University of Winnipeg

Research



Systems and Complexity Sciences Applied to Health Systems and Distributed Computing

The Complex Health Systems Group research applies systems and complexity sciences into health systems and distributed computing. Our research is divided in four main areas of work: chronic disease as a complex adaptive system, health systems models to improve care delivery, distributed systems and systems and complexity sciences.

Chronic Disease as a Complex Adaptive System


Chronic Disease

Chronic Disease is long-lasting condition that can be controlled but not cured. Some examples include heart disease, diabetes, chronic lung disease, cancer, allergies, among others. It is also a major cause of premature death around the world. However it is among the most preventable and can be effectively managed. Our research proposes to use Complexity Sciences models to get insights about how all sorts of factors give rise to the appearance of a chronic disease in an individual or at the community level, helping to improve its management, thus people’s health.

Health Systems Models to Improve Care Delivery


Health Systems Models

Care delivery at a clinic/hospital is a web of interrelated elements (people, resources, processes, technology). The clinic is organized in departments that must work (in/out) collaboratively to function, otherwise negative consequences can arise (e.g. wait times, high costs, improper care) The patient requires health services from a holistic view with quality and safety. This research creates health system models to get insights in those hospital interrelations that potentially can help us to improve care delivery and therefore the quality of patient’s health.

Distributed Systems Design and Implementation


Distributed Computing

Modeling and simulating complex systems mechanisms from other realms assist to develop innovate methodology that improves distributed systems design and implementation. This research advances systems research and impact with new approaches based on complex systems to achieve innovative distributed computing systems.

Systems and Complexity Sciences


Systems and Complexity Sciences

Currently there are chaos of language vaguely defined and terms not quite existing in Complexity Sciences (e.g. adaptation, self-organization, emergence, attractors, entropy, bifurcation, nonlinearity among many) . We believe that there is a mathematical language and fundamental theory waiting to be discovered that unifies dynamics, information processing and evolution in complex systems. Our long term goal for this research is to bring together all cross-disciplinary insights obtained from health systems and other related applied research to help us develop a general theory for Complexity Sciences.


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