Long wait times is one of the most common complaints from patients visiting the glaucoma clinic at the Kellogg Eye Center at the University of Michigan (UM). Long wait times have also been reported as a barrier to glaucoma care in other clinics as well. To address this issue, we develop a discrete-event simulation model to identify bottlenecks in the clinic that cause the majority of patient wait time. Different policies in terms of resource supplementation, i.e. adding staff and the corresponding equipment and exam rooms, are then accordingly proposed. We evaluate each of them using our simulation model through a series of what-if experiments. The most beneficial policy, considering the trade-off between patient wait time and resource supplementation expense, is proposed to the clinic to carry out in practice.