Modeling the adoption patterns of new healthcare technology with respect to Continuous Glucose Monitoring

This paper develops a model that explains trends and relationships between factors that affect the adoption patterns of continuous glucose monitoring (CGM) devices for diabetes patients, hoping ultimately to develop a predictive tool that can inform stakeholders (patients, doctors, insurance companies, and CGM device manufacturers) about the long-term economic prospects associated with this emerging technology. To describe the methodological approach, we have adopted an agent-based framework due to the large number of independent decision makers involved in CGM adoption. After studying the industry, we have identified the principle stakeholders in healthcare as patients, physicians, device manufacturers, and insurance providers, who interact with one another in complex ways, with the nature of the interaction being highly asymmetric. The model is instantiated as an agent-based simulation using the freeware NetLogo to be implemented as a web-based application. Agent creation and representation are supported with data that reflects the dynamic relationships found within the healthcare industry between the principle continuous glucose monitoring stakeholders. A broader impact of this work is that it provides a design methodology and solutions for constructing these models for systems with multiple independent decision-makers.