Changing mindsets and getting groovy to effect change in complex settings

In a public-sector context, failure is a type of learning that dares not speak its name

“For every complex problem, there is an answer that is clear, simple and wrong.” So said Amer­ican journalist and professional curmudg­eon H. L. Mencken, who was always good for a quote. In health policy, there are an infinite number of clear, simple and wrong solutions to complex problems. But what do we mean by “complex”, and how do we navigate a health policy world that is beset with complexity?

One of the most stimulating and exciting intellectual developments of the past 30 years has been the growth of “complexity theory” which draws from evolutionary bi­ology, physics, economics and information science. Com­plex is different from complicated. Complicated problems are intricate, but can be solved step by step, like a Rubik’s cube or a cryptic crossword.

Complexity dynamics are likely when there are multi­ple, competing values and criteria of success and where no solution is optimal at all times under all conditions. Complex problems are embedded in complex contexts. Response to complex problems evolve continually, as does the nature of the problem.

In evolutionary biology, species evolve in the context of their environment, which includes the evolution of other species they might want to eat, or that might want to eat them. Figuring out a strategy to survive today doesn’t mean the same strategy will work tomorrow. As the en­vironment changes, so does the nature of the trade-offs between conflicting criteria.

The most important implication is that no one is in con­trol of a complex system (I know this is a mantra of this column). Sure, some people, some groups, some actors have much more capacity to shape what goes on around them than others, but that should not be mistaken for control. Think of any professional sport. Coaches do not control the evolution of a sport – they might be the most influential par­ticipants, but the best they can do is to adapt to the environment created by their fellow coaches, players and officials, and the best coaches are those who are the most adaptable. Those who write the rule book of a sport are constantly re­acting to innovations that evolve within the con­text of the game.

Complexity thinking also requires a mindset that goes beyond a “dose-response” view of how the world works. In this mindset, for every given input of energy (eg, funding, staffing) there will be a proportion­ate increase in some outcome. Most of us are conditioned by our education to think of dose-response patterns as normal, and other scenarios as abnormal.

Complexity thinking flips this. Dose-response thinking only works when all other aspects of the environment are known and controllable – which in any area of public policy is pretty much never. Complex environments can­not be “modelled” in order to improve predictability – there are too many moving parts, parameters and criteria of success. Prediction is a mug’s game.

In complex systems, inputs of energy are subject to negative or positive feedback. Negative feedback, or “dampening”, refers to large inputs of energy resulting in minimal change. Think of the myriad efforts to achieve interoperable electronic health records, for example. His­torical happenstances cut a deep groove that manifests in different forms over time but is extremely difficult to get out of.

In complexity jargon, this is called “sensitivity to initial condition”. The best example in New Zealand is the cre­ation of the right to charge copayments in primary care. No one could have understood the multiple implications of this back in 1940. But the upshot is that any attempt – be it by a minister of health, a DHB or a PHO – to im­prove access to primary care services has to deal with this fundamental force of gravity in primary care.

On other occasions, a minor and seemingly insignifi­cant input can foster massive change: positive feedback, or amplification. This can tip – as in Canadian writer Malcolm Gladwell’s “tipping point” – systems from one groove to another. The almost-accidental creation of Pharmac in 1993 is one such example in New Zealand’s health policy history.

Complexity also puts an interesting lens on the buzzword “innovation”. If we take biological evolution as an example of a complex system, most improvements in the fitness of a species are generated by mutations. But for every mutation that provides an evolutionary advantage, there are countless others that do not, or are harmful. Only a small subset of innovations end up being useful. We can see this dynamic very clearly in the development of new pharmaceuticals, but it applies just as well to the world of policy.

In health policy, we need a mindset that tol­erates and anticipates that most attempts to improve things will not work, but a handful will. However, in a public-sector context, failure is a type of learning that dares not speak its name, lest it be construed as a drain on the public purse and an indication of the incompetence of govern­ments. (Imagine if we applied that thinking to the development of pharmaceuticals!) It is also challenging when there is a tendency, ampli­fied by news media, to think anything that goes wrong or fails in the health system could have been readily anticipated and predicted.

Complexity thinking, therefore, challenges our habits of thinking about democracy and accountability in our health system, which have been rooted in a dose-response mindset. If these values are to remain useful, the mean­ings of these words will also need to evolve to reflect the realities of a complex, adaptive health system.

Tim Tenbensel is associate professor, health policy, in the School of Population Health at the University of Auckland