Background:Radiotherapy (RT) time factors are well-established prognostic factor for oral squamous cell carcinoma (OSCC). We investigated the association of a nudge-based intervention for clinicians and time factors in a referral cancer center. Methods:We examined 89 OSCC patients receiving RT at our center between 2015 and 2017. A dashboard displaying dose/time variation between planned values and actual values was used in the electronic medical record since 2015. The association between planned and actual time factors [radiotherapy treatment time (RTT), OP to RT interval (ORI), and treatment package time (TPT)] and time period was analyzed with linear regression after dashboard launching. Autoregressive Integrated Moving Average (ARIMA) model was further used to establish the best-fit model for the intervals of the RT therapy process. Results: After dashboard implementation, the RT duration shortened from 48 days to 38.8 days (p value=0.013), waiting from 35.2 days to 33.5 days (p value=0.002), and total treatment duration from 80.8 days to 76 days (p value<0.001). Estimation of time factors with ARIMA found that the ARIMA model with an auto-regression term of 1, difference of 1, and a moving average term of 1, or ARIMA (1,1,1) model, could both describe and predict the days of RTT, ORI, and TPT well. The mean absolute percentage error (MAPE) for the models were 4.2%, 4.7%, and 2.1% respectively, which implied the models were reasonable for use in the hospital setting.ConclusionsThis study demonstrated that an electronic dashboard with alerts for RT interval can significantly shorten RTT for OSCC patients. Furthermore, AIRMA (1,1,1) provided an estimation of time factors.