Like most countries, Canada faces rising rates of diabetes and diabetic ESRD, which adversely affect cost, morbidity/mortality and quality of life. These trends raise great challenges for financial, human resource and facility planning and place a premium on understanding tradeoffs between different intervention strategies. We describe here our hybrid simulation model built to inform such efforts. To secure computational economies while supporting upstream intervention investigation, we use System Dynamics to characterize evolution of the health, body weight and (pre-diabetes) diagnosis status of nondiabetics. Upon developing diabetes, population members are individuated into agents, thereby supporting key functionality, including accumulation of longitudinal statistics, and investigation of differential treatment regimens based on patient history. Finally, discrete event modeling is used to characterize patient progression through health care processes, so as to capture impact of resource availability, enforce queuing discipline, etc. The paper discusses model findings and tradeoffs associated with the architecture.
Figure 1: Overview of agent-based model structure