To Be Healthy, Wealthy, and Wise: Using Decision Modeling to Personalize Policy in Health, Hunger Relief, and Education

Abstract

Decision-making to satisfy the basic human needs of health, food, and education is complex, accomplishing this in such a way that solutions are personalized to the needs of the individual has been the focus of my research. This chapter will present an overview of my research with several of my former students in the area of decision-making under conditions of uncertainty with a focus on human-centric decision problems in three primary areas: health care, humanitarian logistics, and education. This research seeks to inform decision-making with the goal of improving decision quality. To this end, this research utilizes and develops theory in the areas of Markov decision processes (MDPs), semi-Markov decision processes (SMDPs), partially observable Markov decision processes (POMDPs), optimization, simulation, and Bayesian decision analysis to address these real-world problems. This research has made an impact on how researchers and practitioners address complex societal issues, such as health disparities, public health preparedness, hunger relief, student performance, and personalized medical decision-making.