Evaluation of a Prospective Radiation Oncology Departmental Peer Review Process Using Standardized Simulation Directives

IntroductionThe primary objective of this study is to evaluate the utility and value of an institutional, multi-disciplinary radiation oncology team review process prior to radiotherapy (RT) simulation.MethodsOver a period of 3 months and through an iterative team-based process, a standardized simulation requisition directive (SSRD) was developed, piloted, modified, and subsequently implemented for all patients treated with external beam RT at a single tertiary care institution from January to December 2020. The SSRDs were reviewed at a daily multi-disciplinary radiation oncology team review conference; modifications consequential to the review were prospectively recorded in a quality database.Results1500 consecutive SSRDs were prospectively reviewed for this study. 397 modifications on 290 (19.3%) SSRDs were recorded and parsed into 5 main categories and 18 subcategories. The most common modifications resulted from changes in immobilization device (n = 88, 22.2%), RT care path (n = 56, 14.1%), and arm positioning (n = 43, 10.8%). On univariate analysis, modifications were associated with RT intent, scan parameters, tumor site, and consultation type. An increased rate modifications was observed for patients had telemedicine consults (n = 101, 22.7%) compared to in-person consultations (n = 189, 17.9%) (p = 0.032). Using logistic regression analysis, there was also a statistically significant relationship between postoperative RT delivery and modification rates (OR: 2.913, 95% CI: 1.014–8.372) (p = 0.0126). Overall, only 14 patients (0.9%) needed re-simulation during the entire study period.ConclusionsProspective multi-disciplinary radiation oncology team review prior to simulation identifies actionable change in approximately 19% of procedures, and results in an extremely low rate (<1%) of re-simulation. As departmental processes transition to virtual platforms, thorough attention is needed to identify patients at higher risk of simulation modifications.