A Modeling, Health IT, Analytics Framework for Healthcare Management and Application to Diabetes II

We develop a framework using modern Model-Based System Engineering methodologies and apply it to Diabetes 2. We include a Controlled Hidden Markov Chain model for diabetes, three diagnostic tests, ten interventions, three types of patients. We develop three methods for computing tradeoffs between cost and health care quality. One is an exhaustive Monte Carlo simulation and the other two use multi-criteria optimization with full and partial state information. The latter obtain similar results at a fraction of the time of the first. We demonstrate the powerful capabilities of such a framework.