Business processes may face a variety of problems due to the number of tasks that need to be handled within short time periods, resources' workload and working patterns, as well as bottlenecks. These problems may arise locally and be short-lived, but as the process is forced to operate outside its standard capacity, the effect on the underlying process instances can be costly. We use the term high-level behavior to cover all process behavior which can not be captured in terms of the individual process instances. %Whenever such behavior emerges, we call the cases which are involved in it participating cases. The natural question arises as to how the characteristics of cases relate to the high-level behavior they give rise to. In this work, we first show how to detect and correlate observations of high-level problems, as well as determine the corresponding (non-)participating cases. Then we show how to assess the connection between any case-level characteristic and any given detected sequence of high-level problems. Applying our method on the event data of a real loan application process revealed which specific combinations of delays, batching and busy resources at which particular parts of the process correlate with an application's duration and chance of a positive outcome.