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Departmental Quality, Safety and Health: Predicting Dosimetry Staff Stress Levels and RO-ILS Events as a Function of Planning and Scheduling Metrics

RG Price*, Y Huang, BJ Salter, University of Utah - Huntsman Cancer Institute, Salt Lake City, UT

Presentations

PO-GePV-T-195 (Sunday, 7/10/2022)   [Eastern Time (GMT-4)]

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Purpose: The ebb and flow of treatment-planning volume and its effect on department health and safety can be challenging to manage. We sought to facilitate this by capturing changing stress levels of all department dosimetrists and evaluating them with respect to planning volume and treatment-plan workflow metrics, using data from our treatment-planning workflow software.

Methods: For 20 months, an in-house script delivered a daily, one-question stress-level survey to every dosimetrist computer in order to collect data on the changing stress of the dosimetry team. Stress level was self-reported, and was based on a 1-5 scale, with 1 being low stress, 5 being high stress. This data was compared to total number of treatment plans ‘in progress’, the number of plans that were ‘behind schedule’, and the occurrence of reported ROILS events.

Results: Average stress level across all 20 months was 2.5±0.6. Daily average stress level across all dosimetrists correlated with total number of treatment plans on the dosimetry worklist with a Pearson Correlation Coefficient of 0.41, and 0.43 for the number of ‘delayed’ plans. For all 153 days that included a recorded ROILS event, 62% occurred when the total number of patients was above average, and 58% when there was an above average number of plans behind schedule. Additionally, for all 55 days that included a Treatment-Planning-related ROILS event, 62% occurred when the total number of active plans was above average, and 71% when there was an above average number of plans behind schedule.

Conclusion: Overall, dosimetry stress level was dependent on the number of treatment plans in-progress and the number of delayed treatment plans. Both corresponded to higher likelihood of a recorded ROILS event.

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