Reinforcement Learning (RL) is a Machine Learning (ML) paradigm, used for decision-making tasks, where an agent learns to achieve a specified goal, by interacting with its underlying environment. Compared to the widely explored games and physics simulation problems in RL, real-world RL systems must contend with much more technical challenges. We explore the use of RL in healthcare applications.