The Heart of Complexity

The Heart of Complexity

Complexity Models + Hard Data =
Solutions to Hard Problems in Health Care

Kevin Dooley, Ph.D.

Why is story-telling important?

How can we tell stories with data? There are ways we can and cannot solve problems using data.
Consider the Learning by Doing model (right). The missing link is, we're not telling stories. We're not making the link between the model and the system.
As we tell stories, it helps to frame the world. However, we can also be biased by those frames.

The Inverse Power Law

The Inverse Power Law is a pervasive model in complex systems.
The Inverse Power Law says small stuff tends to happen a lot, big stuff happens less frequently. This holds true for earthquakes, for example: There are lots of small tremors, but few big disasters. It's true in economic behavior: mostly a stable market with small fluctuations. In evolution: Number of species going extinct is usually very few... but occasionally it's a lot. It's also true in earth temperature changes, music, energy dissipation and waves.
This same pattern keeps showing up in data. People have discovered several different stories in how the inverse power law comes out.

Bak’s Sandpile model

If you drop grains of sand on a table top, it will begin to self-organize into a sand pile. But soon, you can't make the sand pile any higher -- it stays the same height and eventually starts having avalanches. Additional grains of sand you drop will usually have no effect. Many will displace just a few other grains of sand. But sometimes, a single grain will make a huge avalanche happen.
Now think of the avalanches as human behavior. As we look forward to massive connection in our organizations with info technology... we're going past the point of criticality -- like the sandpile that cannot grow in height any longer. We don't need to be superconnected. Not everyone needs to know everything. Intelligence in the future is knowing when not to connect.
Conventional wisdom: If a catastrophe is happening, we look for a catastrophic cause. "What huge collapse in our system occurred?!" And maybe there is one. But it's also likely that it just happens. It's just that single extra grain of sand. By eliminating the causes of small problems, we can also eliminate the causes of severe "avalanches."

Conclusions

We have a problem with data. We spend all of our time collecting and summarizing it... and no time modeling, story telling, and building theory.
We are going 100% in the wrong direction with our information systems. Companies are spending billions of dollars, and most systems are failing. We need localized, specialized information systems.
Our health care systems are complex adaptive systems... Are our Information Systems CAS?
- Do they self-organize?
- Do they exhibit emergent behavior?
- Do they adapt to changes in environment?
- Do they hold "multiple mental models" at once?
We need a bit more "profound knowledge" about statistics and complex systems behavior in health care
Current quality and information systems may be woefully inadequate in their capability to address complex problems in health care arena...
We need look to complexity for additional insights...
Note that Kevin Dooley's overheads can be found at: www.eas.asu.edu/~kdooley/vha98.ppt
For more reading:
- Per Bak, How Nature Works
- West & Deering, The Lure of Modern Science: Fractal Thinking