Find patients likely to come back within 30 days, read the tree's rules and stop it from memorising.
New to this? See the worked example firstA decision tree learns if-else questions, such as which discharged patients are likely to come back within 30 days. In these questions you read the tree's splits, Gini impurity and rules, and control its size with depth, leaf size and pruning.
Interviewers like trees because you can explain them, and because they show overfitting so clearly.
If you are new to it, read the worked example first, then solve the questions in order: the early ones explore the data and train a first model, the middle ones test it on rows it has not seen, and the last ones tune it and turn the result into a business decision.