Background: Diabetes and its related complications and comorbidities (C&Cs) represent a significant and increasing healthcare burden. Absence of a systematic manner to evaluate value propositions of technologies from various stakeholders' perspectives impedes the best uses of current and emerging technologies.
Methods: A system dynamics methodology was used to develop a comprehensive causal simulator of the U.S. population and give proof of principle that entire portfolios of present and future technologies can be evaluated for direct and indirect impacts. An explicit semiquantitative methodology was used for surveying, prioritizing, and grouping C&Cs, patient subgroups, and technologies, utilizing diverse publicly available clinical literature.
Results: The resulting model simulates the incidence and prevalence of diabetes and 10 of its most commonly associated C&Cs, reflecting their interrelated upstream and downstream relationships. The simulator enables systematic evaluation of tens of thousands of potential combinations of emerging technologies and technology leverage points that can be used to improve patient outcomes and guide technology investments. Feasibility was demonstrated through single, pair-wise, and targeted analyses of technologies.
Conclusions: This effort demonstrated the feasibility of linking complex, interconnected disease states, impact points, outcomes, and interventions with a variety of outcome metrics, to an extent greater than existing models developed for other purposes. The project demonstrated the ability to identify priority technologies and pipeline therapies and leverage points among diabetes interventions. It demonstrated more effective knowledge management of diverse information essential for formulating strategy that could be applied in a wide range of therapeutic applications and technology innovation uses.