A Dynamic System Model for Personalized Healthcare Delivery and Managed Individual Health Outcomes

The current healthcare system is facing an unprecedented chronic disease burden. This paper develops a dynamic mathematical simulation model for personalized healthcare delivery and managed individual health outcomes. It utilizes a highly novel hetero-functional graph theory, most easily understood as an ontological convergence of model-based systems engineering and network science, along with Petri nets. The dynamics of the model builds upon a recently developed systems architecture for healthcare delivery, which bears several analogies to the architecture of mass-customized production systems. At its essence, the model consists of two synchronized Petri nets; one for the healthcare delivery system and another for individuals’ health state evolution. The dynamic model links logistical and medical phenomena using a combination of a deterministic Petri net model for the former and a fuzzy Petri net for the latter. The model is demonstrated on two clinical case studies; acute and chronic. Together, the case studies show that the model applies equally to the care of both acute and chronic conditions, transparently describes health outcomes and links them to the evolution of the healthcare delivery system and its associated costs.