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Background: A Physician Assistant (PA) degree is earned during a high-intensity, fast-paced, and academically challenging graduate-level program that can be anxiety-inducing for students. The exam schedule and amount of material can be overwhelming and result in a disruption of healthy sleep patterns. Purpose: This research is intended to determine if there is a correlation between physician assistant students’ sleep schedules and their overall academic performance. Methods: Current didactic year PA students across the US, using convenience and snowball sampling methods, were asked to complete an anonymous survey about their sleep habits and performance in their medical education and pharmaceutical courses. This survey was developed on the SurveyMonkey platform and based on a similar study using pharmacology students. This survey was then piloted with 10 current PA students who met inclusion and exclusion criteria. After minor alterations, the approved survey was open to participants for 6 weeks. After the collection was complete, an independent statistician analyzed the results. Descriptive statistics and correlation analysis were calculated. In addition, a Chi-squared test was performed to assess associations between study variables, and a T-test was used to compare mean results. Results: The final sample was 234 respondents, a 75% completion rate. There was no correlation found when comparing academic performance to the amount of sleep before exams, grade point average, daytime sleepiness, sleep in an average week, or wake time. There was a significant difference (p< 0.0001) between hours of sleep before an exam versus an average week. iv Conclusion: The results of this research allow PA programs and students to see the significant differences in sleep before an exam. Future recommendations for research include using realtime study over multiple weeks using an easy tracking method to improve response accuracy and account for variables such as weeks with and without examinations/competencies. Accessing a larger sample size would also help improve external validity.