Technology resource planning in radiation oncology: application of a needs-based analytic framework to radiosurgery planning in Ontario.

Abstract

With the emergence of radiosurgery as a new radiotherapeutic technique, health care decision makers are required to allocate capital radiotherapy resources to meet both current and future radiosurgery requirements. The goal of this article is to demonstrate the feasibility of applying an explicit, needs-based model to resource planning in radiation oncology. Using an analytic model that relates radiosurgery need to population size, epidemiology, level of service planned, and productivity, the current radiosurgical need for single brain metastases in Ontario was estimated. The model was populated using Ontario-specific data where possible and supplemented with information from the published literature. Multiway sensitivity analyses were performed to calculate the minimum and maximum technology requirements. The calculated number of full-time radiosurgical units required to treat patients with single brain metastases in Ontario was 5.9. Sensitivity analyses performed varying both level of service planned and productivity yielded a range of requirements from 2.5 to 12.2 full-time radiosurgery units. We have shown through the example of single brain metastases in Ontario that it is feasible to perform explicit, needs-based resource planning in radiation oncology. As the availability of new specialized technology increases, health care decision makers may use this approach to ensure the needs of their population are met while maximizing productivity and minimizing opportunity cost.