Techno-Economic Feasibility Analysis of a Fully-Mobile Radiation Oncology System Using Monte Carlo Simulation

Abstract

<h3>Purpose/Objective(s)</h3> Disparities in radiation oncology (RO) care exist, in part, due to geographic barriers in access to care. A first step to mitigate these barriers is the development of a semi-mobile RO system for single-facility, temporary care (∼months), which has been successfully implemented in several locations across the United States. To further address geographic disparities, we investigate the feasibility and financial viability of a fully mobile RO system, capable of delivering RO treatments in multiple geographic locations in a single day through Monte Carlo simulation. <h3>Materials/Methods</h3> A ring-gantry linear accelerator (LINAC) was mounted on a mobile coach that can be transported from one location to another via a tractor trailer. In our model, the mobile coach visits two separate geographic locations within a given day, and a total of three locations in a given two-week period. At each location, the mobile coach is parked within a concrete bay to provide shielding. Timing of setup and quality assurance (QA) testing were evaluated to investigate speed and clinical safety. Monte Carlo simulations were performed in Python to model patient throughput and outside factors, such as traffic, that could affect patient treatments. In this simulation, five-fraction treatment regimens were considered for lung, breast, rectum, and prostate. Cancer census data were collected for Southeastern Missouri to represent the geographic supply of patients. The mobile system was also compared to three separate brick and mortar facilities that would treat the same total number of patients, but equally divided amongst three hypothetical facilities. Statistical and sensitivity analyses were conducted for the simulations to evaluate factors impacting financial viability and feasibility. <h3>Results</h3> Machine setup and comprehensive QA that performs all necessary tests according to national standards, could be performed in < 2.5 hours in most situations, leaving > 5 hours for treatment time and driving. On average, the mobile RO system would see 50.0 breast, 39.6 lung, 14, rectum, and 0 prostate patients within a given year. No overtime was needed to treat any patient under treatment, given simulated traffic or setup delays. Assuming a Medicare patient rate of 50%, a five-year life cycle profit would be 355% ± 125% percentage increase for the mobile system compared to the three separate brick and mortar facilities. The number of patients treated has the highest correlation with profit, r(9998) = 0.44, <i>P</i> = < 0.01, followed by concrete bay construction costs, r(9998) = -.05, <i>P</i> = < 0.01. Sensitivity analysis showed that if there is a 10% decrease in patient population, the profit would decrease by -15%. If the Medicare patient rate decreased to 30%, the patients treated vs. profit correlation would become r(9998) = 0.53, <i>P</i> = < .01. <h3>Conclusion</h3> A fully mobile RO-system is a viable and affordable option for RO delivery in areas that lack RO resources.