Background: The cardiac catheterization lab (CCL) can be a fast-paced and unpredictable setting, as the staff must balance inpatient, emergent, and outpatient cases, which can make the CCL susceptible to inefficiencies. The goal of this project is to improve the efficiency of the CCL by reducing unnecessary patient wait times. Methods: Lean and Six Sigma methods were used in this project. Outpatients were timed from the point that they entered the waiting area of the cardiology unit to be checked in to the point that they left the CCL after recovering from the procedure. This was a convenience sample; it does not represent all outpatients that entered the CCL during the collection period, and not all patients were consecutive. The major stages of the patient experience in the CCL were mapped to include value and non-value adding steps. Results: We collected data on 89 outpatients presenting to the Michael E. DeBakey VA Medical Center CCL for elective procedure between June 20, 2018 to October 30, 2018. In the current state, patients are asked to come at the same time the morning of their procedure. The first patient who arrived in the morning would wait an average of 58 minutes for their procedure (n=36), the second patient 110 minutes (n=26), the third 188 minutes (n=17), and the fourth patient 240 minutes (n=7). The process mapping revealed that the largest contributors to wait time were: waiting upon arrival to be checked in, (28.9% of total time 37.3/129), waiting before nurse prep (11.1%, 14.4/129), waiting in the holding area after nurse prep (52%, 67.1/129), and waiting during the procedure (7.9%, 10.2/129). Patient timings additionally revealed that turnover rate of rooms in the CCL was not heavily influenced by janitorial delays. Time spent cleaning the room after a procedure was less than 20% of the total turnover time (10.8/57.7), whereas the majority of the turnover time consisted of the room being unused. Conclusion: We found that patient arrival order determined total wait time, waiting in the holding area after nurse prep contributed most to total patient wait time, and janitorial delays did not heavily influence turnover rate. In our next step in this work, we will design a ranking system that allows clinicians to rate the likelihood that their patient will undergo an intervention to allow staggering of scheduling patients. Currently, all patients are asked to come at the same time in the morning, which leads to 4 hour wait times for the fourth patients that arrive. Instead, the CCL can use this ranking system to stagger patients throughout the morning so that more complex interventional cases are scheduled last and those corresponding patients come later in the morning/wait less throughout the day. The next steps of this project include implementing proposed recommendations with input and guidance from the CCL team and measuring patient wait times after interventions are implemented.