Refinement of the basic treatment equivalent model to reflect radiotherapy treatment throughput using Australasian...

A model of radiotherapy linear accelerator throughput has been developed and shown to be a more sensitive measure of throughput than current measures of throughput. The present study aims to develop a more sensitive basic treatment equivalent (BTE) model that still measures linear accelerator throughput and considers some of the shortcomings of the previous model. All radiation oncology departments in Australia and New Zealand were invited to participate. Departments were asked to time with a stopwatch all episodes of radiotherapy treatment over a 4-week period. Data collected for each treatment fraction included treatment intent, tumour site, patient age, Eastern Cooperative Oncology Group (ECOG) performance status, number of fields used, number of wedges used, number of junctions, number of shielding blocks used, whether the treatment was the first fraction, the use of general anaesthesia and whether port films or electronic portal imaging was used. Twenty-six departments of radiation oncology (70%) participated in this trial. A total of 7929 fractions of treatment, administered to 2424 patients, were timed. The factors found to most significantly impact on treatment duration on multivariate analysis were the type of fraction (first fraction was longer than subsequent fractions), type of beam (electrons were quicker than photons, which were quicker than mixed), number of fields, number of shields, number of junctions, number of port films and performance status (ECOG < 2 vs > 2). The age of the patient, number of compensators and the sex of the patient were not significant. The relationships between factors were assessed, and models of measuring linear accelerator throughput which consider complexity corrections were derived. It is possible to show that linear accelerator throughput is poorly measured by just considering numbers of patients or fields treated per unit time; and that other factors that impact on treatment duration must be considered. A more sensitive model of patient throughput is suggested; but even when a large number of factors are considered, some insensitivity still remains in the model.