Implementation and Case Study of a Clinical Research Data Warehouse in Radiation Oncology

Abstract

<h3>Purpose/Objective(s)</h3> Radiation oncology generates large volumes of multi-source data that can be harnessed to accelerate personalized cancer care. We describe the implementation of a departmental clinical data warehouse and a case demonstrating application of this tool. <h3>Materials/Methods</h3> Physician stakeholders collaborated with software engineers and developers with domain knowledge in electronic medical records (EMR), cancer registries, and radiation treatment planning systems to design a departmental radiation oncology data warehouse. Data from EMR, radiation treatment planning system, institutional cancer registry, and pathology database were merged by patient medical record number and made accessible via a web application with a graphical user interface (GUI) written in R Shiny and hosted on Shiny Server Pro (RStudio). Data sources are refreshed at weekly to quarterly intervals and extracted to Shiny Server Pro. Team meetings were held every two weeks to refine current data elements, implement process improvements, and improve data quality and integrity. The warehouse can only be accessed by departmental users who have completed data privacy training and attestation under an IRB. Using the data warehouse, we examined radiotherapy fractionation patterns among breast cancer patients in our department. Filters for demographic, prognostic, and treatment characteristics were applied to build cohorts of patients treated with hypofractionated whole breast irradiation (WBI, 2.6-2.7 dose/fraction for 15-16 fractions) and standard fractionated WBI (1.8-2 dose/fraction for 25-30 fractions). <h3>Results</h3> The data warehouse includes 66,078 unique patients seen in our department from 4/28/1997 through 12/7/2021. We identified 2,206 patients diagnosed with breast cancer who received WBI between 2010 and 2020. Use of hypofractionation increased from 16% in 2010 to 71% in 2020. Of the patients who received hypofractionated WBI in 2010, median age was 69 years, 89% had Tis (33%) or T1-2, N0 (56%) tumors, and 67% had right-sided breast cancer, compared to 58 years, 86% (13%, 73%), and 48% in 2020, respectively. Among the patients who received hypofractionated WBI and with known hormone receptor status, 100% in 2010 and 80% in 2020 were ER/PR+/HER2-. These large-scale analyses took minutes to execute and yielded hypofractionation trends similar to those in existing studies. <h3>Conclusion</h3> We created a clinical data warehouse that includes all patients treated in one radiation oncology department and aggregates health information from different data sources into a centralized and user-friendly, web-based GUI console. We used this resource to efficiently examine WBI fractionation patterns in the warehouse over a 10-year period; work is ongoing to continually improve data quality. By leveraging real-time clinical data for secondary uses, this effort can drive precision cancer medicine by making research, quality assessment, and predictive modeling a natural outgrowth of routine patient care.