PROJECT SUMMARY
Agitation is defined as excessive psychomotor activity leading to aggressive and violent behavior in patients
and is often due to exacerbation of underlying serious mental illnesses. Those presenting with agitation in the
emergency setting represent the most marginalized populations. Coercive measures like physical restraints are
currently used routinely on agitated individuals, but are associated with physical trauma, apnea, and death.
Recent studies have shown disproportionate use of physical restraint on Black patients, those who are
homeless, and those with public or no insurance. At the same time, healthcare workers experience stress and
burnout from episodes of workplace violence by agitated patients, leading to reinforcement of negative
attitudes and bias towards marginalized individuals. Interventions to address disparities during psychiatric
crises have been hindered by increased boarding, overcrowding, and other system-based challenges. System
dynamics modeling is a rigorous method that uses advanced mathematical equations and simulations to study
complex systems and identify causal structures that evolve over time. This approach allows us to measure,
predict, and improve health equity and value during agitation care. Our overall objective is to apply systems
dynamics modeling to identify and quantify modifiable targets for reducing disparities in agitation management
and assess benefits and costs of potential interventions addressing those targets across diverse populations
and marginalized groups. To achieve this objective, we will use group model building focus groups (Aim 1) to
adapt our existing qualitative model of agitation care and merge key insights from clinicians, administrators,
security/police, minority patients, and prehospital services to focus on health equity. We will then create a
mathematical model and incorporate existing datasets of patient records, staff injuries, and survey responses
into the model, calibrating quantitative outcomes of restraint use and staff assault and validating parameters of
the relationships established in the qualitative model (Aim 2). Finally, this expanded and validated model will
guide participatory design sessions with stakeholders in an iterative process where computational simulations
for outcomes on equity can be created and predicted in real-time on proposed interventions across three sites
(Aim 3). This will allow us to translate research findings from the model into practice to assist hospital
leadership in deciding if implementing potential interventions is warranted.
This proposed work will make a positive contribution to mental health research by describing, measuring, and
predicting bias and discrimination against minority and socioeconomically disadvantaged individuals with
psychiatric emergencies. Our study is highly innovative as it will be the first to address staff safety and patient
advocacy as one unified issue and applies simulation modeling and systems science methods to address the
understudied topic of agitation management and reduce health disparities in psychiatric emergency care.