Process Orientated Health Care

The current health system of today is episodic, health considerations occur occasionally and at irregular intervals. We are assessed by our doctors at periodic physical examinations and we are treated by our doctors when symptoms of ill-health become evident. In the periods in between, health goes largely ignored; as we often engage in behavior that is deleterious to our health. Health systems are not just fractured by departments and geography they are also are fractured over time – individuals appear on the health system radar when they are sick and then disappear again. Without effective integration between the formal and informal health system, there is huge discontinuity over time making the formal health system reactive instead of adaptive and preemptive.

In a pre-information technology world where we could only see specific events we could only be reactive but today we can increasingly start to move to a model that is proactive. When we have a 360-degree view and pervasive information we can start to see processes instead of snapshots and the challenge becomes one of designing health services and systems that are process oriented instead of just based around specific disconnected events. On the macro-level, of the whole health system, when we adopt a language of systems thinking and start to see health systems as complex adaptive systems our approach inevitably changes from one of specifying future outcomes and directing linear incremental processes of change, to instead looking at the conditions for emergence and processes of evolution.

Health Care Ecosystems

Using this metaphor of the ecosystem to look at health systems can give us a valuable lens with which to see things. It helps us to move away from treating the health system as a massive machine where somebody at the top can pull a lever and make things happen; such an approach typically leads to unintended consequences as we are using a simplified set of assumptions to deal with a complex reality. The linear approach to development works for a short period and then, for example, a new government comes in with a new agenda and we start again – lots of going round in circles, without really having time to measure outcomes. These changes are costly, and often just move issues from one place to another within the system due to a narrow focus on specific metrics and outcomes. How can we shift the model into an evolutionary one where we are building upon past solutions in a modular way?

This starts with a realization that actually we are dealing with this slowly evolved complex adaptive system that has to be seen within bounded parameters; evolutionary innovation that learns from and builds upon the knowledge that is already there; this is health systems as evolutionary networks, as complex adaptive systems. Complex adaptive systems constitute a collection of individual agents that have the autonomy to act in ways that are not always predictable to the observer and whose actions are interdependent so that one agent’s actions changes the dynamic for other agents.

It helps to use biological metaphors to help shift our paradigm from specifying outcomes and expecting linear progression via fixed metrics to creating the context for evolution and emergence; creating conditions in which the system can evolve naturally over time. Provide simple rules and few specifications; create a high-level vision and a wide space for creativity to emerge from local actions within the system.

Complex Adaptive Systems

In a recent publication entitled “Crossing the Quality Chasm: A New Health System for the 21st Century” the authors note two processes in order for CAS to evolve: one, processes that generate variation, and two, processes that select from the resulting variants. Applying this to designing the next generation health care system means combining the many ways to generate and test ideas with ways to enhance the spread of effective ideas and impede the spread of deleterious ideas.

Complex adaptive systems modeling provides a way of looking at health that is focused on defining and understanding the dynamic interrelationships and forces that shape the structure and behavior of health practices through the local interactions and adaptations of actors within the system. A key tool for mapping out this whole macro-scale system is that of system dynamics that is a holistic approach used to identify the feedback loops and how those reinforcing or counterbalancing feedback dynamics create certain behaviors and patterns of development over time.

System dynamic modeling can be very effective when we are looking at resistance to change or a system that is creating counter-intuitive behavior. These systems are adaptive and will keep changing in response to interventions; interventions based upon a static analysis will likely lead only to a partially desired outcome and unintended consequences. Our interventions into health systems are often conceptualized in a simplified manner accounting for only a limited set of variables and not recognizing the adaptive capacity of the agents and that every force has an equal and opposite force that will surface over time in unpredictable ways. System dynamic modeling of feedback loops, stocks and flows give us some chance of getting at how and why the system really behaves the way it does.