Author: James M. Lamb, Jack Neylon, Dylan P. O'Connell 👨🔬
Affiliation: Department of Radiation Oncology, University of California, Los Angeles 🌍
Purpose: Communication is imperative to safe, accurate, and timely radiotherapy. The past decade has seen a significant shift toward higher doses and shorter fractionations, which has in turn led to increased patient throughputs. With busier clinics, higher risk techniques, and heterogeneous clinical systems, there is a clear need for a consolidated hub tracking patients through the clinical workflow with high frequency, fidelity, and availability. Here we describe our efforts to develop and implement a fully automated, web-based, patient tracking dashboard.
Methods: Our clinic previously utilized on-premise, then cloud-based, enterprise software, but these were dependent on manual data entry, which required redundant work and still proved error prone. We identified reliable events in our clinical workflow to signify patient progression, such as new contour sessions, completed appointments, and plan approvals. Application programming interfaces (APIs) were developed to capture these events by directly querying our various clinical systems. One to query the commercial software we use for contouring, another to query our record and verify (RV) appointment schedule, and a third to perform DICOM queries of radiotherapy plans. The retrieved data was housed in a non-relational database, and a web-based dashboard was developed and hosted locally to display pertinent information for current patients.
Results: Our in-house solution has been running in beta for approximately 3 months and has collected over 1000 patients. Extensive logging has facilitated iterative improvements to query logic and frequency. It has demonstrated robustness to myriad of variations in the clinical workflow, including cancellations, rescheduling, and plan revisions. Visual feedback was incorporated to the dashboard through to indicate changes or contradicting information.
Conclusion: As our dashboard exits beta and enters full clinical operation, we are optimistic that it will improve the dissemination of information, reduce miscommunication, and minimize treatment delays, while also providing quantitative insights into our clinical processes.