Fractal Geometry and the Complexity of Medical Decision-Making

With advances in technology, medical decision-making has become increasingly complex. Fractal geometry provides a framework to grapple with this daunting complexity. Fractals are defined as, 'infinitely complex patterns that are self-similar across different scales.' These patterns have been used to understand the seeming randomness of recurring patterns in nature, financial markets, quantum physics, and even forest fires, war, and the respiratory system. Mandlebrot the mathematician who discovered his eponymous fractal pattern wrote, 'Beautiful, damn hard, increasingly useful. That's fractals.' The same could be said about medicine. To understand optimal medical decision making, we need to examine not only performance, but the complexity-cost to obtain that performance. This complexity can be visualized through the fractal tree of potential branches produced by a plan of care. To confront the growing complexity of medical care, we must prune this fractal tree while ensuring favorable outcomes. To do this, we offer three propositions as pruning shears for the complexity of the fractal tree: wisdom, trust, and prevention.