Dynamic complex problems in health

Health systems are overwhelmed by complex problems. You know them. The burden of long-term conditions is increasing as our ability to prevent them diminishes; patients quit their treatments due to unanticipated adverse effects or they do not fit their lifestyles; hospitals can be places to get sick rather than well; accident and emergency rooms are overflowing; some people get to access good quality care, others do not; health insurance is complex and inaccessible to many; personal health data is fragmented or non-existent; drug resistance builds; wide discrepancies in key health indicators endure, not just between rich and poor countries but within them as well … of course, there are hundreds more.

Complex problems in health such as these are notoriously difficult to address. Their root causes are multiple, tangled, hard to identify and impossible to extract from their effects. Attempts to resolve one problem can worsen another; they are dynamically linked and deeply nested. Cost savings made in one part of a health system may incur bigger cost increases in another. Seeing, knowing and framing a complex problem is a challenge in itself as patients, practitioners, providers and payers attach different meanings, contexts, priorities, values and assumptions to their importance, as well as how to solve them.

It is little wonder that efforts to resolve these complex dynamic health problems rarely succeed or meet their ambitions. Even the most breakthrough technological innovations suffer from slow or low adoption, contrary to high expectations. The much-promised digital transformation is only gradually coming. They don’t always come if you build it. Change in health systems cannot be driven technologically. Institutions are resistant to disruption from technology. Many new technology interventions, whether drugs, devices or IT systems require just too much effort to introduce, to integrate with or adapt existing practices or to train teams; there is just too much to unlearn. Often, their evidence is insufficiently compelling to persuade people to switch from long-established practices and systems. Clinicians and managers are reluctant to introduce risk or they lack the time or inclination to change entrenched routines. Each new intervention or innovation may even create inefficiency to begin with as users grapple with its adoption. Often, payers simply cannot afford new drugs and devices or make the case to do so when faced with ever diminishing budgets that need to be expended on frontline services.

Despite the promise of rapid technological, medical and scientific advances, health spending is growing and increasingly wasted whilst outcomes plateau or decline. Patients and professionals are ever more dissatisfied whilst their expectations from new technologies, sales visits and the media rise. Conflict and frustration mount whilst underlying problem root causes become more deep-seated and distant from view. The reality is that piecemeal adaptations and interventions are deepening problem complexity further. The healthcare environment becomes overwhelmingly defined by crisis, diverting actors’ attention from real possibilities for transformational change and limiting change efforts to incremental improvements or firefighting only.

Time for a rethink

Complex health system problems persist because we are using problem-solving approaches that are increasingly ineffective to address them. The logic, assumptions and innovation practices in popular use today are incapable of making a significant difference. To better identify, understand and address deeply rooted, dynamic and most of all – human – systemic problems in health (and other complex social systems), I argue we need to develop new, more advanced problem learning capabilities. Especially, we need to rethink the current fad for generative, iterative, solution- and technology-oriented problem solving approaches used commonly under the umbrella term of design thinking.

In a complex health systems context, the penchant for agile, lean prototyping is insufficiently holistic in its understanding of wider system problems, the diversity of actors who experience them, the systemic-level interactions they have with others and the variety of contexts they have to adapt and respond to. Also, trial and learn methods tend to take only a short-term view of the value of the solutions being tested. Often, difficulty arises because the problems they set out to tackle are themselves framed and analysed by the solutions currently being used or the solution being evaluated. Due to these profound limitations, solution-focused practices centred on product, technology and/or experience design and evaluation risk ignoring long-term system wellbeing, can promote further complexity and may even widen the gap in problem understanding. The result? They suffer from low adoption, they do not scale or are not sustained in use. That’s if they get adopted in the first place.

In short, current design thinking approaches in health suffer from what I call the 5S Syndrome:

Their problem framing scope is too narrow, they do not take a wide-enough systems view, they seek to understand problems in the context of solutions, which are too short-term and more often than not address symptoms rather than root causes.

What can be done?

To resolve these limitations, I argue for a greater separation of problem learning from solution design activity. This means that organisations seeking to intervene in complex system problems must first frame those problems independent of the means to resolve them. Having this wider boundary setting allows for the capture of deeper problem and especially, causal factor insight. When made-up of clear, consistent units of analysis, indicators and narratives – also ideally stated free of solutions – problems (now opportunities) are easier to theme, pivot, frame, analyse, compare, share and be assimilated by those tasked with designing value propositions and co-creating solutions. Such problem learning capability is deployed not only when designing completely novel interventions, products and technologies but also on an ongoing basis to improve existing ones.

The ecosystems lens offers much more

Increasingly, health planners and innovators think of health systems as ecosystems, consisting of a mix of interacting stakeholders – patients, practitioners, payers, providers, institutions and government bodies – each with varying goals, needs and desired outcomes.

Whilst the ecosystem concept is largely understood in respect of how it helps identify multiple actors and stakeholders, our understanding of how health systems dynamically function, evolve and adapt is less well articulated. Critically, knowing why they do not function well has clear practical application for complex health problem solving. Indeed, the ecosystems metaphor provides several uses for rethinking and redesigning health innovation and design thinking. It helps innovators to:

  • Understand better how health systems are structured, function, evolve, adapt and sometimes, fail
  • Determine the multiple factors and properties that lead to, and define, complex health problems
  • Reveal new opportunities for addressing complex health problems
  • Reveal a wider set of possibilities or frames for new value propositions (from functional and clinical, to experience, adaptation and transformation); as well as evaluate existing ones for their ecosystem fitness
  • Design a portfolio of health system interventions ranging from the incremental to transformative
  • Create adaptive ecosystem growth and evolution strategies
  • Co-create superior solutions with stakeholders aligned with all the above

Last but not least, an ecosystem lens shows us how to build a dynamic complex health problem solving capability. It tells us what we can do to build design thinking and innovation leadership within organisations that wish to better and continuously address complex health problems. There are four interrelating capabilities involved in this (see figure). I shall write more on these in the future.

Design Value in Health: A Service Ecosystem Framework

The above is a draft extract from my forthcoming publication: Design Value in Health: A Service Ecosystem Framework. To receive a copy when released, please connect, register on the UMIO website or sign up to the UMIO community.

Some useful further reading

Afek A, Meilik A, Rotstein Z (2009). ‘The complexity of medical organizations in the 21st century.’ Harefuah 148(2): 121-4.

Olsson P, Folke C, Berkes F (2004). ‘Adaptive comanagement for building resilience in social-ecological systems.’ Environ Manage 34(1): 75-90.

Keshavarz N, Nutbeam D, Rowling L, Khavarpour F (2010). ‘Schools as social complex adaptive systems: a new way to understand the challenges of introducing the health promoting schools concept.’ Soc Sci Med 70(10):1467-74.

Kernick D (2002). The demise of linearity in managing health services: a call for post normal health care. J Health Serv Res Policy 7(2): 121-4

Nesse RE, Kutcher G, Wood D, Rummans T (2010). ‘Framing change for high-value healthcare systems.’ J Healthc Qual 32(1):23-8.

Lindstrom RR (2003). ‘Evidence-based decision-making in healthcare: exploring the issues though the lens of complex, adaptive systems theory.’ Healthc Pap 3(3):29-35.

Health Foundation (2010) Complex Adaptive Systems http://www.health.org.uk/sites/health/files/ComplexAdaptiveSystems.pdf