Parkinson’s disease (PD) is the second most common neurodegenerative disease worldwide affecting up to 3% of people over the age of 65. Common treatments for PD target dopamine, a brain neurotransmitter, and include levodopa and dopamine agonists (DA). However, DA treatment increases the risk of developing an impulse control disorder (ICD), characterized by the inability to control impulses despite self-harm. Recent work has demonstrated that a model consisting of clinical variables, DA and levodopa use, and 3 genetic markers can predict ICD risk in PD patients. How ICD risk affects different domains of human impulsivity, including response inhibition, decisional impulsivity, delayed gratification, risk-taking, and impulsive personality traits, is unknown. We first sought to characterize DA, levodopa or other PD medication exposure in people with PD who receive care at the UPenn PD clinic who are enrolled in the whole-clinic biobanking effort called the molecular integration in neurological diagnosis (MIND) initiative. At enrollment, all MIND participants self-report ICD symptoms. Next, we extracted participants’ medical records to identify those who have a billing code of ICD, impulsiveness, sexual impulsiveness, or impulse disorder. We utilized descriptive statistics to summarize self-report of ICD, medication usage at time of clinical visit, and the demographics of 1475 PD individuals. Participants had an average age of 68 years old (SD = 9), 1343 (91% of total cohort) were White, 950 (64%) were male, and 525 (36%) were female. We find that only a small percentage of participants (4.36%) had an ICD diagnosis in their medical records. This differs from the self-reported frequency of 17.46% for ICD symptoms in the MIND cohort. We then identified study instruments to evaluate different domains of impulsivity in groups of high versus low ICD risk. Future research following this project involves recruiting individuals for clinical impulsivity testing using these study instruments. In addition, we will assign ICD risk scores with their genetic information. The overall goal is to further validate the predictive model to enable future translation into a precision medicine treatment approach for PD patients.