Abstract
OBJECTIVE: We used quantitative analytics to assess the efficiency of the clinical workflow for radiation therapy delivery in children and adults focusing on our experience with volumetric modulated arc therapy (VMAT) craniospinal irradiation (CSI). METHODS: We retrospectively collected clinical and treatment specific data between June 2013 and November 2018 for 614 VMAT CSI sessions of 41 pediatric patients and 48 VMAT CSI sessions of 6 adult patients treated at two hospitals within the same academic institution. Descriptive statistics were generated and a multiple linear regression model was created to predict total radiation time (TRT) based on these predictors. Prolonged treatment sessions were filtered using the interquartile range outlier detection method for quality assurance review. RESULTS: The median pediatric TRT for all VMAT CSI treatment sessions was 21.07 min (interquartile range (IQR) 9.05). Pediatric patient height, fraction number (fractions 1-3 vs. fractions > 3), and number of isocenters were significant predictors for TRT (p < 0.01). In the case of adult patients, the median TRT for all VMAT CSI treatment sessions was significantly longer at 37.23 min (IQR 45.92, p < 0.05), even in subgroup analyses comparing plans adjusted for the same number of isocenters and IGRT modality in non-sedated patients. Only in pediatric patients did the median TRT decrease after the first three treatments. Qualitative causal factor analysis revealed plausible causes for prolonged TRT as anxiety, anticipatory nausea and vomiting, challenging setups, anesthesia tolerance, and delay to allow for physician online IGRT review of setup. CONCLUSIONS: Simple descriptive statistics and regression modeling can be used to assess workflow efficiency and estimate radiation treatment times based on patient and technique-specific factors. We modeled VMAT CSI treatment delivery times at our pediatric and adult hospitals to set time expectations for IGRT and beam delivery. Workflow analytics can identify opportunities to minimize time inefficiencies and optimize coordination of care.