163 Background: In the current era of rapid advances in cancer care, economic burden of these treatments is becoming increasingly apparent. Measures taken by Centers for Medicare & Medicaid Services (CMS) such as closely monitoring length of inpatient stay might be inadequate in their goal to curtail costs. SEER analysis shows a 5-year overall survival for prostate cancer of 98.2 % and incidence of 179.1 in 2000 versus 97.8 in 2015 per 100,000, respectively. This encouraging result comes at the cost of increasing healthcare costs. Methods: We used National Inpatient Sample (NIS) database to extract data for patients hospitalized with primary diagnosis of prostate cancer using ICD-9 code 185. The 15-year time from 2000 till 2014 was analyzed. The metrics focused on were mean length of stay (LOS), mean cost of hospitalization and rate of discharges. Results: Discharge rate was 32.2 +/- 1.3 in 2000 versus 20.4 +/- 0.8 in 2014 per 100,000, respectively. Mean LOS declined from 3.7 +/- 0.115 days in 2000 to 2.2 +/- 0.044 days in 2014. During this same time period mean hospitalization charges increased from $14,680 +/- 466 to $49,464 +/- 1,019. The average annual inflation rate during this time period was 2.26%. After adjusting for inflation, the cost of stay in 2000 was $20,072 versus $49,464 in 2014. This effect is magnified when analyzing the cost per day of hospitalization. Cost per day in 2000 was $5,424 versus $22,483 in 2014. Conclusions: The increase in cost of inpatient stay is likely due to the advances in multi-modality treatment in prostate cancer. With the aging population and focus on cost conscious allocation of resources, this increase in costs will remain a challenge for hospital decision makers and insurance companies. We have to apply models such as the Markov model that are increasingly used to justify exorbitant prices of individual drugs. Also, given the complexity of health care costs, more variables should be included to rationalize health care spending. Cost metrics such as LOS are out dated given costs of treatments will continue to exceed costs such as nursing care and room and board costs. These complex analyses might be feasible with advances in deep learning which enable consideration of multiple variables in the decision-making process.