Complexity modeling: Identify instability early

Abstract

Biological systems are innately complex, display nonlinear behavior, and respond to both disease and its treatment in similar complex ways. Complex systems display self-organization and predictive behavior along a range of possible states, often referred to as chaotic behavior, and can be both characterized and quantified in terms of this chaotic behavior, which defined strange attractors (ρ) and variability. In this context, disease can be characterized as a difference in a disease state ρ and a healthy ρ. Furthermore, effectiveness of treatment can be defined as a minimization problem to decrease the phase-state difference between disease and health ρ values, such that effective treatment is defined as the ability to restore the healthy ρ. Importantly, this approach will be effective without anything being known about the physiologic processes that define health or disease. The implication is that this approach is a powerful tool to define the determinants of instability as compared with normal variability, to answer why disease is not healthy, and to identify all potentially effective treatment options independent of known pharmacology and physiology.

Evaluating performance of early warning indices to predict physiological instabilities

“…However, individual vital signs may not provide noticeable changes prior to a critical event [1] and may trigger alarms with low clinical relevance contributing to high alarm rates and alarm fatigue [2]. Warning indices and notification systems that use physiological measurements to produce comprehensive metrics of patient health [3,4] and identify patterns predictive of patient instabilities [5,6] are a promising tool to provide lead time prior to a critical event when effective mitigations can be taken [7]. A sampling of such methods include approaches for identifying need for life-saving interventions in trauma patients [8,9], patients at risk for septic shock in the intensive care unit [10], need for care escalation from step-down units [11–13], and potential heart failure in at-home monitoring [14,15] environments.…”

Physical Exertion Monitoring: Elite Athletes Modify Their Coach’s Task

“…Biological systems consist of numerous different components that are linked together to form a complex system characterized by non-linear dynamics (Pinsky, 2010). However, a system of self-regulation that leads to a single factor within the system does not exist because it determines the entire system.…”

Implications of complexity theory for clinical practice and healthcare organization

“…normal homeostasis) can also be thought of as a complex system characterized by a high degree of biological variability, negative entropy, and emergent order. 4,5 It is this variability that provides us with the resilience to withstand physiological insults. The loss of biological variability, with an attendant increase in entropy, is characteristic of several disease states, including MODS and even normal ageing.…”