Health systems are increasingly expected to anticipate and manage complex, interconnected issues, including aging populations, increasing costs, and the threat of climate-related illnesses—often through simulation modelling for healthcare to explore dynamic scenarios and outcomes.
But their digital tools are antiquated, fragmented and siloed.
We know that digital toolsets that assist and transform healthcare networks aren’t just valuable assets—they save lives. Simulation modelling for healthcare is a proven method to understand system behavior, and health state modeling enables clinicians and planners to explore evolving patient conditions and outcomes before decisions are made.
We know that equity-focused policies and de-risked plans lead to better patient outcomes. These have both been primary applications of RWI’s Synthetic Twins from the start, supported by sophisticated health state simulation and health modeling software that answer “what if” questions at scale.
RWI enables proactive, data-driven preparedness and health system planning through dynamic synthetic populations and simulation scenarios. We generate and validate Synthetic Population data that includes relevant health attributes and disease conditions, such as air quality, co-morbidities, and relationships between transit access and mental health, thereby significantly improving resource allocation efficiency through health state modeling and simulation modelling for healthcare.
Health attributes are inseparable from the human condition. When our Synthetic Twins model reality, we ensure the equation always accounts for the physical well-being of people and populations using cutting-edge health modeling software that supports both operational and strategic planning through health state simulation.
When our Synthetic Twins model reality, we ensure the equation always accounts for the physical well-being of people and populations.
What We’ve Done
RWI is receiving advisory services and funding from the National Research Council of Canada’s Industrial Research Assistance Program (NRC IRAP) to support research and development in mapping disease conditions into rural and remote synthetic populations. This effort aims to health state modeling within connected care interventions using advanced simulation modelling for healthcare and emerging health modeling software to model, analyze, and visualize the deployment of connected care solutions—enhancing how health systems prepare for future challenges.