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Se Young Choi(최세영),Ho Heon Kim(김호헌),Bumjin Lim(임범진),Jong Won Lee(이종원),Young Seok Kim(김영석),Jeong Kon Kim(김정곤),Jae Lyun Lee(이재련),Yong Mee Cho(조영미),Dalsan You(유달산),In Gab Jeong(정인갑),Cheryn Song(송채린),Jun 대한비뇨기종양학회 2021 대한비뇨기종양학회지 Vol.19 No.4
Purpose: To construct a urologic cancer database using a standardized, reproducible method, and to assess preliminary characteristics of this cohort. Materials and Methods: Patients with prostate, bladder, and kidney cancers who were enrolled with diagnostic codes in the electronic medical record (EMR) at Asan Medical Center from 2007–2016 were included. Research Electronic Data Capture (REDCap) was used to design the Asan Medical Center-Urologic Cancer Database (AMC-UCD). The process included developing a data dictionary, applying branching logic, mapping clinical data warehouse structures, alpha testing, clinical record summary testing, creating “standards of procedure,” importing data, and entering data. Descriptive statistics were used to identify rates of surgeries and numbers of patients. Results: Clinical variables (n=407) were selected to develop a data dictionary from REDCap. In total, 20,198 urologic cancer patients visited our institution from 2007–2016 (bladder cancer, 4,616; kidney cancer, 5,750; prostate cancer, 10,330). The overall numbers of patients and surgeries increased over time, with robotic surgeries rapidly growing over a decade. The most common treatment for urologic cancer was surgery, followed by chemotherapy and radiation therapy. Conclusions: Using a standardized method, the AMC-UCD fosters multidisciplinary research. This constructed database provides access to clinical statistics to effectively assist research. Preliminary data should be refined through EMR chart review. The successful organization of data from 2007–2016 provides a framework for future periods of investigation and prospective models.