With the rise of novel coronavirus cases, hospitals across the United States have become inundated with patients. Due to a severe lack of resources including healthcare workers, personal protective equipment, beds, and ventilators, patients are faced with significant delays for medical treatment. By utilizing California Public Patient Discharge data to examine 1,750,850 patients, this study explores the effect of medical treatment delays on total cost. ‘Delay’ is defined as the number of days between a patient’s initial diagnosis or hospital admission until treatment. ‘Total Cost’ includes the total monetary charge for services rendered during the length of stay at the hospital facility. An OLS regression model with diagnosis fixed effects, hospital fixed effects, and patient-specific controls was used. When running a regression of log Total Cost on Delay, it was found that, on average and ceteris paribus, an additional day of delay resulted in a 10.6 log point (11.2%) increase in total cost. Results were found to be statistically significant (p<0.01). When compared with Day 0 (no delay), a delay of one day increased total cost by 14.1% ($40,619.3USD), 30.5% the second day ($46,443.9USD), 46.5% the third day ($52,156.3USD), 62.9% the fourth day ($57,988.5USD), and 78.4% the fifth day ($63,513.0USD). If we compare a delay of six days to no delay, we find an increased total cost of 95% ($69,424.8), approximately double the cost of treatment of Day 0 ($35,596.4USD). Consequent to our observed correlation between Delay and Total Cost, the magnitude of increased Total Cost could potentially be debilitating for patients and families.