  College counseling centers in various universities have been tasked with the
important responsibility of attending to the mental health needs of their
students. Owing to the unprecedented recent surge of demand for such services,
college counseling centers are facing several crippling resource-level
challenges. This is leading to longer wait times which limits access to
critical mental health services. To address these challenges, we construct a
discrete-event simulation model that captures several intricate details of
their operations and provides a data-driven framework to quantify the effect of
different policy changes. In contrast to existing work on this matter, which
are primarily based on qualitative assessments, the considered quantitative
approach has the potential to lead to key observations that can assist
counseling directors in constructing a system with desirable performance. To
demonstrate the benefit of the considered simulation model, we use data
specific to Texas A&M's Counseling & Psychological Services to run a series of
numerical experiments. Our results demonstrate the predictive power of the
simulation model, highlight a number of key observations, and identify policy
changes that result in desirable system performance.
