A Quantitative Simulation-based Modeling Approach for College Counseling Centers

TL;DR

This paper develops a detailed simulation model for college counseling centers to evaluate policy impacts on wait times and service quality, addressing resource challenges amid rising demand.

Contribution

It introduces a novel quantitative simulation framework capturing complex operations, enabling data-driven policy analysis for counseling center management.

Findings

Simulation accurately predicts system performance under various policies.

Key policy changes can significantly reduce wait times.

Model provides actionable insights for resource allocation.

Abstract

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.