V. L. Doss1, E. M. Shupe1, T. R. McNutt1, A. N. Souranis1, S. R. Alcorn2, L. R. Kleinberg1, K. J. Redmond1, and A. W. LaVigne1; 1Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 2University of Minnesota: Department of Radiation Oncology, Minneapolis, MN
Purpose/Objective(s): Uncontrolled symptoms such as anxiety, pain and nausea, whether cancer driven or unrelated, place patients at higher risk of unsuccessful and/or delayed treatment delivery. Patients undergoing radiotherapy courses with lengthier per fraction delivery times and requisite treatment mask use are at particular risk. Such disruptions in care impact not only the patient experience but also the efficacy and efficiency of intradepartmental workflow. We sought to investigate whether proactive identification of patients at high risk for uncontrolled symptoms results in reduced treatment delays. Materials/
Methods: Data collection was limited to patients undergoing stereotactic radiosurgery (SRS) or body radiotherapy (SBRT) using a robotic platform. Preliminary data from 2/24/22 to 6/9/22 identified anxiety, pain and nausea as the most frequent etiologies of delays, which were defined as intrafraction treatment interruptions or inability to deliver treatment. Interdisciplinary staff were trained to screen patients for such symptoms at the time of consult or simulation. A “Treatment Tolerance Risk” alert system embedded in an electronic patient information management system served to preemptively notify therapy teams of identified concern for symptom-related treatment delays and delineate a pre-treatment management plan to minimize this risk. Following alert system implementation, delays were recorded from 3/1/23 to 12/31/23. Chi-square tests and logistic regressions evaluated associations between alerts and delays. Reported statistics are p<.05. Results: Prior to intervention, there were 10 delays for 204 patients treated with SRS or SBRT, equating to 0.049 delays per patient. Of the 432 patients during the implementation period, alerts were placed for 13 patients and 8 delays were recorded, resulting in an observed 0.019 delays per patient. To confirm no temporal difference in delay rates aside from use of alerts in the pre- versus post-intervention cohorts, we used alerts as a surrogate for estimated delays. This revealed a predicted 0.044 delays per patient, verifying no significant difference in pre and post-intervention rate of delays if alerts had not been used. Care alert implementation resulted in statistically significant reduction in the odds of delay by 63%. Conclusion: Proactive identification of patients at risk for experiencing treatment-limiting symptoms and anticipatory management through an electronic alert system can effectively and sustainably reduce treatment delays. These results demonstrate the feasibility of enhancing both quality and efficiency of care delivery through a simple clinical intervention focused on improving the patient experience.
