OBJECTIVES: Modeling the number of hospital beds needed to cover a hospital patient population for isolated surgical aortic valve replacements (sAVR). METHODS: To simulate the skewed hospital length of stay (LoS) distribution a 3 layered gamma distribution of hospital LoS was fit to the 2014 Medicare Medpar (N=18,889) reported data. Mean LoS was 8.4 days with a 6.4 day standard deviation. One thousand, 52 week (364 day) simulations were created for each hypothetical hospitals with volumes of 1, 5, 10, and 15 sAVR/week. RESULTS:  For a center with 1, 5, 10, and 15 sAVR/week volume, the number of beds required to cover 100% of patients for every one of the simulated 364 day period was modeled to be 6, 13, 22, and 30 beds respectively. When reducing patient day bed coverage rates to 95%, 90% and 80%, scale effects can be seen. Low volume centers see no or lower change in required number of beds when compared to higher volume centers. A 95% coverage leads to a substantial reduction in the number of required beds with 1, 5, 10, and 15 sAVR/week centers only requiring 4, 11, 18, and 25 respectively. 90% and 80% coverage rates for a 1 sAVR/week center remained at 4 beds, while a 5 sAVR/week center had a bed requirement of 10 and 9 respectively. 50% coverage for 1, 5, 10, and 15 sAVR/week centers were projected to be 2, 8, 14, and 19 beds respectively. CONCLUSIONS: Identifying the number of hospital beds needed to cover a patient population is critical in hospital resource planning. Simulating patient LoS variability can provide insight on the estimated number of beds required to service centers of varying isolated sAVR patient volumes and coverage requirements.