Investing in networks: “Building a community” (Public sector commissioner)
• Workforce development –monitoring & data analysis –and time to think: retreats etc
• From Monitoring to Learning
10. Specifically for public health professionals
10a. Address the wrong paradigm issue. PH has a problem in this space
Public health is not like medicine, it is more like social policy
Thus approach to evidence in public health should not be like evidence based medicine
(Maybe we ought to also think about medicine in a complex system way. The body is quite complex)
10b The PH profession has painted ourselves into a number of corners
Hierarchy of evidence – comes from our professions background of biomedical
And short term ROI
It’s a set of tools that may work in heath CARE, but don’t work well in public health, need social policy.
Some aspects rigidly constrained by a biomedical paradigm
NICE works in a biomedical paradigm
Health care system inhabits a biomedical paradigm
A rational response is to accept the responsibility and to actively push away from that, but not abandon it, multiple paradigms have different roles. Don’t throw out tools that other paradigm have given us (aka EBM & RCT paradigm)
But taking them and applying them to a context
Epidemiology & stats are critical can be too reductionist in that context – BUT many stakeholders won’t act till someone has invented expected effect sizes & numerical impact. It’s THIS that drives the (over-) simplification and pushes towards epi – PAF, NNTs etc.
The bottom line message for me is that the work needed is a composite of population and system thinking, but we are only formally educated / trained in population thinking. And – to bring it back to the case in point – I would argue that system thinking provides a useful vehicle as an approach to complexity. We have to rationalise and simplify the complex system in order to tackle it.
10c Skills needed to do public health in a social context are completely different.
Training and competency development around this agenda
FPH curriculum arguably places over emphasis on epi / stats and “traditional” competencies, not complexity stuff (It’s not valued, it’s seen as soft and fluffy)
Focus on educators and redesign syllabus. Let’s crowdsource the competencies needed, what skill sets do we think people in this space need.
10d Learn to talk different languages.
The point of the HEAT tool was to step away from the standard public health model but put it all into the transport economist language.
There are examples of multi lingual system experts in transport, town planning – but they tend to be exceptional rather than the norm.
There isn’t a pamphlet on this. This is a different way of doing the thing called public health
Jim McManus Blog and here. Jim’s webinar slides and website here: Complex Public Health Problems – systems approaches
Using systems science to understand the determinants of inequities in healthy eating – An instruction manual on creating a system map – AKA Foresight Obesity with an inequality twist
the Stacey Matrix – describing decision making in complex systems is an excellent primer in this space around clinical decision making.