Addressing healthcare operational deficiencies using stochastic and dynamic programming

This paper provides an overview of our 10-year research on the application of stochastic and dynamic programming techniques to address health care operational deficiencies in a demand-driven way. We first describe the main operational deficiencies motivating our research in the capacity allocation and scheduling of diagnostic equipment and operating rooms. We then present main findings of extensive field studies to show current practices and key features of the problems under consideration. Applications of stochastic and dynamic programming to these problems are discussed by giving key assumptions, mathematical models, properties of the optimal solution, solution approaches and main numerical findings. The relaxation of the key assumptions is shown to lead to various future research directions that have drawn significant interests of the operations research and industrial engineering communities. We conclude by identifying barriers and potential solutions on the path from theories to applications.