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In the wake of a national mental health crisis exacerbated by the COVID-19 pandemic, Leavey School of Business professors are stepping up to offer innovative, data-driven solutions to one of higher education’s most urgent problems: how to respond swiftly and effectively when tragedy strikes a campus.

Amber Xiaoyan Liu, Assistant Professor of Information Systems & Analytics, alongside fellow Leavey professors, Wilson Lin and Hussein El Hajj, is breaking new ground with research that focuses on operational strategies in mental health care. Specifically, how university counseling centers can better prepare for surges in demand following tragic events, such as student deaths.

The inspiration behind Liu’s work came after witnessing the painful aftermath that followed multiple student suicides at Santa Clara University. Many students expressed a heartbreaking wish, that better help had been available when they needed it most. Determined to turn that grief into action, Liu and her coauthors gathered recent years of data from a Counseling and Psychological Services (CAPS) center and launched a rigorous study combining empirical causal inference with optimization methodologies.

The team’s findings are eye-opening. In the immediate aftermath of a tragic event, students were 131% more likely to book an appointment with CAPS. Even more strikingly, those within the same social or academic cohort as the deceased were disproportionately represented among the help-seekers. These patterns underscore that crisis events send shockwaves through the community, triggering an urgent, widespread need for mental health services. “While prior research has primarily examined the psychological or emotional impact of crises on survivors, our study offers empirical evidence on how such events influence mental health service-seeking behavior,” Liu emphasizes. “Identifying this behavioral change in mental health service-seeking helps us anticipate surge in demand.”

However, meeting that surge in demand induced by a crisis isn’t easy. University mental health centers often face resource constraints, and traditional crisis response models fall short. Liu’s research critiques two commonly used approaches: the “myopic” strategy, where all available resources are exhausted immediately following an event, and the “empirically informed fixed reservation” strategy, where some resources are heuristically saved for later but not strategically deployed. Both approaches often fail to balance immediate needs with long-term accessibility.

That’s where a multi-period optimization model comes in. Designed to guide CAPS and similar organizations in allocating their budgets and staffing levels more intelligently and effectively, the model anticipates demand fluctuations over time. It weighs when and how many mental health clinicians should be added in the immediate time window (e.g., days) following a tragic event, not just to meet the immediate rush, but to ensure sustained support. By looking at historical, real-time, and projected data, and leveraging the rigorous empirical estimation of crisis-induced demand surge, the model provides a rolling-horizon framework that can drastically improve decision-making.

“Our model is two steps ahead,” Liu explains. “It doesn’t just react to a crisis. It prepares for the next one, while also making sure help is available today. Our goal is to enhance access to care, making sure that CAPS has the least number of unserved students possible following a crisis through better resource allocation.”

With findings that offer valuable insights and practical implications for universities nationwide, the project is being prepared for submission to a leading peer-reviewed academic journal in the field of Operations Management. Liu and her coauthors look forward to continuing their collaboration with CAPS on future research. Their next goal is to work directly with CAPS on a pilot implementation phase—translating theory into practice and gathering feedback to further refine and strengthen the model’s effectiveness.

Beyond its scholarly value, Liu’s work speaks to a larger mission: empowering institutions to meet students where they are, especially in moments of vulnerability. By combining causal inference and operations research with compassion, this project represents the very best of what business research can do, solving complex problems in service of human well-being.

At its core, Liu’s work exemplifies the Leavey School of Business’ commitment to using business tools for social good. In an age when student mental health is more critical than ever, her research offers not just insights, but a real path forward. When tragedy strikes, thanks to work like this, universities may finally be ready to not just respond, but to truly support.