Theory of complexity
Our quest to create a universal definition of “health”.
There currently exists no single objective metric that defines “health”.
When we prescribe a treatment, is it actually improving our health overall or just fixing certain symptoms? When millions of dollars are on the line, which treatments will actually move the needle?
This inability to objectively measure overall health and therefore the efficacy of treatments is detrimental to health outcomes and costly to public funds.
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Health can be measured as the balance point between pure order and pure chaos
The state of any system can be plotted on an axis of regularity, with complete irregularity (chaos) on one end of the spectrum and perfect regularity (order) on the other.
When the system is at either extreme, it is sub-optimal.
Too much chaos and the system is breaking down and loses control of itself.
This is what the heart rate of a {critically ill heart patient} looks like…
Multiscale Entropy - a quantifiable measure of systemic complexity
{Show how complexity can be quantified - refer to video}
Graph
Graph
Utilizing a measurement of healthiness (via complexity) opens the door to new solutions.
{Describe potential applications of this concept:
Healthcare
Compare treatment options - which will be more effective
More efficient use of public funds - make more objective judgements about which treatments to fund, reducing spend on low efficacy treatments
Personalized treatments
Outside of healthcare
... the same can be applied to systems other than the human body...
Inanimate objects e.g. bridges - likelihood of falling in an earthquake
}
About
The Center for Dynamical Biomarkers (DBIOM) was founded by Prof. Chung-Kang Peng at Beth Israel Deaconess Medical Center, a major teaching hospital of Harvard Medical School. We combine principles from traditional Eastern medicine with modern scientific rigor in our quest to unlock new possibilities in human health.
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