Improving the performance of the healthcare sector requires an understanding of the effectiveness and efficiency of care delivered by providers. Although this topic is of great interest to policymakers, researchers, and hospital managers, rigorous methods of measuring effectiveness and...

In a variety of applications, decisions needs to be made dynamically after receiving imperfect observations about the state of an underlying system. Partially Observable Markov Decision Processes (POMDPs) are widely used in such applications. To use a POMDP, however, a decision-maker must have...

An important contributor to the well-known problem of Emergency Department (ED) overcrowding is prolonged boarding of patients who are admitted through the ED. Patients admitted through the ED constitute about 50% of all non-obstetrical hospital admissions, and may be boarded in the ED for long...

Addressing hospital emergency department (ED) overcrowding is a critical challenge for many healthcare systems worldwide. Many hospitals (including our partner hospital) have been experimenting with innovative patient flow designs to address this challenge. A promising new design is to separate...

In various organizations including hospitals, individuals are not forced to follow specific assignments, and thus, deviations from preferred task assignments are common. This is due to the conventional wisdom that professionals should be given the flexibility to deviate from preferred...

Problem definition: The recent upward trend in the U.S. hospital closures can have important impacts on the healthcare sector by changing the operational efficiency and quality of care of the remaining hospitals. Understanding how hospital closures impact the way the remaining hospitals operate...

Understanding potential channels through which physicians impact each other's performance can yield new insights into better management of hospitals' operations. We use evidence from Emergency Medicine to study whether and how physicians who work alongside each other during the same shifts...

Intervention policies, like stay-at-home orders, are shown to be effective in controlling the spread of the novel Coronavirus Disease 2019 (COVID-19). However, concerns over economic burdens of these policies have propelled U.S. states to move towards reopening. Decision-making in most states...

This chapter develops a novel approach to predict post-money valuation of startups across various regions and sectors, as well as their probabilities of success. Using startup funding data and descriptions from Crunchbase over a ten-year period, we develop two models linking information such as...

There is a growing amount of evidence that machine learning (ML) algorithms can be used to develop accurate clinical risk scores for a wide range of medical conditions. However, the degree to which such algorithms can affect clinical decision-making is not well understood. Our work attempts to...